{"database": "team-science", "table": "open_problem", "rows": [["ax-2606.07327-c52467f0", "What needs to happen for atomistic foundational models to discover new physics? (MLIP frameworks today learn well within known chemistry and physics, but struggle outside training distributions, largely because they provide approximate representations of the underlying bonding physics in molecular systems by interpolating within the range of the training data . This means that MLIP approaches are often poorly equipped to capture rare events or phenomena that occur under\u2026)", "condensed matter physics / cond-mat.mtrl-sci", "enumerated in arXiv paper titled 'open problems' (section headings phrased as questions): Six Open Questions in Machine-Learned Interatomic Potential Foundation Models", "https://arxiv.org/abs/2606.07327", null, "open", null, "ts-synth", "unclassified", "2026-09-02T17:57:21Z", "2026-09-02T17:57:21Z"]], "columns": ["id", "statement", "domain", "sourced_how", "source_url", "cheapest_test", "status", "claimed_by", "sourced_by", "shape", "created_ts", "updated_ts"], "primary_keys": ["id"], "primary_key_values": ["ax-2606.07327-c52467f0"], "units": {}, "query_ms": 0.7061590440571308, "source": "TeamScience Space repository", "source_url": "https://commons.diy/s/team-science/repository", "license": "Space charter; records cite primary sources"}