Papers with no author rows
| lom_id | title | year | arxiv | openalex |
|---|---|---|---|---|
| arxiv:2601.14525 | Towards Execution-Grounded Automated AI Research | 2026 | 2601.14525 | W7125390180 |
| arxiv:2602.02660 | MARS: modular agent with reflective search for automated ai research | 2026 | 2602.02660 | W7127617026 |
| arxiv:2602.06855 | AIRS-Bench: a Suite of Tasks for Frontier AI Research Science Agents | 2026 | 2602.06855 | W7128395166 |
| arxiv:2604.09805 | Building an Internal Coding Agent at Zup: Lessons and Open Questions | 2026 | 2604.09805 | |
| arxiv:2605.03546 | ProgramBench: Can Language Models Rebuild Programs From Scratch? | 2026 | 2605.03546 | W7160416041 |
| arxiv:2605.05076 | High-Dimensional Statistics: Reflections on Progress and Open Problems | 2026 | 2605.05076 | |
| arxiv:2605.29885 | Open Problem: Separating Geometric and Algorithmic Compression via Cayley-Table Completion | 2026 | 2605.29885 | |
| arxiv:2605.30389 | The Inclusion Depth of Pattern Languages: An Open Problem in Algorithmic Learning Theory | 2026 | 2605.30389 | |
| arxiv:2606.07327 | Six Open Questions in Machine-Learned Interatomic Potential Foundation Models | 2026 | 2606.07327 | |
| arxiv:2607.04129 | Toward the Right Analytical Model and System Software for Autonomous Driving Systems: Open Problems and Research Directions | 2026 | 2607.04129 | |
| arxiv:2607.07851 | Kime-Representation Formulations of Three Open Problems in the Foundations of Classical Mechanics: Uncertainty, Invariant Entropy, and Directional Degrees of Freedom | 2026 | 2607.07851 | |
| arxiv:2607.12870 | A Survey on Code Equivalence: The State-of-the-Art and Open Questions | 2026 | 2607.12870 | |
| arxiv:2608.01206 | On three open problems in zero-sum Ramsey numbers | 2026 | 2608.01206 | |
| arxiv:2608.10119 | Machine Shape and Hierarchical Blocking: A Mathematics of Arrays Formalization, with an Open Problem in Hierarchical Shape Occupancy | 2026 | 2608.10119 | |
| arxiv:2608.26628 | Open Problems in Mathematical Logic | 2026 | 2608.26628 | |
| doi:10.1002/aps.70060 | On Technology and the Ecology of Thinking: Thinking and Aliveness in the Brave New World | 2026 | W7165450586 | |
| doi:10.1002/chem.202503630 | Pondering the Future of Chemical Research Amid the Wider Adoption of Artificial Intelligence Technologies | 2026 | W7130428711 | |
| doi:10.1002/mgea.70089 | MatInform: A Two‐Stage Multi‐Agent Framework for Consistent and Interpretable Extraction of Biomaterial Literatures | 2026 | W7170068741 | |
| doi:10.1007/978-3-032-29794-5_17 | Small Language Models for Education: Opportunities, Challenges, and a Shared Research Agenda | 2026 | W7166098480 | |
| doi:10.1007/978-3-032-30846-7_7 | Beyond the Render: Grounding Generative AI with Real-World Material Data for Informed Design Decisions | 2026 | W7167420744 | |
| doi:10.1007/978-3-032-31048-4_18 | Evaluating Usability and User Trust in Large Vision-Language Models for Robotic Sorting Tasks with Visual Instructions | 2026 | W7167470445 | |
| doi:10.1007/978-3-658-50335-2_12 | Künstliche Superintelligenz und das Ende der Demokratie | 2026 | W7146976549 | |
| doi:10.1007/978-981-92-3417-2_43 | Adaptive Multi-view Routing for Neural Code Search | 2026 | W7169022864 | |
| doi:10.1007/978-981-95-8597-7_3 | LLMs for Evolutionary Optimization | 2026 | W7168096795 | |
| doi:10.1007/s00211-026-01531-9 | Alternative Basis matrix multiplication is fast and stable† | 2026 | W7131665108 | |
| doi:10.1007/s10649-026-10497-2 | Mathematicians’ values and norms related to algorithms, definitions, and proofs: How do they interrelate? | 2026 | W7139990632 | |
| doi:10.1007/s10664-026-10921-4 | Large language models in model-driven engineering: a systematic mapping study | 2026 | W7168583524 | |
| doi:10.1007/s10994-026-07044-8 | LMTree: Leveraging LLMs with Monte Carlo Tree Search for Automated Feature Engineering | 2026 | W7160706898 | |
| doi:10.1007/s11192-026-05695-x | Exploiting large language models in peer review: indirect prompt injection attacks and integrity probes | 2026 | W7168048551 | |
| doi:10.1007/s11390-026-6258-x | Physical AI: Evolution, Progress, Challenges, and Prospects | 2026 | W7147036522 | |
| doi:10.1007/s11831-026-10675-8 | A Holistic Review of Agentic AI Frameworks, Applications, and Research Trajectories | 2026 | W7164841116 | |
| doi:10.1007/s12599-026-01013-0 | Academic Publishing in the Age of Generative AI | 2026 | W7166529178 | |
| doi:10.1007/s13347-026-01079-4 | Are Large Language Models Intentional? The Limits of Referential Grounding | 2026 | W7140189339 | |
| doi:10.1007/s40820-025-01982-z | TENG-Based Self-Powered Silent Speech Recognition Interface: from Assistive Communication to Immersive AR/VR Interaction | 2026 | W7123223599 | |
| doi:10.1007/s44163-026-01438-2 | A diagnostic hierarchy of epistemic betrayal in large language models | 2026 | W7162115645 | |
| doi:10.1007/s44196-026-01262-7 | Rote Memorization or Intelligence: An Assessment of Inferential Reasoning in Large Language Models | 2026 | W7162775107 | |
| doi:10.1007/s44227-026-00105-3 | Cost-Aware Structured Content Generation Using Hybrid Retrieval-Augmented Generation and Adaptive Compute Routing | 2026 | W7163386884 | |
| doi:10.1017/pds.2026.10412 | Comparing human, LLM, and LLM-QFD approaches to technical requirement extraction | 2026 | W7167040899 | |
| doi:10.1017/pds.2026.10576 | Challenges hindering the application of GenAI methods in engineering design and the product development process: a meta-analysis | 2026 | W7167081362 | |
| doi:10.1021/acs.analchem.6c00352 | Artificial Intelligence for Academic Text Generation in Analytical Chemistry: Current Risks, Indicators, and Perspectives toward Greener and More Sustainable Approaches | 2026 | W7129024017 | |
| doi:10.1021/acs.chemrev.5c00583 | General-Purpose Models for the Chemical Sciences: LLMs and Beyond | 2026 | W7128043854 | |
| doi:10.1021/acs.est.5c09526 | Leveraging LLMs for Environmental Complexity: Structured Fine-Tuning Data Sets and Deployment Strategies | 2026 | W7117888748 | |
| doi:10.1021/acs.jctc.6c00591 | Aitomia: An Agentic Framework for AI-Driven Atomistic and Quantum Chemical Simulations | 2026 | W7165561096 | |
| doi:10.1038/s41467-026-69549-z | Synthesis of covalent organic frameworks for photocatalytic hydrogen peroxide production guided by large language models | 2026 | W7130820291 | |
| doi:10.1038/s41467-026-71928-5 | DxDirector: an agentic large language model driving the full-process clinical diagnosis | 2026 | W7155362722 | |
| doi:10.1038/s41540-026-00656-9 | The future of mathematical oncology in the age of AI | 2026 | W7125703619 | |
| doi:10.1038/s41568-025-00900-0 | Artificial intelligence agents in cancer research and oncology | 2026 | W7122487524 | |
| doi:10.1038/s41586-026-10265-5 | Towards end-to-end automation of AI research | 2026 | W7140287209 | |
| doi:10.1038/s41586-026-10652-y | A multi-agent system for automating scientific discovery | 2026 | W7161734976 | |
| doi:10.1038/s41587-026-03035-1 | Agentic AI and the rise of in silico team science in biomedical research | 2026 | W7131288999 | |
| doi:10.1038/s41587-026-03064-w | Generalist biological artificial intelligence in modeling the language of life | 2026 | W7139101859 | |
| doi:10.1038/s41588-026-02670-3 | Toward generalizable and interpretable AI in regulatory genomics | 2026 | W7171362730 | |
| doi:10.1038/s41591-025-04184-7 | Scaling medical AI across clinical contexts | 2026 | W7127437567 | |
| doi:10.1038/s41598-025-32583-w | What are the limits to biomedical research acceleration through general-purpose AI? | 2026 | W7122841500 | |
| doi:10.1038/s42256-026-01188-x | A large-scale randomized study of large language model feedback in peer review | 2026 | W7131125571 | |
| doi:10.1038/s43246-026-01099-9 | Perovskite-R1: a domain-specialized large language model for intelligent discovery of precursor additives and experimental design | 2026 | W4414414676 | |
| doi:10.1039/d5dd00471c | ToPolyAgent: AI agents for coarse-grained bead-spring topological polymer simulations | 2026 | W4415270367 | |
| doi:10.1039/d6dd00001k | From literature to lab protocols with knowledge-graph-guided large language models | 2026 | W4415693904 | |
| doi:10.1080/02602938.2026.2691499 | AI in the gatekeeper’s chair: elite researchers’ perceptions of AI-assisted feedback in journal peer review | 2026 | W7165676348 | |
| doi:10.1080/03081079.2026.2663918 | Eneragentic: multi-agent large language models for assisting scientific research tasks in integrated energy systems | 2026 | W7159926744 | |
| doi:10.1080/20964471.2025.2600178 | An LLM-based multi-agent system for remote sensing analysis | 2026 | W7119479065 | |
| doi:10.1080/21620555.2026.2707167 | Vibe researching: can AI agents with skills replace or augment social scientists? | 2026 | W7171540262 | |
| doi:10.1093/jncics/pkag033 | Computational identification of salient cancer care topics and themes in oncology social work notes | 2026 | W7147347256 | |
| doi:10.1140/epjds/s13688-026-00672-z | Can large language models generate novel scientific ideas? A comprehensive study on data-driven astronomy | 2026 | W7165138641 | |
| doi:10.1145/3770762.3772619 | Improving LLM-Generated Educational Content: A Case Study on Prototyping, Prompt Engineering, and Evaluating a Tool for Generating Programming Problems for Data Science | 2026 | W7128820760 | |
| doi:10.1145/3770855.3817539 | LingxiDiagBench: A Multi-Agent Framework for Benchmarking LLMs in Chinese Psychiatric Consultation and Diagnosis | 2026 | W7197016314 | |
| doi:10.1145/3770855.3817742 | PACE: Unleashing the Power of Code Embeddings to Boost AutoML Agents | 2026 | W7196945845 | |
| doi:10.1145/3770855.3818107 | BiVCoder: A Multi-Agent Framework for Code Generation via Bidirectional Code-Test Diagnosis | 2026 | W7196925665 | |
| doi:10.1145/3770855.3819049 | Rewarding the Scientific Process: Process-Level Reward Modeling for Agentic Data Analysis | 2026 | W7196949335 | |
| doi:10.1145/3772318.3790802 | "I Need to Find That One Chart": How Data Workers Navigate, Summarize and Communicate Analytical Conversations | 2026 | W7154020075 | |
| doi:10.1145/3772363.3798573 | Playground+: an AI-MR System for Adaptable Open-Ended Family Physical Activity Play | 2026 | W7153895797 | |
| doi:10.1145/3786335.3813158 | fastWorkflow: Closing the Performance Gap Between Small and Frontier Language Models for Conversational Agents | 2026 | W7162074529 | |
| doi:10.1145/3786335.3813220 | Wily: High-Performance Complexity Gated-Feedback for AI Coding Agents | 2026 | W7162099154 | |
| doi:10.1145/3787965 | Large Language Model Aided Multi-objective Evolutionary Algorithm: A Low-cost Adaptive Approach | 2026 | W7133501808 | |
| doi:10.1145/3789240.3822571 | Beyond Monoliths: Enabling Flexible and Composable AI Systems via Memory Disaggregation | 2026 | W7202199195 | |
| doi:10.1145/3794763.3794815 | CodeGlance: Understanding Code Reasoning Challenges in LLMs through Multi-Dimensional Feature Analysis | 2026 | W7171638749 | |
| doi:10.1145/3795101.3814735 | Mutation Without Variation: Convergence Dynamics in LLM-Driven Program Evolution | 2026 | W7163679667 | |
| doi:10.1145/3797120 | CertiCoder: Towards MISRA-Compliant C Code Generation with LLMs | 2026 | W7166698220 | |
| doi:10.1145/3797145 | Small Is Beautiful: A Practical and Efficient Log Parsing Framework | 2026 | W7166727601 | |
| doi:10.1145/3798238 | InspectCoder: Dynamic Analysis-Driven Self Repair through Interactive LLM-Debugger Collaboration | 2026 | W7153127543 | |
| doi:10.1145/3800645.3812956 | Compass vs Railway Tracks: Unpacking User Mental Models for Communicating Long-Horizon Work to Humans vs. AI | 2026 | W7164507293 | |
| doi:10.1145/3801961 | Large Language Models for Combinatorial Optimization: A Systematic Review | 2026 | W4415344803 | |
| doi:10.1145/3805689.3806444 | Helpful, Harmless, Honest? RLHF as Survey Design and Content Moderation | 2026 | W7166535162 | |
| doi:10.1145/3805689.3812402 | Human oversight of agentic systems in practice: Examining the oversight work, challenges, and heuristics of developers using software agents | 2026 | W7166552472 | |
| doi:10.1145/3805760.3814911 | Wink: Recovering from Misbehaviors in Coding Agents | 2026 | W7167425954 | |
| doi:10.1145/3805760.3814925 | ClassEval-Pro: A Cross-Domain Benchmark for Class-Level Code Generation | 2026 | W7167416774 | |
| doi:10.1145/3808097 | PlayCoder: Making LLM-Generated GUI Code Playable | 2026 | W7166666112 | |
| doi:10.1145/3829372 | Judgment, Delegation and Trust in AI-Mediated Scholarly Evaluation | 2026 | W7167633935 | |
| doi:10.1161/hypertensionaha.126.27004 | Empowering Patients and Clinicians: LLMs in Hypertension Care, A Scoping Review | 2026 | W7155401880 | |
| doi:10.1162/opmi.a.365 | Do Language Models Know Who Did What to Whom? | 2026 | W4415067366 | |
| doi:10.14778/3797919.3797942 | TACO: A Benchmark for Open-Domain Text-to-SQL with Ambiguous and Cross-Database Queries | 2026 | W7160661995 | |
| doi:10.21105/joss.09678 | CatLLM: A Python package for Generating, Assigning, and Scoring Open-Ended Survey Data and Images | 2026 | W7161540902 | |
| doi:10.21468/scipostphys.20.2.040 | $\mathcal{CP}$-analyses with symbolic regression | 2026 | W7128593784 | |
| doi:10.21468/scipostphys.20.3.091 | Agents of discovery | 2026 | W7140324928 | |
| doi:10.2196/86365 | Context-Aware Sentence Classification of Radiology Reports Using Synthetic Data: Development and Validation Study | 2026 | W7132846923 | |
| doi:10.2196/preprints.109705 | When Artificial Intelligence Solves Long-Standing Mathematical Problems: Semiosis as a Common Framework for Mathematical Research, Education, and Health AI (Preprint) | 2026 | W7203820194 | |
| doi:10.31127/tuje.1838765 | Generative AI in Academic Writing: A Comparison of DeepSeek, Qwen, ChatGPT, Gemini, Llama, Mistral, and Gemma | 2026 | W4409480044 | |
| doi:10.3389/fcimb.2026.1876326 | Artificial intelligence can match domain experts in evidence extraction and critical appraisal of microbial oncogenesis research publications | 2026 | W7196972652 | |
| doi:10.3389/fonc.2026.1808714 | Knowledge localization is associated with higher performance of domestic large language models in a Chinese radiation oncology examination | 2026 | W7165031300 | |
| doi:10.3389/fpsyg.2026.1786724 | Granularity paradox: how emotion taxonomies shape GPT-5’s affective cognition and human-AI alignment | 2026 | W7135241025 | |
| doi:10.3389/frai.2026.1820375 | Building MCP-native hierarchical AI scientist ecosystems: a perspective on scaling multi-agent scientific discovery | 2026 | W7160988562 | |
| doi:10.3389/fsci.2026.1721295 | Enhancing soil science research with multi-agent artificial intelligence systems | 2026 | W7161986360 | |
| doi:10.48130/gcomm-0026-0005 | From foundation models to autonomous agents in biology | 2026 | W7141642849 | |
| doi:10.5281/zenodo.18973271 | Oversight-Centered Metrology and Control for Agentic Systems: Costly Interrupt Channels, Claim Margins, and Deployment-Relevant Evaluation | 2026 | W7135029326 | |
| doi:10.5281/zenodo.18973272 | Oversight-Centered Metrology and Control for Agentic Systems: Costly Interrupt Channels, Claim Margins, and Deployment-Relevant Evaluation | 2026 | W7135034058 | |
| doi:10.5281/zenodo.19044633 | Recursive Self-Improvement Stability under Endogenous Yardstick Drift | 2026 | W3124659334 | |
| doi:10.5281/zenodo.19447442 | Standing-Layer Honest Public Standing Dynamics for Research Claims under Observable-Only, No-Meta Governance | 2026 | W7151510008 | |
| doi:10.5281/zenodo.19447443 | Standing-Layer Honest Public Standing Dynamics for Research Claims under Observable-Only, No-Meta Governance | 2026 | W7151543449 | |
| doi:10.60097/acig/215416 | Artificial Intelligence Propaganda Factories with Language Models | 2026 | W7131798674 | |
| doi:10.64628/aai.6g5jsmq3s | How AI English and human English differ – and how to decide when to use artificial language | 2026 | W7138883926 | |
| doi:10.64628/aai.7r9t95dsn | The greatest risk of AI in higher education isn’t cheating – it’s the erosion of learning itself | 2026 | W7130503522 | |
| doi:10.64898/2026.01.05.697809 | Can AI Conduct Autonomous Scientific Research? Case Studies on Two Real-World Tasks | 2026 | W7118690722 | |
| doi:10.64898/2026.01.15.26344200 | Automated Task-Specific vs General-Purpose Artificial Intelligence for Detecting Subtle Intraoperative Warning Signs During Cataract Surgery: A Multicenter Diagnostic Study | 2026 | W7124584342 | |
| doi:10.64898/2026.02.05.703998 | Using a GPT-5-driven autonomous lab to optimize the cost and titer of cell-free protein synthesis | 2026 | W7128028999 | |
| doi:10.64898/2026.04.22.720079 | Decoding the phenomenology of spontaneous thought using large language-model ratings on verbal retrospective free reports | 2026 | W7155708236 | |
| doi:10.64898/2026.06.10.731360 | GALILEO: Embodied AI scientist for autonomous therapeutic discovery in dynamic membrane systems | 2026 | W7164550912 | |
| doi:10.64898/2026.06.11.731775 | OmicOS: A Comprehensive Omics Ecosystem Infrastructure and Agent System for the AI Era | 2026 | W7164888123 | |
| doi:10.64898/2026.06.23.734132 | Practical Use of Advanced AI Frameworks on Real-Life Scientific Problems: Three Case Studies | 2026 | W7166566643 | |
| doi:10.64898/2026.08.11.26360118 | REFINE: Closing the Loop Between Large Language Models and Symbolic Rules in Clinical NLP | 2026 | W7203624744 | |
| doi:10.7717/peerj-cs.3761 | A review of the evolution and challenges of few-shot medical image semantic segmentation | 2026 | W7155534923 | |
| doi:10.7717/peerj-cs.4000 | Generative small language models in clinical NLP: applications, adaptation, and evaluation | 2026 | W7169569484 | |
| doi:10.7717/peerj-cs.4063 | CAD2TechSpec: a framework for automating design processes within computer-aided design systems | 2026 | W7202164808 | |
| arxiv:2302.04810 | Machine learning systems: A survey from a data-oriented perspective | 2025 | 2302.04810 | W4320342986 |
| arxiv:2410.02958 | Automl-agent: A multi-agent llm framework for full-pipeline automl | 2025 | 2410.02958 | W4403885480 |
| arxiv:2410.07095 | Mle-bench: Evaluating machine learning agents on machine learning engineering | 2025 | 2410.07095 | W4403345800 |
| arxiv:2411.01679 | Autoformulation of mathematical optimization models using llms | 2025 | 2411.01679 | W4404352823 |
| arxiv:2411.14499 | Understanding world or predicting future? a comprehensive survey of world models | 2025 | 2411.14499 | W4404985365 |
| arxiv:2412.04604 | ARC Prize 2024: Technical Report | 2025 | 2412.04604 | W4405173200 |
| arxiv:2501.03916 | Dolphin: Moving towards closed-loop auto-research through thinking, practice, and feedback | 2025 | 2501.03916 | W4406192744 |
| arxiv:2501.04227 | Agent laboratory: Using llm agents as research assistants | 2025 | 2501.04227 | W4406231153 |
| arxiv:2502.07316 | Codei/o: Condensing reasoning patterns via code input-output prediction | 2025 | 2502.07316 | W4407424342 |
| arxiv:2502.12466 | Equibench: Benchmarking large language models’ reasoning about program semantics via equivalence checking | 2025 | 2502.12466 | W4407759429 |
| arxiv:2502.12468 | MCTS-Judge: Test-Time Scaling in LLM-as-a-Judge for Code Correctness Evaluation | 2025 | 2502.12468 | W4407759425 |
| arxiv:2502.13138 | Aide: Ai-driven exploration in the space of code | 2025 | 2502.13138 | W4407760093 |
| arxiv:2502.14352 | Sr-llm: Rethinking the structured representation in large language model | 2025 | 2502.14352 | W4407806675 |
| arxiv:2502.14499 | Mlgym: A new framework and benchmark for advancing ai research agents | 2025 | 2502.14499 | W4407806895 |
| arxiv:2502.18864 | Towards an ai co-scientist | 2025 | 2502.18864 | |
| arxiv:2504.08066 | The AI Scientist-v2: Workshop-Level Automated Scientific Discovery via Agentic Tree Search | 2025 | 2504.08066 | W4414827381 |
| arxiv:2504.09737 | Can LLM feedback enhance review quality? A randomized study of 20K reviews at ICLR 2025 | 2025 | 2504.09737 | W4415157997 |
| arxiv:2504.11453 | A clean slate for offline reinforcement learning | 2025 | 2504.11453 | |
| arxiv:2505.04588 | Zerosearch: Incentivize the search capability of llms without searching | 2025 | 2505.04588 | W4417092508 |
| arxiv:2505.07782 | Mle-dojo: Interactive environments for empowering llm agents in machine learning engineering | 2025 | 2505.07782 | |
| arxiv:2505.13941 | Mlzero: A multi-agent system for end-to-end machine learning automation | 2025 | 2505.13941 | |
| arxiv:2505.14738 | R&d-agent: An llm-agent framework towards autonomous data science | 2025 | 2505.14738 | W4414801145 |
| arxiv:2505.16938 | Internagent: When agent becomes the scientist – building closed-loop system from hypothesis to verification | 2025 | 2505.16938 | W4417439318 |
| arxiv:2505.23723 | Ml-agent: Reinforcing llm agents for autonomous machine learning engineering | 2025 | 2505.23723 | W4416613142 |
| arxiv:2506.01372 | Ai scientists fail without strong implementation capability | 2025 | 2506.01372 | W4417114405 |
| arxiv:2506.02098 | LibriBrain: over 50 hours of within-subject meg to improve speech decoding methods at scale | 2025 | 2506.02098 | |
| arxiv:2506.02153 | Small Language Models are the Future of Agentic AI | 2025 | 2506.02153 | W4415130727 |
| arxiv:2506.05213 | LLM-First Search: Self-Guided Exploration of the Solution Space | 2025 | 2506.05213 | W4416138629 |
| arxiv:2506.10165 | The 2025 pnpl competition: speech detection and phoneme classification in the libribrain dataset | 2025 | 2506.10165 | W4417348337 |
| arxiv:2506.10974 | Automind: Adaptive knowledgeable agent for automated data science | 2025 | 2506.10974 | W4417357139 |
| arxiv:2506.12618 | OpenUnlearning: accelerating LLM unlearning via unified benchmarking of methods and metrics | 2025 | 2506.12618 | |
| arxiv:2506.13131 | Alphaevolve: A coding agent for scientific and algorithmic discovery | 2025 | 2506.13131 | W4415108068 |
| arxiv:2506.15692 | Mle-star: Machine learning engineering agent via search and targeted refinement | 2025 | 2506.15692 | |
| arxiv:2506.16499 | Ml-master: Towards ai-for-ai via integration of exploration and reasoning | 2025 | 2506.16499 | W4417538505 |
| arxiv:2506.18096 | Deep research agents: A systematic examination and roadmap | 2025 | 2506.18096 | |
| arxiv:2507.01903 | Ai4research: A survey of artificial intelligence for scientific research | 2025 | 2507.01903 | W4417183323 |
| arxiv:2507.02554 | Ai research agents for machine learning: Search, exploration, and generalization in mle-bench | 2025 | 2507.02554 | |
| arxiv:2507.05241 | Scimaster: Towards general-purpose scientific ai agents, part i. x-master as foundation: Can we lead on humanity’s last exam? | 2025 | 2507.05241 | W4416059741 |
| arxiv:2507.18074 | Alphago moment for model architecture discovery | 2025 | 2507.18074 | W4415232784 |
| arxiv:2508.10177 | Kompeteai: Accelerated autonomous multi-agent system for end-to-end pipeline generation for machine learning problems | 2025 | 2508.10177 | |
| arxiv:2508.10925 | Gpt-oss-120b & gpt-oss-20b Model Card | 2025 | 2508.10925 | |
| arxiv:2508.12752 | Deep research: A survey of autonomous research agents | 2025 | 2508.12752 | W4414489845 |
| arxiv:2509.19349 | Shinkaevolve: Towards open-ended and sample-efficient program evolution | 2025 | 2509.19349 | |
| arxiv:2509.24372 | Evolution Strategies at Scale: LLM Fine-Tuning Beyond Reinforcement Learning | 2025 | 2509.24372 | W4415336592 |
| arxiv:2509.25084 | Scaling generalist data-analytic agents | 2025 | 2509.25084 | W4415337623 |
| arxiv:2509.26476 | Regression language models for code | 2025 | 2509.26476 | W4415338554 |
| arxiv:2510.02387 | Cwm: An open-weights llm for research on code generation with world models | 2025 | 2510.02387 | W4417107321 |
| arxiv:2510.08009 | Language models do not embed numbers continuously | 2025 | 2510.08009 | W4416400894 |
| arxiv:2510.08511 | Automlgen: Navigating fine-grained optimization for coding agents | 2025 | 2510.08511 | W4416385763 |
| arxiv:2510.16872 | Deepanalyze: Agentic large language models for autonomous data science | 2025 | 2510.16872 | W4415960243 |
| arxiv:2510.17795 | Executable knowledge graphs for replicating ai research | 2025 | 2510.17795 | |
| arxiv:2511.03773 | Scaling agent learning via experience synthesis | 2025 | 2511.03773 | W4416021968 |
| arxiv:2511.08522 | Alpharesearch: Accelerating new algorithm discovery with language models | 2025 | 2511.08522 | W4416191637 |
| arxiv:2511.16652 | Evolution Strategies at the Hyperscale | 2025 | 2511.16652 | W4416550811 |
| arxiv:2512.01822 | Innogym: Benchmarking the innovation potential of ai agents | 2025 | 2512.01822 | W4416967341 |
| arxiv:2512.02556 | DeepSeek-V3.2: Pushing the Frontier of Open Large Language Models | 2025 | 2512.02556 | W4417006854 |
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| doi:10.1038/s41562-024-01991-9 | Building machines that learn and think with people | 2024 | W4403637376 | |
| doi:10.1038/s41583-024-00802-4 | The language network as a natural kind within the broader landscape of the human brain | 2024 | W4394752750 | |
| doi:10.1038/s41586-024-07441-w | A whole-slide foundation model for digital pathology from real-world data | 2024 | W4398201291 | |
| doi:10.1038/s41586-024-08025-4 | Scalable watermarking for identifying large language model outputs | 2024 | W4403680773 | |
| doi:10.1038/s41591-024-02857-3 | Towards a general-purpose foundation model for computational pathology | 2024 | W4392947521 | |
| doi:10.1038/s41591-024-03097-1 | Evaluation and mitigation of the limitations of large language models in clinical decision-making | 2024 | W4400324908 | |
| doi:10.1038/s41592-024-02201-0 | scGPT: toward building a foundation model for single-cell multi-omics using generative AI | 2024 | W4392168151 | |
| doi:10.1038/s41598-024-55903-y | An evolutionary model of personality traits related to cooperative behavior using a large language model | 2024 | W4392956085 | |
| doi:10.1038/s41598-024-60709-z | Novel applications of Convolutional Neural Networks in the age of Transformers | 2024 | W4396561785 | |
| doi:10.1038/s41598-024-64827-6 | OpenMedLM: prompt engineering can out-perform fine-tuning in medical question-answering with open-source large language models | 2024 | W4399807068 | |
| doi:10.1038/s41746-024-01010-1 | Diagnostic reasoning prompts reveal the potential for large language model interpretability in medicine | 2024 | W4391170193 | |
| doi:10.1038/s41746-024-01029-4 | Prompt engineering in consistency and reliability with the evidence-based guideline for LLMs | 2024 | W4391971084 | |
| doi:10.1038/s41746-024-01196-4 | The METRIC-framework for assessing data quality for trustworthy AI in medicine: a systematic review | 2024 | W4401283978 | |
| doi:10.1038/s41746-024-01239-w | Closing the gap between open source and commercial large language models for medical evidence summarization | 2024 | W4402348202 | |
| doi:10.1038/s41746-024-01251-0 | Results and implications for generative AI in a large introductory biomedical and health informatics course | 2024 | W4402505619 | |
| doi:10.1038/s42256-024-00832-8 | Augmenting large language models with chemistry tools | 2024 | W4396723768 | |
| doi:10.1038/s43018-024-00861-7 | How AI agents will change cancer research and oncology | 2024 | W4405459204 | |
| doi:10.1038/s44184-024-00056-z | Large language models could change the future of behavioral healthcare: a proposal for responsible development and evaluation | 2024 | W4393397034 | |
| doi:10.1039/d3sc05281h | Materials discovery with extreme properties via reinforcement learning-guided combinatorial chemistry | 2024 | W4395094243 | |
| doi:10.1039/d4cs00913d | From text to insight: large language models for chemical data extraction | 2024 | W4405616956 | |
| doi:10.1039/d4dd00074a | Materials science in the era of large language models: a perspective | 2024 | W4399377978 | |
| doi:10.1039/d4dd00178h | Towards a science exocortex | 2024 | W4401702120 | |
| doi:10.1039/d4dd00231h | Exploring inhomogeneous surfaces: Ti-rich SrTiO 3 (110) reconstructions via active learning | 2024 | W4402817436 | |
| doi:10.1039/d4fd00153b | Spiers Memorial Lecture: How to do impactful research in artificial intelligence for chemistry and materials science | 2024 | W4402507667 | |
| doi:10.1039/d4sc03921a | A review of large language models and autonomous agents in chemistry | 2024 | W4405185373 | |
| doi:10.1073/pnas.2318124121 | Evaluating language models for mathematics through interactions | 2024 | W4399281666 | |
| doi:10.1080/12265934.2024.2382706 | Replicate and generalize to make urban research coherent | 2024 | W4401395356 | |
| doi:10.1080/17404622.2024.2397558 | AI translated task setup for non-native English speaking students | 2024 | W4402519213 | |
| doi:10.1080/20964471.2024.2396159 | PreparedLLM: effective pre -pretraining framework for domain-specific large language models | 2024 | W4402379815 | |
| doi:10.1080/23311975.2024.2396526 | Does the digital economy enhance tourism employment? An empirical study of tourism industry in China | 2024 | W4402372759 | |
| doi:10.1093/bib/bbae354 | Harnessing large language models’ zero-shot and few-shot learning capabilities for regulatory research | 2024 | W4401798548 | |
| doi:10.1093/nsr/nwae403 | A survey on multimodal large language models | 2024 | W4404356490 | |
| doi:10.1093/qje/qjae044 | Generative AI at Work | 2024 | W4407142724 | |
| doi:10.1098/rspb.2024.0423 | The changing landscape of text mining: a review of approaches for ecology and evolution | 2024 | W4401184890 | |
| doi:10.1098/rsta.2024.0100 | Large language models (LLMs) as agents for augmented democracy | 2024 | W4404336302 | |
| doi:10.1101/2024.04.25.591003 | CRISPR-GPT for Agentic Automation of Gene Editing Experiments | 2024 | W4395703652 | |
| doi:10.1101/2024.05.30.24308179 | Large language models identify causal genes in complex trait GWAS | 2024 | W4399269289 | |
| doi:10.1101/2024.06.17.599260 | Balancing complexity, performance and plausibility to meta learn plasticity rules in recurrent spiking networks | 2024 | W4399790383 | |
| doi:10.1101/2024.07.24.24310930 | The TRIPOD-LLM Statement: A Targeted Guideline For Reporting Large Language Models Use | 2024 | W4400974494 | |
| doi:10.1101/2024.10.15.618501 | Multimodal learning of transcriptomes and text enables interactive single-cell RNA-seq data exploration with natural-language chats | 2024 | W4403548015 | |
| doi:10.1101/2024.11.11.623004 | The Virtual Lab: AI Agents Design New SARS-CoV-2 Nanobodies with Experimental Validation | 2024 | W4404283941 | |
| doi:10.1101/2024.11.14.623630 | InterPLM: Discovering Interpretable Features in Protein Language Models via Sparse Autoencoders | 2024 | W4404420622 | |
| doi:10.1109/acait63902.2024.11022234 | EECSA: Enhancing Textual Sentiment Analysis through Emotion-Enriched Contextual Integration and Self-Adaptive Prompting Optimization | 2024 | W4411172594 | |
| doi:10.1109/access.2024.3365349 | A Machine Learning-Oriented Survey on Tiny Machine Learning | 2024 | W4391759599 | |
| doi:10.1109/access.2024.3365742 | A Review on Large Language Models: Architectures, Applications, Taxonomies, Open Issues and Challenges | 2024 | W4391855109 | |
| doi:10.1109/access.2024.3368871 | A Novel Scheme for Generating Context-Aware Images Using Generative Artificial Intelligence | 2024 | W4392078326 | |
| doi:10.1109/access.2024.3376441 | A Comprehensive Survey of Convolutions in Deep Learning: Applications, Challenges, and Future Trends | 2024 | W4392902287 | |
| doi:10.1109/access.2024.3381967 | A Survey on Goal-Oriented Semantic Communication: Techniques, Challenges, and Future Directions | 2024 | W4393185338 | |
| doi:10.1109/access.2024.3387941 | ChatGPT for Robotics: Design Principles and Model Abilities | 2024 | W4394828156 | |
| doi:10.1109/access.2024.3389497 | GPT (Generative Pre-Trained Transformer)— A Comprehensive Review on Enabling Technologies, Potential Applications, Emerging Challenges, and Future Directions | 2024 | W4394828356 | |
| doi:10.1109/access.2024.3397775 | Advancements in Generative AI: A Comprehensive Review of GANs, GPT, Autoencoders, Diffusion Model, and Transformers | 2024 | W4396685186 | |
| doi:10.1109/access.2024.3427369 | LLM for SoC Security: A Paradigm Shift | 2024 | W4400578969 | |
| doi:10.1109/access.2024.3478805 | Sharing to Learn and Learning to Share; Fitting Together Meta, Multi-Task, and Transfer Learning: A Meta Review | 2024 | W4403331381 | |
| doi:10.1109/bigdata62323.2024.10825307 | Assessing Empathy in Large Language Models with Real-World Physician-Patient Interactions | 2024 | W4406458340 | |
| doi:10.1109/bigdata62323.2024.10825618 | Embracing Foundation Models for Advancing Scientific Discovery | 2024 | W4406458040 | |
| doi:10.1109/bigdata62323.2024.10825658 | Opportunities and Challenges of Generative-AI in Finance | 2024 | W4406460142 | |
| doi:10.1109/cog60054.2024.10645565 | Online Adaptation for Enhancing Imitation Learning Policies | 2024 | W4401943597 | |
| doi:10.1109/cog60054.2024.10645619 | ChatPCG: Large Language Model-Driven Reward Design for Procedural Content Generation | 2024 | W4401943811 | |
| doi:10.1109/cvpr52733.2024.00463 | Point Transformer V3: Simpler, Faster, Stronger | 2024 | W4402667891 | |
| doi:10.1109/cvpr52733.2024.00786 | Diffusion Model Alignment Using Direct Preference Optimization | 2024 | W4402753790 | |
| doi:10.1109/cvpr52733.2024.00987 | Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data | 2024 | W4402727359 | |
| doi:10.1109/cvpr52733.2024.01295 | MM-Narrator: Narrating Long-form Videos with Multimodal In-Context Learning | 2024 | W4402703105 | |
| doi:10.1109/cvpr52733.2024.01370 | SpatialVLM: Endowing Vision-Language Models with Spatial Reasoning Capabilities | 2024 | W4402716288 | |
| doi:10.1109/cvpr52733.2024.01421 | Feedback-Guided Autonomous Driving | 2024 | W4402726877 | |
| doi:10.1109/cvpr52733.2024.01426 | Weak-to-Strong 3D Object Detection with X-Ray Distillation | 2024 | W4402727683 | |
| doi:10.1109/cvpr52733.2024.01453 | Diffusion-ES: Gradient-Free Planning with Diffusion for Autonomous and Instruction-Guided Driving | 2024 | W4402753718 | |
| doi:10.1109/cvpr52733.2024.01470 | DriveWorld: 4D Pre-Trained Scene Understanding via World Models for Autonomous Driving | 2024 | W4402716059 | |
| doi:10.1109/cvpr52733.2024.01520 | Jointly Training and Pruning CNNs via Learnable Agent Guidance and Alignment | 2024 | W4402753996 | |
| doi:10.1109/cvpr52733.2024.01543 | MP5: A Multi-modal Open-ended Embodied System in Minecraft via Active Perception | 2024 | W4402753835 | |
| doi:10.1109/cvpr52733.2024.01554 | Auto MC-Reward: Automated Dense Reward Design with Large Language Models for Minecraft | 2024 | W4402716424 | |
| doi:10.1109/cvpr52733.2024.02283 | Intern VL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks | 2024 | W4402713111 | |
| doi:10.1109/cvpr52733.2024.02482 | Embodied Multi-Modal Agent trained by an LLM from a Parallel TextWorld | 2024 | W4402726973 | |
| doi:10.1109/dsn-s60304.2024.00032 | Bridging the Gap: A Study of AI-based Vulnerability Management between Industry and Academia | 2024 | W4401990463 | |
| doi:10.1109/ichms59971.2024.10555871 | Strengthening LLM Trust Boundaries: A Survey of Prompt Injection Attacks Surender Suresh Kumar Dr. M.L. Cummings Dr. Alexander Stimpson | 2024 | W4399801327 | |
| doi:10.1109/icmla61862.2024.00201 | NSP: A Neuro-Symbolic Natural Language Navigational Planner | 2024 | W4408146577 | |
| doi:10.1109/icra57147.2024.10610391 | Barrier Functions Inspired Reward Shaping for Reinforcement Learning | 2024 | W4401413949 | |
| doi:10.1109/icra57147.2024.10610421 | Robot Fine-Tuning Made Easy: Pre-Training Rewards and Policies for Autonomous Real-World Reinforcement Learning | 2024 | W4401415522 | |
| doi:10.1109/icra57147.2024.10610455 | Distilling and Retrieving Generalizable Knowledge for Robot Manipulation via Language Corrections | 2024 | W4401417251 | |
| doi:10.1109/icra57147.2024.10610566 | Gen2Sim: Scaling up Robot Learning in Simulation with Generative Models | 2024 | W4401413701 | |
| doi:10.1109/icra57147.2024.10610634 | Statler: State-Maintaining Language Models for Embodied Reasoning | 2024 | W4401414337 | |
| doi:10.1109/icra57147.2024.10610676 | Scalable Multi-Robot Collaboration with Large Language Models: Centralized or Decentralized Systems? | 2024 | W4401415431 | |
| doi:10.1109/icra57147.2024.10610744 | Kinematic-aware Prompting for Generalizable Articulated Object Manipulation with LLMs | 2024 | W4401416612 | |
| doi:10.1109/icra57147.2024.10610784 | How to Prompt Your Robot: A PromptBook for Manipulation Skills with Code as Policies | 2024 | W4401415119 | |
| doi:10.1109/icra57147.2024.10610855 | RoCo: Dialectic Multi-Robot Collaboration with Large Language Models | 2024 | W4401416363 | |
| doi:10.1109/icra57147.2024.10610981 | Interactive Planning Using Large Language Models for Partially Observable Robotic Tasks | 2024 | W4401414856 | |
| doi:10.1109/icra57147.2024.10611038 | Model-Based Runtime Monitoring with Interactive Imitation Learning | 2024 | W4401416269 | |
| doi:10.1109/icra57147.2024.10611220 | Dream2Real: Zero-Shot 3D Object Rearrangement with Vision-Language Models | 2024 | W4401415110 | |
| doi:10.1109/icra57147.2024.10611442 | Learning Agile Bipedal Motions on a Quadrupedal Robot | 2024 | W4401416158 | |
| doi:10.1109/isit57864.2024.10619136 | Predicting Uncertainty of Generative LLMs with MARS: Meaning-Aware Response Scoring | 2024 | W4401693274 | |
| doi:10.1109/iv55156.2024.10588403 | A Superalignment Framework in Autonomous Driving with Large Language Models | 2024 | W4400645974 | |
| doi:10.1109/mipro60963.2024.10569439 | Implementing Literature-based Discovery (LBD) with ChatGPT | 2024 | W4400113876 | |
| doi:10.1109/mits.2024.3381793 | Receive, Reason, and React: Drive as You Say, With Large Language Models in Autonomous Vehicles | 2024 | W4394595621 | |
| doi:10.1109/mnet.2024.3420120 | Intent-Based Management of Next-Generation Networks: an LLM-Centric Approach | 2024 | W4400072049 | |
| doi:10.1109/ojvt.2024.3447449 | IDAS: Intelligent Driving Assistance System Using RAG | 2024 | W4401725315 | |
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| doi:10.1109/sc41406.2024.00089 | Fire-Flyer AI-HPC: A Cost-Effective Software-Hardware Co-Design for Deep Learning | 2024 | W4405756264 | |
| doi:10.1109/sp54263.2024.00210 | LLMs Cannot Reliably Identify and Reason About Security Vulnerabilities (Yet?): A Comprehensive Evaluation, Framework, and Benchmarks | 2024 | W4402264467 | |
| doi:10.1109/tc.2024.3449084 | Joint Pruning and Channel-Wise Mixed-Precision Quantization for Efficient Deep Neural Networks | 2024 | W4401808781 | |
| doi:10.1109/tcad.2024.3383347 | ChatEDA: A Large Language Model Powered Autonomous Agent for EDA | 2024 | W4393305455 | |
| doi:10.1109/tgrs.2024.3356074 | RSPrompter: Learning to Prompt for Remote Sensing Instance Segmentation Based on Visual Foundation Model | 2024 | W4391021462 | |
| doi:10.1109/thms.2024.3467370 | The Augmented Intelligence Perspective on Human-in-the-Loop Reinforcement Learning: Review, Concept Designs, and Future Directions | 2024 | W4403534251 | |
| doi:10.1109/tifs.2024.3414249 | AutoSMC: An Automated Machine Learning Framework for Signal Modulation Classification | 2024 | W4399620332 | |
| doi:10.1109/tii.2024.3395648 | Combining Compressed Sensing and Neural Architecture Search for Sensor-Near Vibration Diagnostics | 2024 | W4396852839 | |
| doi:10.1109/tkde.2024.3352100 | Unifying Large Language Models and Knowledge Graphs: A Roadmap | 2024 | W4390692489 | |
| doi:10.1109/tkde.2024.3392335 | Recommender Systems in the Era of Large Language Models (LLMs) | 2024 | W4394994587 | |
| doi:10.1109/tmm.2024.3377125 | Pseudo Label Fusion With Uncertainty Estimation for Semi-Supervised Cropping Box Regression | 2024 | W4392745503 | |
| doi:10.1109/tnnls.2024.3373749 | Off-Policy Prediction Learning: An Empirical Study of Online Algorithms | 2024 | W4399486984 | |
| doi:10.1109/tnsre.2024.3358491 | Cross-Subject Motor Imagery Decoding by Transfer Learning of Tactile ERD | 2024 | W4391216055 | |
| doi:10.1109/tpami.2024.3362475 | SpectralGPT: Spectral Remote Sensing Foundation Model | 2024 | W4393906060 | |
| doi:10.1109/tpami.2024.3367329 | A Comprehensive Survey of Continual Learning: Theory, Method and Application | 2024 | W4392173735 | |
| doi:10.1109/tpami.2024.3435937 | End-to-End Autonomous Driving: Challenges and Frontiers | 2024 | W4401109681 | |
| doi:10.1109/tpami.2024.3498035 | PATNAS: A Path-Based Training-Free Neural Architecture Search | 2024 | W4404371508 | |
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| doi:10.1109/tse.2024.3408448 | Improving Issue-PR Link Prediction via Knowledge-Aware Heterogeneous Graph Learning | 2024 | W4399310703 | |
| doi:10.1109/tse.2024.3428972 | LLM-Based Test-Driven Interactive Code Generation: User Study and Empirical Evaluation | 2024 | W4400878080 | |
| doi:10.1109/tse.2024.3470333 | Multitask-Based Evaluation of Open-Source LLM on Software Vulnerability | 2024 | W4403182498 | |
| doi:10.1109/ur61395.2024.10597463 | Enhancing Human-Robot Interaction: Integrating ASL Recognition and LLM-Driven Co-Speech Gestures in Pepper Robot with a Compact Neural Network | 2024 | W4401018271 | |
| doi:10.1109/wacv57701.2024.00559 | FuseCap: Leveraging Large Language Models for Enriched Fused Image Captions | 2024 | W4394625850 | |
| doi:10.1109/wacvw60836.2024.00101 | Drive as You Speak: Enabling Human-Like Interaction with Large Language Models in Autonomous Vehicles | 2024 | W4394862768 | |
| doi:10.1109/wacvw60836.2024.00102 | Drive Like a Human: Rethinking Autonomous Driving with Large Language Models | 2024 | W4394862732 | |
| doi:10.1109/wacvw60836.2024.00106 | A Survey on Multimodal Large Language Models for Autonomous Driving | 2024 | W4394862623 | |
| doi:10.1126/sciadv.adi3621 | Open-endedness in synthetic biology: A route to continual innovation for biological design | 2024 | W4391019346 | |
| doi:10.1126/science.adj0998 | GPTs are gpts: labor market impact potential of llms | 2024 | ||
| doi:10.1145/3620666.3651380 | NeuPIMs: NPU-PIM Heterogeneous Acceleration for Batched LLM Inferencing | 2024 | W4392427708 | |
| doi:10.1145/3624724 | Talking about Large Language Models | 2024 | W4391215636 | |
| doi:10.1145/3630106.3658921 | Benchmarking the Fairness of Image Upsampling Methods | 2024 | W4399365242 | |
| doi:10.1145/3638530.3648432 | Using Large Language Models for Evolutionary Search | 2024 | W4401213361 | |
| doi:10.1145/3639372 | Explainability for Large Language Models: A Survey | 2024 | W4390490761 | |
| doi:10.1145/3641289 | A Survey on Evaluation of Large Language Models | 2024 | W4391136507 | |
| doi:10.1145/3643651.3659892 | Evaluating Large Language Models for Real-World Vulnerability Repair in C/C++ Code | 2024 | W4399516134 | |
| doi:10.1145/3645102 | Trustworthy Distributed AI Systems: Robustness, Privacy, and Governance | 2024 | W4391614477 | |
| doi:10.1145/3649468 | Envisioning Information Access Systems: What Makes for Good Tools and a Healthy Web? | 2024 | W4392163191 | |
| doi:10.1145/3651890.3672274 | CacheGen: KV Cache Compression and Streaming for Fast Large Language Model Serving | 2024 | W4401176373 | |
| doi:10.1145/3658644.3670344 | MGTBench: Benchmarking Machine-Generated Text Detection | 2024 | W4405182784 | |
| doi:10.1145/3661167.3661221 | A Performance Study of LLM-Generated Code on Leetcode | 2024 | W4399667811 | |
| doi:10.1145/3663529.3663794 | Predicting test results without execution | 2024 | ||
| doi:10.1145/3689728 | Statically Contextualizing Large Language Models with Typed Holes | 2024 | W4402954209 | |
| doi:10.1145/3689776 | Drowzee: Metamorphic Testing for Fact-Conflicting Hallucination Detection in Large Language Models | 2024 | W4403223051 | |
| doi:10.1145/3691620.3695513 | Towards Understanding the Effectiveness of Large Language Models on Directed Test Input Generation | 2024 | W4403536418 | |
| doi:10.1145/3695988 | Large Language Models for Software Engineering: A Systematic Literature Review | 2024 | W4402665833 | |
| doi:10.1145/3701728 | Efficient Deep Learning Infrastructures for Embedded Computing Systems: A Comprehensive Survey and Future Envision | 2024 | W4403735204 | |
| doi:10.1145/3703155 | A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions | 2024 | W4404534210 | |
| doi:10.1145/3708519 | Automatic Programming: Large Language Models and Beyond | 2024 | W4405396136 | |
| doi:10.1145/3708531 | Large Language Model Supply Chain: A Research Agenda | 2024 | W4405366282 | |
| doi:10.1145/3718491.3718640 | Multi-domain Data Association Analysis: Research on Precise Customer Classification Based on LLM and GMM Models | 2024 | W4409095318 | |
| doi:10.1146/annurev-neuro-120623-101142 | Language in Brains, Minds, and Machines | 2024 | W4395661358 | |
| doi:10.1162/coli_a_00524 | Bias and Fairness in Large Language Models: A Survey | 2024 | W4399528455 | |
| doi:10.1162/neco_a_01642 | An Overview of the Free Energy Principle and Related Research | 2024 | W4392579763 | |
| doi:10.1162/opmi_a_00155 | Group Coordination Catalyzes Individual and Cultural Intelligence | 2024 | W4402037109 | |
| doi:10.1162/tacl_a_00638 | Lost in the Middle: How Language Models Use Long Contexts | 2024 | W4391876619 | |
| doi:10.1177/02783649241281508 | Foundation models in robotics: Applications, challenges, and the future | 2024 | W4402890475 | |
| doi:10.1177/07439156241309874 | Generative AI in Marketing and Principles for Ethical Design and Deployment | 2024 | W4405628342 | |
| doi:10.1177/23780231241259651 | Start Generating: Harnessing Generative Artificial Intelligence for Sociological Research | 2024 | W4400920253 | |
| doi:10.1186/s41239-024-00448-3 | Embracing the future of Artificial Intelligence in the classroom: the relevance of AI literacy, prompt engineering, and critical thinking in modern education | 2024 | W4392773210 | |
| doi:10.1364/jocn.511863 | Model and data-centric machine learning algorithms to address data scarcity for failure identification | 2024 | W4391433192 | |
| doi:10.1371/journal.pdig.0000503 | Addressing 6 challenges in generative AI for digital health: A scoping review | 2024 | W4398245384 | |
| doi:10.14778/3681954.3682003 | The Dawn of Natural Language to SQL: Are We Fully Ready? | 2024 | W4402042542 | |
| doi:10.1515/nanoph-2023-0646 | Language‐controllable programmable metasurface empowered by large language models | 2024 | W4390588287 | |
| doi:10.1609/aaai.v38i11.29154 | PPO-Clip Attains Global Optimality: Towards Deeper Understandings of Clipping | 2024 | W4393159597 | |
| doi:10.1609/aaai.v38i16.29704 | Learn to Follow: Decentralized Lifelong Multi-Agent Pathfinding via Planning and Learning | 2024 | W4393160223 | |
| doi:10.1609/aaai.v38i16.29720 | Graph of Thoughts: Solving Elaborate Problems with Large Language Models | 2024 | W4393160302 | |
| doi:10.1609/aaai.v38i19.30115 | Chasing Fairness in Graphs: A GNN Architecture Perspective | 2024 | W4393146624 | |
| doi:10.1609/aaai.v38i19.30185 | Can LLM Replace Stack Overflow? A Study on Robustness and Reliability of Large Language Model Code Generation | 2024 | W4393152795 | |
| doi:10.1609/aaai.v38i7.28597 | NavGPT: Explicit Reasoning in Vision-and-Language Navigation with Large Language Models | 2024 | W4393154152 | |
| doi:10.1609/aaaiss.v3i1.31254 | Evaluating Large Language Models with RAG Capability: A Perspective from Robot Behavior Planning and Execution | 2024 | W4398160866 | |
| doi:10.1609/icaps.v34i1.31503 | On the Prospects of Incorporating Large Language Models (LLMs) in Automated Planning and Scheduling (APS) | 2024 | W4399177300 | |
| doi:10.1613/jair.1.14747 | Can Fairness be Automated? Guidelines and Opportunities for Fairness-aware AutoML | 2024 | W4391932574 | |
| doi:10.1613/jair.1.15703 | Structure in Deep Reinforcement Learning: A Survey and Open Problems | 2024 | W4395007752 | |
| doi:10.1613/jair.1.15884 | Tackling Cooperative Incompatibility for Zero-Shot Human-AI Coordination | 2024 | W4401007148 | |
| doi:10.21203/rs.3.rs-3883562/v1 | Integrating Deep Learning with Symbolic Reasoning in TinyLlama for Accurate Information Retrieval | 2024 | W4391143839 | |
| doi:10.2139/ssrn.4841493 | FinRobot: An Open-Source AI Agent Platform for Financial Applications using Large Language Models | 2024 | W4399146196 | |
| doi:10.21681/2311-3456-2024-3-68-75 | METHODOLOGY FOR THE DEVELOPMENT OF AUTOMATED SOFTWARE CODE GENERATION TOOLS BY FINE-TUNING LARGE LANGUAGE MODELS | 2024 | W4398788199 | |
| doi:10.2196/59782 | Evaluating Medical Entity Recognition in Health Care: Entity Model Quantitative Study | 2024 | W4402552866 | |
| doi:10.2196/62678 | Advancing AI Data Ethics in Nursing: Future Directions for Nursing Practice, Research, and Education | 2024 | W4402503172 | |
| doi:10.22503/inftars.xxiv.2024.4.5 | AGI-Correlationism and Its Discontents | 2024 | W4410064622 | |
| doi:10.23919/iccas63016.2024.10773080 | Kolmogorov-Arnold Networks for Online Reinforcement Learning | 2024 | W4405180437 | |
| doi:10.26434/chemrxiv-2024-9l6jc | Machine-Learning-Backed Evolutionary Exploration of Ti-rich SrTiO3(110) Surface Reconstructions | 2024 | W4400041655 | |
| doi:10.26599/tst.2024.9010047 | Diffusion Models for Medical Image Computing: A Survey | 2024 | W4402449885 | |
| doi:10.32388/atahd0 | aiXcoder-7B: A Lightweight and Effective Large Language Model for Code Completion | 2024 | W4404900300 | |
| doi:10.32604/cmc.2024.050790 | A Comprehensive Survey of Recent Transformers in Image, Video and Diffusion Models | 2024 | W4400094413 | |
| doi:10.3389/feduc.2024.1418006 | Advanced large language models and visualization tools for data analytics learning | 2024 | W4401434138 | |
| doi:10.3389/fpls.2024.1452551 | Plant disease recognition datasets in the age of deep learning: challenges and opportunities | 2024 | W4402933835 | |
| doi:10.3389/frai.2024.1293084 | Knowledge sharing in manufacturing using LLM-powered tools: user study and model benchmarking | 2024 | W4393231265 | |
| doi:10.3389/frai.2024.1460364 | Large language models for whole-learner support: opportunities and challenges | 2024 | W4403439632 | |
| doi:10.3390/a17120582 | Integrating Large Language Models and Optimization in Semi- Structured Decision Making: Methodology and a Case Study | 2024 | W4405427358 | |
| doi:10.3390/wevj15100438 | The Safety Risks of AI-Driven Solutions in Autonomous Road Vehicles | 2024 | W4402861568 | |
| doi:10.34133/research.0399 | Prospective Role of Foundation Models in Advancing Autonomous Vehicles | 2024 | W4396869735 | |
| doi:10.36227/techrxiv.171742375.53309794/v1 | The Illusion of Boundless AI: Analyzing Limitations and Ethical Concerns | 2024 | W4399288710 | |
| doi:10.3724/2096-7004.di.2024.0001 | Large Knowledge Model: Perspectives and Challenges | 2024 | W4399790320 | |
| doi:10.4230/oasics.dx.2024.27 | On a Method to Measure Supervised Multiclass Model’s Interpretability: Application to Degradation Diagnosis (Short Paper) | 2024 | W2962862931 | |
| doi:10.4324/9781003459026 | Generative AI in Higher Education | 2024 | W4392658848 | |
| doi:10.5121/csit.2024.140703 | In-Context Learning for Scalable and Online Hallucination Detection in RAGS | 2024 | W4395693361 | |
| doi:10.55041/ijsrem39464 | Meta-Learning (Learning to Learn): Investigating How Meta-Learning Algorithms Can Improve Learning Efficiency Across Tasks | 2024 | W4405065335 | |
| doi:10.5539/cis.v18n1p39 | DevSecOps Sentinel: GenAI-Driven Agentic Workflows for Comprehensive Supply Chain Security | 2024 | W4405653054 | |
| doi:10.57702/iuuvgtaz | A simple framework for contrastive learning of visual representations | 2024 | W3034978746 | |
| doi:10.57702/o9raffed | Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift | 2024 | W2949117887 | |
| doi:10.57702/vkcnqiqb | Off-Policy Deep Reinforcement Learning without Exploration | 2024 | W2963704132 | |
| doi:10.57702/zp44cu3g | Learning Multiple Layers of Features from Tiny Images | 2024 | W3118608800 | |
| doi:10.59863/miql7785 | The Rise of Artificial Intelligence in Educational Measurement: Opportunities and Ethical Challenges | 2024 | W4405276448 | |
| arxiv:2201.11903 | Chain-of-thought prompting elicits reasoning in large language models | 2023 | 2201.11903 | W4221143046 |
| arxiv:2205.11916 | Large language models are zero-shot reasoners | 2023 | 2205.11916 | W4281557260 |
| arxiv:2210.03629 | React: Synergizing reasoning and acting in language models | 2023 | 2210.03629 | W4304195432 |
| arxiv:2301.08727 | Neural Architecture Search: Insights from 1000 Papers | 2023 | 2301.08727 | W4317838087 |
| arxiv:2301.12987 | The Optimal Choice of Hypothesis Is the Weakest, Not the Shortest | 2023 | 2301.12987 | W4318719367 |
| arxiv:2302.09051 | Complex QA and language models hybrid architectures, Survey | 2023 | 2302.09051 | W4321393106 |
| arxiv:2302.13971 | LLaMA: open and efficient foundation language models | 2023 | 2302.13971 | W4322718191 |
| arxiv:2303.10158 | Data-centric artificial intelligence: A survey | 2023 | 2303.10158 | W4327993492 |
| arxiv:2303.13375 | Capabilities of GPT-4 on Medical Challenge Problems | 2023 | 2303.13375 | W4360891289 |
| arxiv:2304.07193 | DINOv2: Learning Robust Visual Features without Supervision | 2023 | 2304.07193 | W4366208220 |
| arxiv:2305.14259 | Scimon: Scientific inspiration machines optimized for novelty, 2024b | 2023 | 2305.14259 | W4378509293 |
| arxiv:2305.17144 | Ghost in the Minecraft: Generally Capable Agents for Open-World Environments via Large Language Models with Text-based Knowledge and Memory | 2023 | 2305.17144 | W4378768661 |
| arxiv:2306.08647 | Language to rewards for robotic skill synthesis | 2023 | 2306.08647 | W4380993732 |
| arxiv:2306.12672 | From word models to world models: Translating from natural language to the probabilistic language of thought | 2023 | 2306.12672 | W4381827075 |
| arxiv:2307.15008 | A LLM Assisted Exploitation of AI-Guardian | 2023 | 2307.15008 | W4385373743 |
| arxiv:2310.12931 | Eureka: Human-level reward design via coding large language models | 2023 | 2310.12931 | W4387839203 |
| arxiv:2310.15164 | LINC: A Neurosymbolic Approach for Logical Reasoning by Combining Language Models with First-Order Logic Provers | 2023 | 2310.15164 | W4387929841 |
| arxiv:2311.16079 | MEDITRON-70B: Scaling Medical Pretraining for Large Language Models | 2023 | 2311.16079 | W4389116614 |
| arxiv:2312.09390 | Weak-to-strong generalization: Eliciting strong capabilities with weak supervision, 2023 | 2023 | 2312.09390 | W4389911544 |
| doi:10.1001/jamanetworkopen.2023.43689 | Leveraging Large Language Models for Decision Support in Personalized Oncology | 2023 | W4388759569 | |
| doi:10.1002/mef2.43 | Accelerating the integration of ChatGPT and other large‐scale AI models into biomedical research and healthcare | 2023 | W4377043947 | |
| doi:10.1007/978-3-031-33469-6_5 | The Optimal Choice of Hypothesis Is the Weakest, Not the Shortest | 2023 | W4377724273 | |
| doi:10.1007/s10514-023-10136-2 | Large language models for chemistry robotics | 2023 | W4387937021 | |
| doi:10.1007/s11263-023-01785-y | Neural Architecture Search for Dense Prediction Tasks in Computer Vision | 2023 | W4365814106 | |
| doi:10.1007/s12599-023-00834-7 | Generative AI | 2023 | W4386693657 | |
| doi:10.1016/j.aiopen.2023.08.012 | GPT understands, too | 2023 | W3139080614 | |
| doi:10.1016/j.apsadv.2023.100523 | Scope of machine learning in materials research—A review | 2023 | W4389113368 | |
| doi:10.1016/j.asoc.2023.110757 | Multiobjective evolutionary pruning of Deep Neural Networks with Transfer Learning for improving their performance and robustness | 2023 | W4385830668 | |
| doi:10.1016/j.cogsys.2023.101155 | Inductive reasoning in humans and large language models | 2023 | W4385652328 | |
| doi:10.1016/j.compbiomed.2023.107356 | Artificial intelligence in cancer diagnosis and therapy: Current status and future perspective | 2023 | W4385813064 | |
| doi:10.1016/j.dss.2023.114043 | Utilizing the omnipresent: Incorporating digital documents into predictive process monitoring using deep neural networks | 2023 | W4382797291 | |
| doi:10.1016/j.eswa.2023.122499 | Meta-IRLSOT++: A meta-inverse reinforcement learning method for fast adaptation of trajectory prediction networks | 2023 | W4388562378 | |
| doi:10.1016/j.icte.2023.11.001 | Training-free neural architecture search: A review | 2023 | W4388570717 | |
| doi:10.1016/j.inffus.2023.102135 | General Purpose Artificial Intelligence Systems (GPAIS): Properties, definition, taxonomy, societal implications and responsible governance | 2023 | W4388499755 | |
| doi:10.1016/j.ipm.2023.103454 | Cyberbullying detection for low-resource languages and dialects: Review of the state of the art | 2023 | W4384520880 | |
| doi:10.1016/j.jag.2023.103569 | Ten deep learning techniques to address small data problems with remote sensing | 2023 | W4388792466 | |
| doi:10.1016/j.jbi.2023.104487 | BioREx: Improving biomedical relation extraction by leveraging heterogeneous datasets | 2023 | W4381573137 | |
| doi:10.1016/j.jfop.2023.100005 | Conversational AI Models for ophthalmic diagnosis: Comparison of ChatGPT and the Isabel Pro Differential Diagnosis Generator | 2023 | W4323030608 | |
| doi:10.1016/j.jss.2023.111734 | GitHub Copilot AI pair programmer: Asset or Liability? | 2023 | W4367672983 | |
| doi:10.1016/j.knosys.2023.110335 | Deep reinforcement learning in recommender systems: A survey and new perspectives | 2023 | W4318159260 | |
| doi:10.1016/j.neucom.2023.02.049 | Distributional reinforcement learning with unconstrained monotonic neural networks | 2023 | W3173552545 | |
| doi:10.1016/j.neunet.2023.01.041 | Continual Object Detection: A review of definitions, strategies, and challenges | 2023 | W4319235394 | |
| doi:10.1016/j.nlp.2023.100048 | A survey of GPT-3 family large language models including ChatGPT and GPT-4 | 2023 | W4389977189 | |
| doi:10.1016/j.rser.2023.114248 | Deep reinforcement learning based energy management strategies for electrified vehicles: Recent advances and perspectives | 2023 | W4390122262 | |
| doi:10.1016/j.sysarc.2023.102990 | A survey of techniques for optimizing transformer inference | 2023 | W4386826409 | |
| doi:10.1016/j.tics.2023.08.006 | What are large language models supposed to model? | 2023 | W4386333898 | |
| doi:10.1016/j.tics.2023.10.002 | Generating meaning: active inference and the scope and limits of passive AI | 2023 | W4388696164 | |
| doi:10.1016/s2589-7500(23)00201-7 | Large language models and their impact in ophthalmology | 2023 | W4388922836 | |
| doi:10.1021/acsphotonics.3c00156 | Neural Operator-Based Surrogate Solver for Free-Form Electromagnetic Inverse Design | 2023 | W4361229860 | |
| doi:10.1021/jacs.2c13467 | Generative Models as an Emerging Paradigm in the Chemical Sciences | 2023 | W4365442601 | |
| doi:10.1038/s41551-023-01056-8 | Algorithmic fairness in artificial intelligence for medicine and healthcare | 2023 | W4382394524 | |
| doi:10.1038/s41562-023-01659-w | Emergent analogical reasoning in large language models | 2023 | W4385430086 | |
| doi:10.1038/s41562-023-01742-2 | Machine culture | 2023 | W4388835050 | |
| doi:10.1038/s41586-023-06291-2 | Large language models encode clinical knowledge | 2023 | W4384071683 | |
| doi:10.1038/s41586-023-06647-8 | Role play with large language models | 2023 | W4388488609 | |
| doi:10.1038/s41586-023-06792-0 | Autonomous chemical research with large language models | 2023 | W4389991792 | |
| doi:10.1038/s41591-023-02448-8 | Large language models in medicine | 2023 | W4384561707 | |
| doi:10.1038/s41593-023-01382-9 | Organizing memories for generalization in complementary learning systems | 2023 | W4384922492 | |
| doi:10.1038/s42256-023-00754-x | A social path to human-like artificial intelligence | 2023 | W4388775529 | |
| doi:10.1038/s43856-023-00370-1 | The future landscape of large language models in medicine | 2023 | W4387500346 | |
| doi:10.1038/s44159-023-00241-5 | Using large language models in psychology | 2023 | W4387617694 | |
| doi:10.1039/d3dd00112a | Domain-specific chatbots for science using embeddings | 2023 | W4387507766 | |
| doi:10.1039/d3dd00113j | 14 examples of how LLMs can transform materials science and chemistry: a reflection on a large language model hackathon | 2023 | W4385671288 | |
| doi:10.1063/5.0146905 | Deep ensembles vs committees for uncertainty estimation in neural-network force fields: Comparison and application to active learning | 2023 | W4377221266 | |
| doi:10.1063/5.0175686 | A comparative study on metric based meta learning approaches for few-shot image and text classification | 2023 | W4387587427 | |
| doi:10.1080/08874417.2023.2261010 | The Potential of Generative Artificial Intelligence Across Disciplines: Perspectives and Future Directions | 2023 | W4387379065 | |
| doi:10.1093/bioinformatics/btad310 | AIONER: all-in-one scheme-based biomedical named entity recognition using deep learning | 2023 | W4376274483 | |
| doi:10.1093/bioinformatics/btad599 | GNorm2: an improved gene name recognition and normalization system | 2023 | W4387934104 | |
| doi:10.1093/gji/ggad460 | DAS-N2N: machine learning distributed acoustic sensing (DAS) signal denoising without clean data | 2023 | W4389969201 | |
| doi:10.1093/oso/9780197653302.001.0001 | From Deep Learning to Rational Machines | 2023 | W4389765664 | |
| doi:10.1101/2023.03.02.23286705 | AI chatbots not yet ready for clinical use | 2023 | W4323354733 | |
| doi:10.1109/access.2023.3253818 | Neural Architecture Search Benchmarks: Insights and Survey | 2023 | W4323644307 | |
| doi:10.1109/access.2023.3300381 | From ChatGPT to ThreatGPT: Impact of Generative AI in Cybersecurity and Privacy | 2023 | W4385452929 | |
| doi:10.1109/cog57401.2023.10333174 | Two-Memory Reinforcement Learning | 2023 | W4389302466 | |
| doi:10.1109/cog57401.2023.10333214 | Extend Wave Function Collapse Algorithm to Large-Scale Content Generation | 2023 | W4389315313 | |
| doi:10.1109/comst.2023.3239220 | Understanding O-RAN: Architecture, Interfaces, Algorithms, Security, and Research Challenges | 2023 | W4317796310 | |
| doi:10.1109/cvpr52729.2023.00593 | A Dynamic Multi-Scale Voxel Flow Network for Video Prediction | 2023 | W4386083005 | |
| doi:10.1109/cvpr52729.2023.01320 | Open-World Multi-Task Control Through Goal-Aware Representation Learning and Adaptive Horizon Prediction | 2023 | W4386065365 | |
| doi:10.1109/cvpr52729.2023.01385 | InternImage: Exploring Large-Scale Vision Foundation Models with Deformable Convolutions | 2023 | W4386076222 | |
| doi:10.1109/fdl59689.2023.10272045 | PLiNIO: A User-Friendly Library of Gradient-Based Methods for Complexity-Aware DNN Optimization | 2023 | W4387444863 | |
| doi:10.1109/iccad57390.2023.10323812 | Invited Paper: VerilogEval: Evaluating Large Language Models for Verilog Code Generation | 2023 | W4389166737 | |
| doi:10.1109/iccad57390.2023.10323953 | GPT4AIGChip: Towards Next-Generation AI Accelerator Design Automation via Large Language Models | 2023 | W4389166691 | |
| doi:10.1109/iccv51070.2023.01100 | Sigmoid Loss for Language Image Pre-Training | 2023 | W4390873312 | |
| doi:10.1109/icpads60453.2023.00126 | Distributed Training of Large Language Models | 2023 | W4393186514 | |
| doi:10.1109/icra48891.2023.10160583 | Benchmarking Reinforcement Learning Techniques for Autonomous Navigation | 2023 | W4383108450 | |
| doi:10.1109/icra48891.2023.10160591 | Code as Policies: Language Model Programs for Embodied Control | 2023 | W4383097638 | |
| doi:10.1109/icra48891.2023.10161267 | Efficient Learning of Locomotion Skills through the Discovery of Diverse Environmental Trajectory Generator Priors | 2023 | W4383108188 | |
| doi:10.1109/icra48891.2023.10161317 | ProgPrompt: Generating Situated Robot Task Plans using Large Language Models | 2023 | W4383108457 | |
| doi:10.1109/icse-fose59343.2023.00008 | Large Language Models for Software Engineering: Survey and Open Problems | 2023 | W4392414327 | |
| doi:10.1109/icse48619.2023.00129 | Automated Program Repair in the Era of Large Pre-trained Language Models | 2023 | W4384345708 | |
| doi:10.1109/ictc58733.2023.10392629 | AuPPLE: Augmented Physical Priors through Language Enhancement using Self-Supervised Learning | 2023 | W4391128605 | |
| doi:10.1109/jas.2023.123618 | A Brief Overview of ChatGPT: The History, Status Quo and Potential Future Development | 2023 | W4367595583 | |
| doi:10.1109/jbhi.2023.3316750 | Large AI Models in Health Informatics: Applications, Challenges, and the Future | 2023 | W4386973901 | |
| doi:10.1109/mts.2023.3306532 | Potential Impact of Data-Centric AI on Society | 2023 | W4386952177 | |
| doi:10.1109/satml54575.2023.00039 | Toward Transparent AI: A Survey on Interpreting the Inner Structures of Deep Neural Networks | 2023 | W4378976798 | |
| doi:10.1109/tai.2023.3314581 | An Overview of Swarm Coordinated Control | 2023 | W4386634495 | |
| doi:10.1109/tase.2023.3292388 | Safe Model-Based Reinforcement Learning With an Uncertainty-Aware Reachability Certificate | 2023 | W4389065366 | |
| doi:10.1109/taslp.2023.3288409 | AudioLM: A Language Modeling Approach to Audio Generation | 2023 | W4381786045 | |
| doi:10.1109/taslp.2023.3328283 | End-to-End Speech Recognition: A Survey | 2023 | W4388017359 | |
| doi:10.1109/tetc.2023.3322033 | Enhancing Neural Architecture Search With Multiple Hardware Constraints for Deep Learning Model Deployment on Tiny IoT Devices | 2023 | W4387490516 | |
| doi:10.1109/tevc.2023.3348475 | Toward Evolutionary Multitask Convolutional Neural Architecture Search | 2023 | W4390421890 | |
| doi:10.1109/tits.2023.3259322 | A Survey on Safety-Critical Driving Scenario Generation—A Methodological Perspective | 2023 | W4361861254 | |
| doi:10.1109/tnnls.2023.3250269 | A Survey on Offline Reinforcement Learning: Taxonomy, Review, and Open Problems | 2023 | W4360584316 | |
| doi:10.1109/tpami.2023.3240565 | DeepEIT: Deep Image Prior Enabled Electrical Impedance Tomography | 2023 | W4319986922 | |
| doi:10.1109/tpami.2023.3292075 | Transfer Learning in Deep Reinforcement Learning: A Survey | 2023 | W4383112908 | |
| doi:10.1109/tpami.2023.3294394 | Learning Symbolic Model-Agnostic Loss Functions via Meta-Learning | 2023 | W4383960481 | |
| doi:10.1109/tro.2023.3257541 | Asymmetric Self-Play-Enabled Intelligent Heterogeneous Multirobot Catching System Using Deep Multiagent Reinforcement Learning | 2023 | W4365421101 | |
| doi:10.1109/tro.2023.3308780 | Circular Accessible Depth: A Robust Traversability Representation for UGV Navigation | 2023 | W4386494430 | |
| doi:10.1109/tvcg.2023.3327163 | AttentionViz: A Global View of Transformer Attention | 2023 | W4387966251 | |
| doi:10.1115/1.4063843 | MechGPT, a Language-Based Strategy for Mechanics and Materials Modeling That Connects Knowledge Across Scales, Disciplines, and Modalities | 2023 | W4387773384 | |
| doi:10.1117/12.2675573 | YOLOv8 for defect inspection of hexagonal directed self-assembly patterns: a data-centric approach | 2023 | W4387379612 | |
| doi:10.1145/3576896 | A Computational Inflection for Scientific Discovery | 2023 | W4385259231 | |
| doi:10.1145/3578938 | Efficient Deep Learning: A Survey on Making Deep Learning Models Smaller, Faster, and Better | 2023 | W3170647102 | |
| doi:10.1145/3593013.3594033 | Harms from Increasingly Agentic Algorithmic Systems | 2023 | W4376632242 | |
| doi:10.1145/3605943 | Recent Advances in Natural Language Processing via Large Pre-trained Language Models: A Survey | 2023 | W4382246105 | |
| doi:10.1155/2023/1923981 | Testing the Ability of Teachers and Students to Differentiate between Essays Generated by ChatGPT and High School Students | 2023 | W4382140847 | |
| doi:10.1162/coli_a_00492 | Language Model Behavior: A Comprehensive Survey | 2023 | W4388691863 | |
| doi:10.1177/26339137231162025 | A learning agent that acquires social norms from public sanctions in decentralized multi-agent settings | 2023 | W3170791277 | |
| doi:10.1257/jel.20231736 | Generative AI for Economic Research: Use Cases and Implications for Economists | 2023 | W4389615177 | |
| doi:10.1371/journal.pdig.0000416 | GPT-4 can pass the Korean National Licensing Examination for Korean Medicine Doctors | 2023 | W4389795202 | |
| doi:10.1561/9781638282099 | Tutorial on Amortized Optimization | 2023 | W4382896054 | |
| doi:10.1609/aiide.v19i1.27516 | Learning of Generalizable and Interpretable Knowledge in Grid-Based Reinforcement Learning Environments | 2023 | W4387394648 | |
| doi:10.1613/jair.1.14174 | A Survey of Zero-shot Generalisation in Deep Reinforcement Learning | 2023 | W4315487473 | |
| doi:10.1787/0e1b4c2f-en | High-performance computing leadership to enable advances in artificial intelligence and a thriving compute ecosystem | 2023 | W4382060930 | |
| doi:10.1787/1f717652-en | Quantifying the “cognitive extent” of science and how it has changed over time and across countries | 2023 | W4382061651 | |
| doi:10.1787/2d0478b9-en | Interpretability: Should – and can – we understand the reasoning of machine-learning systems? | 2023 | W4382061682 | |
| doi:10.1787/63e48242-en | The end of Moore’s Law? Innovation in computer systems continues at a high pace | 2023 | W4382061472 | |
| doi:10.1787/6f256d17-en | Eroom’s Law and the decline in the productivity of biopharmaceutical R&D | 2023 | W4382061131 | |
| doi:10.1787/7b7b1bce-en | Artificial intelligence for science and engineering: A priority for public investment in research and development | 2023 | W4382061090 | |
| doi:10.1787/b885eecd-en | Lessons from shortcomings in machine learning for medical imaging | 2023 | W4382060947 | |
| doi:10.1787/f1262928-en | Preface | 2023 | W4382061812 | |
| doi:10.18653/v1/2023.acl-long | Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) | 2023 | W2148437670 | |
| doi:10.18653/v1/2023.acl-long.147 | Plan-and-Solve Prompting: Improving Zero-Shot Chain-of-Thought Reasoning by Large Language Models | 2023 | W4385570088 | |
| doi:10.18653/v1/2023.acl-long.267 | Pre-Training to Learn in Context | 2023 | W4385569785 | |
| doi:10.18653/v1/2023.acl-long.294 | Reasoning with Language Model Prompting: A Survey | 2023 | W4385569771 | |
| doi:10.18653/v1/2023.acl-long.385 | Few-shot In-context Learning on Knowledge Base Question Answering | 2023 | W4385570025 | |
| doi:10.18653/v1/2023.acl-long.557 | Interleaving Retrieval with Chain-of-Thought Reasoning for Knowledge-Intensive Multi-Step Questions | 2023 | W4385571271 | |
| doi:10.18653/v1/2023.acl-long.626 | Is GPT-3 a Good Data Annotator? | 2023 | W4385571411 | |
| doi:10.18653/v1/2023.acl-long.727 | Exploring and Verbalizing Academic Ideas by Concept Co-occurrence | 2023 | W4385571062 | |
| doi:10.18653/v1/2023.acl-long.767 | Training Trajectories of Language Models Across Scales | 2023 | W4385570738 | |
| doi:10.18653/v1/2023.acl-long.870 | Can Large Language Models Be an Alternative to Human Evaluations? | 2023 | W4385571232 | |
| doi:10.18653/v1/2023.acl-short | Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers) | 2023 | W2759181158 | |
| doi:10.18653/v1/2023.acl-short.38 | Grokking of Hierarchical Structure in Vanilla Transformers | 2023 | W4385571966 | |
| doi:10.18653/v1/2023.conll-babylm.1 | Findings of the BabyLM Challenge: Sample-Efficient Pretraining on Developmentally Plausible Corpora | 2023 | W4389519222 | |
| doi:10.18653/v1/2023.emnlp-demo.49 | Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding | 2023 | W4389519587 | |
| doi:10.18653/v1/2023.emnlp-main.153 | G-Eval: NLG Evaluation using Gpt-4 with Better Human Alignment | 2023 | W4389519254 | |
| doi:10.18653/v1/2023.emnlp-main.313 | LINC: A Neurosymbolic Approach for Logical Reasoning by Combining Language Models with First-Order Logic Provers | 2023 | W4389518758 | |
| doi:10.18653/v1/2023.emnlp-main.322 | Query Rewriting in Retrieval-Augmented Large Language Models | 2023 | W4389518671 | |
| doi:10.18653/v1/2023.emnlp-main.330 | Just Ask for Calibration: Strategies for Eliciting Calibrated Confidence Scores from Language Models Fine-Tuned with Human Feedback | 2023 | W4389518686 | |
| doi:10.18653/v1/2023.emnlp-main.398 | Enabling Large Language Models to Generate Text with Citations | 2023 | W4389520670 | |
| doi:10.18653/v1/2023.emnlp-main.495 | Active Retrieval Augmented Generation | 2023 | W4389519118 | |
| doi:10.18653/v1/2023.emnlp-main.557 | SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Models | 2023 | W4389520749 | |
| doi:10.18653/v1/2023.findings-acl.247 | Why Can GPT Learn In-Context? Language Models Secretly Perform Gradient Descent as Meta-Optimizers | 2023 | W4385571886 | |
| doi:10.18653/v1/2023.findings-acl.507 | Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes | 2023 | W4385571011 | |
| doi:10.18653/v1/2023.findings-acl.527 | What In-Context Learning “Learns” In-Context: Disentangling Task Recognition and Task Learning | 2023 | W4385571671 | |
| doi:10.18653/v1/2023.findings-acl.660 | DePlot: One-shot visual language reasoning by plot-to-table translation | 2023 | W4385565485 | |
| doi:10.18653/v1/2023.findings-acl.67 | Towards Reasoning in Large Language Models: A Survey | 2023 | W4385571689 | |
| doi:10.18653/v1/2023.findings-acl.795 | Language Modeling with Latent Situations | 2023 | W4385572270 | |
| doi:10.18653/v1/2023.findings-acl.824 | Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them | 2023 | W4385571157 | |
| doi:10.18653/v1/2023.findings-emnlp.201 | Three Questions Concerning the Use of Large Language Models to Facilitate Mathematics Learning | 2023 | W4389524520 | |
| doi:10.18653/v1/2023.findings-emnlp.378 | Measuring and Narrowing the Compositionality Gap in Language Models | 2023 | W4389520103 | |
| doi:10.18653/v1/2023.findings-emnlp.620 | Enhancing Retrieval-Augmented Large Language Models with Iterative Retrieval-Generation Synergy | 2023 | W4389520468 | |
| doi:10.18653/v1/2023.findings-emnlp.624 | In-Context Learning Creates Task Vectors | 2023 | W4389518997 | |
| doi:10.18653/v1/2023.findings-emnlp.725 | HuatuoGPT, Towards Taming Language Model to Be a Doctor | 2023 | W4389520259 | |
| doi:10.18653/v1/2023.findings-emnlp.799 | Defining a New NLP Playground | 2023 | W4389518724 | |
| doi:10.18653/v1/2023.findings-emnlp.926 | A Comprehensive Evaluation of Tool-Assisted Generation Strategies | 2023 | W4389524004 | |
| doi:10.18653/v1/2023.ijcnlp-main.45 | A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity | 2023 | W4392669753 | |
| doi:10.18653/v1/2023.law-1.25 | When Do Annotator Demographics Matter? Measuring the Influence of Annotator Demographics with the POPQUORN Dataset | 2023 | W4385571748 | |
| doi:10.20944/preprints202305.1565.v2 | Re-think Data Strategy and Integration for Artificial Intelligence: Concepts, Opportunities and Challenges | 2023 | W4379196653 | |
| doi:10.21203/rs.3.rs-2895792/v1 | A Categorical Archive of ChatGPT Failures | 2023 | W4375949262 | |
| doi:10.2139/ssrn.4341500 | Is ChatGPT Leading Generative AI? What is Beyond Expectations? | 2023 | W4318566811 | |
| doi:10.2139/ssrn.4574814 | Generative AI: Overview, Economic Impact, and Applications in Asset Management | 2023 | W4386820356 | |
| doi:10.2139/ssrn.4605089 | A Scientific Corpus and Search Engine for Biomimetics | 2023 | W4388738990 | |
| doi:10.2139/ssrn.4621210 | Humanity Amplified: The Fusion of Deep Learning and Human Insight to Shape the Future of Innovation | 2023 | W4389125438 | |
| doi:10.31223/x52h3b | Ten deep learning techniques to address small data problems with remote sensing | 2023 | W4379980445 | |
| doi:10.31234/osf.io/8xgzv | Generating Meaning: Active Inference and the Scope and Limits of Passive AI | 2023 | W4380084928 | |
| doi:10.3386/w31161 | Generative AI at Work | 2023 | W4366817968 | |
| doi:10.3389/fnins.2023.1183321 | Meta-SpikePropamine: learning to learn with synaptic plasticity in spiking neural networks | 2023 | W4378745905 | |
| doi:10.3389/fpsyg.2023.1181712 | Reflection on whether Chat GPT should be banned by academia from the perspective of education and teaching | 2023 | W4379010216 | |
| doi:10.3389/fpubh.2023.1166120 | ChatGPT and the rise of large language models: the new AI-driven infodemic threat in public health | 2023 | W4366989525 | |
| doi:10.3390/languages8030191 | Exploring the Ethical Dimensions of Using ChatGPT in Language Learning and Beyond | 2023 | W4385812794 | |
| doi:10.36227/techrxiv.21965675 | The Optimal Choice of Hypothesis Is the Weakest, Not the Shortest | 2023 | W4318830247 | |
| doi:10.36227/techrxiv.23589741.v1 | A Survey on Large Language Models: Applications, Challenges, Limitations, and Practical Usage | 2023 | W4383737134 | |
| doi:10.36227/techrxiv.23589741.v3 | Large Language Models: A Comprehensive Survey of its Applications, Challenges, Limitations, and Future Prospects | 2023 | W4386917649 | |
| doi:10.36227/techrxiv.23589741.v4 | Large Language Models: A Comprehensive Survey of its Applications, Challenges, Limitations, and Future Prospects | 2023 | W4388725733 | |
| doi:10.38023/ad948078-108b-4c66-8d61-c2e97e270b31 | Visualization in the Era of Artificial Intelligence | 2023 | W4382999735 | |
| doi:10.4230/lipics.cosit.2024.11 | GPT-4 Technical Report | 2023 | W4327810158 | |
| doi:10.4230/lipics.giscience.2023.43 | Aion Framework: Dimensional Emergence of AI Consciousness, Observer-Induced Collapse, and Cosmological Portal Dynamics | 2023 | W4292779060 | |
| doi:10.4230/lipics.itp.2023.19 | Exploiting Generative AI to Scale up Intelligent Tutoring Systems | 2023 | W4385245566 | |
| doi:10.4324/9781003320609-52 | Race After Technology | 2023 | W3180342177 | |
| doi:10.53761/1.20.02.07 | Academic Integrity considerations of AI Large Language Models in the post-pandemic era: ChatGPT and beyond | 2023 | W4321605350 | |
| doi:10.7551/mitpress/14207.001.0001 | Distributional Reinforcement Learning | 2023 | W4322729780 | |
| doi:10.7759/cureus.50729 | Safety of Large Language Models in Addressing Depression | 2023 | W4389923012 | |
| arxiv:1606.04671 | Progressive Neural Networks | 2022 | 1606.04671 | W4319988532 |
| arxiv:2007.04074 | Auto-Sklearn 2.0: Hands-free AutoML via Meta-Learning | 2022 | 2007.04074 | |
| arxiv:2108.07258 | On the Opportunities and Risks of Foundation Models | 2022 | 2108.07258 | W3195577433 |
| arxiv:2201.02177 | Grokking: Generalization beyond overfitting on small algorithmic datasets | 2022 | 2201.02177 | W4226434736 |
| arxiv:2202.07646 | Quantifying Memorization Across Neural Language Models | 2022 | 2202.07646 | W4221159672 |
| arxiv:2203.02155 | Training language models to follow instructions with human feedback | 2022 | 2203.02155 | W4226278401 |
| arxiv:2203.11171 | Self-consistency improves chain of thought reasoning in language models | 2022 | 2203.11171 | W4221161695 |
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| arxiv:2209.11895 | In-context learning and induction heads | 2022 | 2209.11895 | W4297412003 |
| arxiv:2210.05359 | Mind’s eye: Grounded language model reasoning through simulation | 2022 | 2210.05359 | W4305028650 |
| arxiv:2210.13777 | SciFact-Open: Towards open-domain scientific claim verification | 2022 | 2210.13777 | W4385574202 |
| arxiv:2211.09085 | Galactica: A Large Language Model for Science | 2022 | 2211.09085 | W4320005767 |
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| doi:10.1007/978-3-658-38891-1_6 | Nutzen und Grenzen der KI am Beispiel der Corona-Pandemie | 2022 | W4312409867 | |
| doi:10.1007/s11263-022-01653-1 | Learning to Prompt for Vision-Language Models | 2022 | W3198377975 | |
| doi:10.1016/j.csl.2022.101429 | On the effect of dropping layers of pre-trained transformer models | 2022 | W3136363192 | |
| doi:10.1016/j.jcp.2022.111121 | Meta-learning PINN loss functions | 2022 | W3181235980 | |
| doi:10.1016/j.neunet.2022.03.037 | Deep learning, reinforcement learning, and world models | 2022 | W4224220194 | |
| doi:10.1016/j.pecs.2022.101010 | Combustion machine learning: Principles, progress and prospects | 2022 | W4224994116 | |
| doi:10.1016/j.rcim.2022.102517 | A review on reinforcement learning for contact-rich robotic manipulation tasks | 2022 | W4313442619 | |
| doi:10.1038/s42256-022-00591-4 | Language and culture internalization for human-like autotelic AI | 2022 | W4313449193 | |
| doi:10.1093/bib/bbac268 | Contexts and contradictions: a roadmap for computational drug repurposing with knowledge inference | 2022 | W4285041540 | |
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| doi:10.1093/oso/9780192843883.001.0001 | Natural General Intelligence | 2022 | W4317367956 | |
| doi:10.1093/oso/9780192843883.002.0003 | Copyright Page | 2022 | W4317367889 | |
| doi:10.1093/oso/9780192843883.002.0004 | Preface | 2022 | W4317367903 | |
| doi:10.1093/oso/9780192843883.002.0006 | Abbreviations | 2022 | W4317367929 | |
| doi:10.1093/oso/9780192843883.003.0002 | The nature of intelligence | 2022 | W4317367835 | |
| doi:10.1093/oso/9780192843883.003.0003 | The language of thought | 2022 | W4317367716 | |
| doi:10.1093/oso/9780192843883.003.0004 | The structure of knowledge | 2022 | W4317367846 | |
| doi:10.1093/oso/9780192843883.003.0006 | The value of action | 2022 | W4317367727 | |
| doi:10.1093/oso/9780192843883.003.0007 | The control of memory | 2022 | W4317367818 | |
| doi:10.1093/oso/9780192843883.003.0008 | A picture of the mind | 2022 | W4317367694 | |
| doi:10.1098/rspa.2021.0068 | Inductive biases for deep learning of higher-level cognition | 2022 | W3108981297 | |
| doi:10.1109/access.2022.3192019 | A Review of End-to-End Autonomous Driving in Urban Environments | 2022 | W4285819294 | |
| doi:10.1109/cvpr52688.2022.00024 | Learning to Prompt for Continual Learning | 2022 | W4312238419 | |
| doi:10.1109/cvpr52688.2022.00951 | Anomaly Detection via Reverse Distillation from One-Class Embedding | 2022 | W4312772600 | |
| doi:10.1109/cvpr52688.2022.01170 | Swin Transformer V2: Scaling Up Capacity and Resolution | 2022 | W4312349930 | |
| doi:10.1109/cvpr52688.2022.01179 | Scaling Vision Transformers | 2022 | W3172942063 | |
| doi:10.1109/cvpr52688.2022.01377 | MetaFSCIL: A Meta-Learning Approach for Few-Shot Class Incremental Learning | 2022 | W4313005250 | |
| doi:10.1109/cvpr52688.2022.01434 | When Does Contrastive Visual Representation Learning Work? | 2022 | W3160314846 | |
| doi:10.1109/cvpr52688.2022.01631 | Conditional Prompt Learning for Vision-Language Models | 2022 | W4312310776 | |
| doi:10.1109/icassp43922.2022.9747766 | AASIST: Audio Anti-Spoofing Using Integrated Spectro-Temporal Graph Attention Networks | 2022 | W3201773091 | |
| doi:10.1109/icde53745.2022.00077 | Federated Learning on Non-IID Data Silos: An Experimental Study | 2022 | W4287332481 | |
| doi:10.1109/icra46639.2022.9811559 | Dynamics-Aware Quality-Diversity for Efficient Learning of Skill Repertoires | 2022 | W3200285024 | |
| doi:10.1109/icra46639.2022.9812249 | Deep Drifting: Autonomous Drifting of Arbitrary Trajectories using Deep Reinforcement Learning | 2022 | W4285102561 | |
| doi:10.1109/lra.2022.3186494 | Efficient Spatiotemporal Transformer for Robotic Reinforcement Learning | 2022 | W4285179996 | |
| doi:10.1109/smc53654.2022.9945326 | Task Detection in Continual Learning via Familiarity Autoencoders | 2022 | W4309345819 | |
| doi:10.1109/sp46214.2022.9833571 | Asleep at the Keyboard? Assessing the Security of GitHub Copilot’s Code Contributions | 2022 | W4288057765 | |
| doi:10.1109/tnnls.2022.3142822 | Efficient Deep Reinforcement Learning With Imitative Expert Priors for Autonomous Driving | 2022 | W4226257065 | |
| doi:10.1109/tnnls.2022.3152527 | Learning From Noisy Labels With Deep Neural Networks: A Survey | 2022 | W3042609801 | |
| doi:10.1109/tnnls.2022.3182979 | Backdoor Learning: A Survey | 2022 | W3042368254 | |
| doi:10.1109/tpami.2022.3157033 | Constructing Stronger and Faster Baselines for Skeleton-Based Action Recognition | 2022 | W3185273257 | |
| doi:10.1109/tpami.2022.3162397 | Dataset Security for Machine Learning: Data Poisoning, Backdoor Attacks, and Defenses | 2022 | W3117572899 | |
| doi:10.1109/tpami.2022.3190471 | MetaDrive: Composing Diverse Driving Scenarios for Generalizable Reinforcement Learning | 2022 | W3203076355 | |
| doi:10.1109/tpami.2022.3213473 | Class-Incremental Learning: Survey and Performance Evaluation on Image Classification | 2022 | W3163939464 | |
| doi:10.1109/tpami.2022.3213503 | Robust Losses for Learning Value Functions | 2022 | W4306167947 | |
| doi:10.1109/tpami.2022.3220744 | The Shape of Learning Curves: A Review | 2022 | W3136016591 | |
| doi:10.1109/tsg.2022.3154718 | Reinforcement Learning for Selective Key Applications in Power Systems: Recent Advances and Future Challenges | 2022 | W4214759040 | |
| doi:10.1109/wacv51458.2022.00112 | Self-Supervised Pretraining Improves Self-Supervised Pretraining | 2022 | W3136987292 | |
| doi:10.1126/science.abq1158 | Competition-level code generation with alphacode | 2022 | ||
| doi:10.1126/scirobotics.abo0235 | From motor control to team play in simulated humanoid football | 2022 | W3164631379 | |
| doi:10.1145/3485128 | Tackling Climate Change with Machine Learning | 2022 | W2950398529 | |
| doi:10.1145/3487569 | In-IDE Code Generation from Natural Language: Promise and Challenges | 2022 | W3123221944 | |
| doi:10.1145/3501385.3543957 | Automatic Generation of Programming Exercises and Code Explanations Using Large Language Models | 2022 | W4283705032 | |
| doi:10.1145/3501714.3501755 | Causality for Machine Learning | 2022 | W2990408532 | |
| doi:10.1145/3510460 | Women’s Participation in Open Source Software: A Survey of the Literature | 2022 | W3162948197 | |
| doi:10.1145/3512290 | Proceedings of the Genetic and Evolutionary Computation Conference | 2022 | W2525203296 | |
| doi:10.1145/3512290.3528754 | Illuminating diverse neural cellular automata for level generation | 2022 | W3199753215 | |
| doi:10.1145/3530811 | Efficient Transformers: A Survey | 2022 | W3085139254 | |
| doi:10.1145/3578580 | A Universal Law of Robustness via Isoperimetry | 2022 | W3164935232 | |
| doi:10.11591/ijai.v11.i3.pp895-904 | Abusive comment identification on Indonesian social media data using hybrid deep learning | 2022 | W4283739314 | |
| doi:10.1162/tacl_a_00447 | Quality at a Glance: An Audit of Web-Crawled Multilingual Datasets | 2022 | W3137010024 | |
| doi:10.1162/tacl_a_00459 | Time-Aware Language Models as Temporal Knowledge Bases | 2022 | W3174266714 | |
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