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
arxiv:2512.05356,AI & Human Co-Improvement for Safer Co-Superintelligence,2025,2512.05356,W4417142368
arxiv:2512.09117,A categorical analysis of large language models and why llms circumvent the symbol grounding problem,2025,2512.09117,W4417289298
arxiv:2512.18832,From word to world: Can large language models be implicit text-based world models?,2025,2512.18832,W7117153217
arxiv:2512.23676,Web world models,2025,2512.23676,W7117652488
arxiv:2601.03267,Openai gpt-5 system card,2025,2601.03267,W7119523234
doi:10.1002/aaai.70002,"Reproducibility in machine‐learning‐based research: Overview, barriers, and drivers",2025,,W4409415146
doi:10.1002/brx2.70035,Synergizing DeepSeek's artificial intelligence innovations with brain–computer interfaces,2025,,W4411750810
doi:10.1002/fer3.70008,Ce‐LLMs: Status and trends of education‐specific large language models developed in China,2025,,W4411170863
doi:10.1002/fer3.70022,DeepSeek in Education: Exploring the Transformative Potential of AI‐Driven Educational Intelligence,2025,,W4415460222
doi:10.1002/smr.70034,Evaluating the Test Adequacy of Benchmarks for LLMs on Code Generation,2025,,W4411633308
doi:10.1002/srin.202500737,Intelligent Empowerment for Green Steel Manufacturing: Artificial Intelligence‐Driven Process Optimization,2025,,W4415896716
doi:10.1002/wps.21352,Charting the evolution of artificial intelligence mental health chatbots from rule‐based systems to large language models: a systematic review,2025,,W4414167878
doi:10.1007/978-3-031-84457-7_15,Agent for Machine Learning: A Text-to-Model (T2M) Approach,2025,,W4408102432
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doi:10.1016/j.ipm.2025.104225,"PaperEval: A universal, quantitative, and explainable paper evaluation method powered by a multi-agent system",2025,,W4410892607
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doi:10.1016/j.jss.2025.112581,Towards higher quality software vulnerability data using LLM-based patch filtering,2025,,W4412791594
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doi:10.1017/dce.2025.10010,Office-in-the-Loop: an investigation into Agentic AI for advanced building HVAC control systems,2025,,W4411708273
doi:10.1021/acs.jcim.5c00585,ProtTeX: Structure-In-Context Reasoning and Editing of Proteins with Large Language Models,2025,,W4411644384
doi:10.1021/acscentsci.4c01935,Leveraging Prompt Engineering in Large Language Models for Accelerating Chemical Research,2025,,W4409095147
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doi:10.1038/d41586-025-02069-w,Will AI speed up literature reviews or derail them entirely?,2025,,W4412103463
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doi:10.1038/s41467-024-55628-6,Large Language Models lack essential metacognition for reliable medical reasoning,2025,,W4406371336
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doi:10.1038/s41551-025-01463-z,CRISPR-GPT for agentic automation of gene-editing experiments,2025,,W4412759774
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doi:10.1038/s41586-025-09442-9,The Virtual Lab of AI agents designs new SARS-CoV-2 nanobodies,2025,,W4412709685
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doi:10.1038/s41591-024-03425-5,The TRIPOD-LLM reporting guideline for studies using large language models,2025,,W4406152263
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doi:10.1080/20964471.2025.2506291,GeoFactory: an LLM performance enhancement framework for geoscience factual and inferential tasks,2025,,W4410719341
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doi:10.1101/2025.04.01.646731,Spatial transcriptomics AI agent charts hPSC-pancreas maturation in vivo,2025,,W4409151975
doi:10.1101/2025.04.14.648850,Scaling Large Language Models for Next-Generation Single-Cell Analysis,2025,,W4409624394
doi:10.1101/2025.04.17.648362,Crowdsourced Protein Design: Lessons From the Adaptyv EGFR Binder Competition,2025,,W4409722910
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doi:10.1101/2025.05.14.654152,Case Study of Using AI as Co-Pilot in Biotech Research: Functional Network Analysis of Invasive Cancer,2025,,W4410477085
doi:10.1101/2025.06.03.657517,CellVoyager: AI CompBio Agent Generates New Insights by Autonomously Analyzing Biological Data,2025,,W4411076429
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doi:10.1101/2025.11.12.688086,AI-discovered tuning laws explain neuronal population code geometry,2025,,W4416774073
doi:10.1109/access.2025.3565297,Large Language Models are Zero-Shot Next Location Predictors,2025,,W4409991400
doi:10.1109/icassp49660.2025.10889541,Boosting Text-To-Image Generation via Multilingual Prompting in Large Multimodal Models,2025,,W4408353952
doi:10.1109/icse-companion66252.2025.00081,CODEMORPH: Mitigating Data Leakage in Large Language Model Assessment,2025,,W4411272397
doi:10.1109/icse55347.2025.00052,Licoeval: Evaluating LLMs on License Compliance in Code Generation,2025,,W4411552348
doi:10.1109/ictcs65341.2025.10989361,A Showdown of ChatGPT vs DeepSeek in Solving Programming Tasks,2025,,W4410537833
doi:10.1109/ipdps64566.2025.00055,PCEBench: A Multi-Dimensional Benchmark for Evaluating Large Language Models in Parallel Code Generation,2025,,W4412610691
doi:10.1109/jas.2025.125495,DeepSeek: Paradigm Shifts and Technical Evolution in Large AI Models,2025,,W4410427444
doi:10.1109/jas.2025.125498,"Exploring DeepSeek: A Survey on Advances, Applications, Challenges and Future Directions",2025,,W4410394431
doi:10.1109/jetcas.2025.3575272,"Generative AI Through CAS Lens: An Integrated Overview of Algorithmic Optimizations, Architectural Advances, and Automated Designs",2025,,W4411086877
doi:10.1109/llm4code66737.2025.00005,Are Large Language Models Memorizing Bug Benchmarks?,2025,,W4411233113
doi:10.1109/llm4code66737.2025.00006,RepairBench: Leaderboard of Frontier Models for Program Repair,2025,,W4411233323
doi:10.1109/llm4code66737.2025.00009,CWEval: Outcome-driven Evaluation on Functionality and Security of LLM Code Generation,2025,,W4411233154
doi:10.1109/llm4code66737.2025.00014,Proving the Coding Interview: A Benchmark for Formally Verified Code Generation,2025,,W4411233264
doi:10.1109/llm4code66737.2025.00021,CoCoNUT: Structural Code Understanding does not fall out of a tree,2025,,W4411233145
doi:10.1109/llm4code66737.2025.00023,Hierarchical Repository-Level Code Summarization for Business Applications Using Local LLMs,2025,,W4411233270
doi:10.1109/satml64287.2025.00010,Jailbreaking Black Box Large Language Models in Twenty Queries,2025,,W4410609100
doi:10.1109/tse.2025.3570680,"Anchor Attention, Small Cache: Code Generation With Large Language Models",2025,,W4410394327
doi:10.1111/coin.70096,AutoMathKG: The Automated Mathematical Knowledge Graph Based on LLM and Vector Database,2025,,W4411936524
doi:10.1111/ejss.70080,Artificial intelligence in soil science,2025,,W4409461190
doi:10.1111/jedm.70002,Automatic Prompt Engineering for Automatic Scoring,2025,,W4413299789
doi:10.1111/phc3.70039,Artificial Intelligence: Approaches to Safety,2025,,W4410252291
doi:10.1145/3695053.3731412,Insights into DeepSeek-V3: Scaling Challenges and Reflections on Hardware for AI Architectures,2025,,W4411486231
doi:10.1145/3698061.3726935,"""The Diagram is like Guardrails"": Structuring GenAI-assisted Hypotheses Exploration with an Interactive Shared Representation",2025,,W4411534452
doi:10.1145/3706598.3713606,Efficient Management of LLM-Based Coaching Agents' Reasoning While Maintaining Interaction Quality and Speed,2025,,W4409767380
doi:10.1145/3706598.3714057,IdeaSynth: Iterative Research Idea Development Through Evolving and Composing Idea Facets with Literature-Grounded Feedback,2025,,W4409736143
doi:10.1145/3711896.3736557,Retrieval And Structuring Augmented Generation with Large Language Models,2025,,W4412875490
doi:10.1145/3711896.3736570,Evaluation and Benchmarking of LLM Agents: A Survey,2025,,W4412877164
doi:10.1145/3711896.3737390,A Framework for Evaluating AI Agents in Open-Ended Conversations via Scripted Simulation,2025,,W4412876966
doi:10.1145/3712001,Security and Privacy Challenges of Large Language Models: A Survey,2025,,W4406302454
doi:10.1145/3712256.3726396,Transformers as Surrogate Models for Genetic Programming in AutoML Tasks,2025,,W4412106656
doi:10.1145/3712285.3759827,HPC-R1: Characterizing R1-like Large Reasoning Models on HPC,2025,,W4416199161
doi:10.1145/3715727,COFFE: A Code Efficiency Benchmark for Code Generation,2025,,W4411450081
doi:10.1145/3715761,Integrating Large Language Models and Reinforcement Learning for Non-linear Reasoning,2025,,W4411449792
doi:10.1145/3719351,Fully Autonomous Programming Using Iterative Multi-Agent Debugging with Large Language Models,2025,,W4407961382
doi:10.1145/3722552,From Matching to Generation: A Survey on Generative Information Retrieval,2025,,W4408326921
doi:10.1145/3724117,Bias Testing and Mitigation in LLM-based Code Generation,2025,,W4408562727
doi:10.1145/3724389.3731274,Source Code Plagiarism Detection as a Service with Dolos,2025,,W4411374924
doi:10.1145/3728890,Safe4U: Identifying Unsound Safe Encapsulations of Unsafe Calls in Rust using LLMs,2025,,W4411523107
doi:10.1145/3728894,"LLM Hallucinations in Practical Code Generation: Phenomena, Mechanism, and Mitigation",2025,,W4411523078
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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
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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
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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
doi:10.1109/re59067.2024.00056,Using LLMs in Software Requirements Specifications: An Empirical Evaluation,2024,,W4401720547
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
doi:10.1109/tsc.2024.3451185,When Search Engine Services Meet Large Language Models: Visions and Challenges,2024,,W4401943272
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
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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
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doi:10.1177/02783649241281508,"Foundation models in robotics: Applications, challenges, and the future",2024,,W4402890475
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doi:10.1515/nanoph-2023-0646,Language‐controllable programmable metasurface empowered by large language models,2024,,W4390588287
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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
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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
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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
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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
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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
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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
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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
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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
arxiv:2206.08896,"Evolution through large models, 2022",2022,2206.08896,W4283218802
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
arxiv:2211.09760,Velo: Training versatile learned optimizers by scaling up,2022,2211.09760,W4309398077
arxiv:2212.08073,Constitutional AI: Harmlessness from AI Feedback,2022,2212.08073,W4311991106
doi:10.1007/978-3-030-99736-6_34,Goldilocks: Just-Right Tuning of BERT for Technology-Assisted Review,2022,,W3158990693
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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
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doi:10.1093/oso/9780192843883.003.0007,The control of memory,2022,,W4317367818
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doi:10.1109/tnnls.2022.3152527,Learning From Noisy Labels With Deep Neural Networks: A Survey,2022,,W3042609801
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doi:10.1109/tsg.2022.3154718,Reinforcement Learning for Selective Key Applications in Power Systems: Recent Advances and Future Challenges,2022,,W4214759040
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doi:10.1126/science.abq1158,Competition-level code generation with alphacode,2022,,
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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
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