{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:4CRA3TSJVGZ2UTA5AF42CQSE74","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"224146ab0254e6ea73a4c580ad9f2861d59f7e611f2f66efb6dfedd17c3e7afa","cross_cats_sorted":["cond-mat.mtrl-sci","cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-01-30T18:37:45Z","title_canon_sha256":"6e55a67aba716a4444c991d316d94caabb0c354da5e2a5b691a9adfcecb8f1d7"},"schema_version":"1.0","source":{"id":"2401.17244","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2401.17244","created_at":"2026-07-05T09:18:22Z"},{"alias_kind":"arxiv_version","alias_value":"2401.17244v3","created_at":"2026-07-05T09:18:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2401.17244","created_at":"2026-07-05T09:18:22Z"},{"alias_kind":"pith_short_12","alias_value":"4CRA3TSJVGZ2","created_at":"2026-07-05T09:18:22Z"},{"alias_kind":"pith_short_16","alias_value":"4CRA3TSJVGZ2UTA5","created_at":"2026-07-05T09:18:22Z"},{"alias_kind":"pith_short_8","alias_value":"4CRA3TSJ","created_at":"2026-07-05T09:18:22Z"}],"graph_snapshots":[{"event_id":"sha256:6b18892aa25c4b8cedb4792cae9c63420a6abc934722b8f0466360e39903411c","target":"graph","created_at":"2026-07-05T09:18:22Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2401.17244/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Reducing hallucination of Large Language Models (LLMs) is imperative for use in the sciences, where reliability and reproducibility are crucial. However, LLMs inherently lack long-term memory, making it a nontrivial, ad hoc, and inevitably biased task to fine-tune them on domain-specific literature and data. Here we introduce LLaMP, a multimodal retrieval-augmented generation (RAG) framework of hierarchical reasoning-and-acting (ReAct) agents that can dynamically and recursively interact with computational and experimental data on Materials Project (MP) and run atomistic simulations via high-t","authors_text":"Chia-Hong Chou, Elvis Hsieh, Janosh Riebesell, Yuan Chiang","cross_cats":["cond-mat.mtrl-sci","cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-01-30T18:37:45Z","title":"LLaMP: Large Language Model Made Powerful for High-fidelity Materials Knowledge Retrieval and Distillation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2401.17244","kind":"arxiv","version":3},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:4e19221fe0c202314808d98e5e9987f956ee05eee2b6fd374e93d5d0b36fe093","target":"record","created_at":"2026-07-05T09:18:22Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"224146ab0254e6ea73a4c580ad9f2861d59f7e611f2f66efb6dfedd17c3e7afa","cross_cats_sorted":["cond-mat.mtrl-sci","cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-01-30T18:37:45Z","title_canon_sha256":"6e55a67aba716a4444c991d316d94caabb0c354da5e2a5b691a9adfcecb8f1d7"},"schema_version":"1.0","source":{"id":"2401.17244","kind":"arxiv","version":3}},"canonical_sha256":"e0a20dce49a9b3aa4c1d0179a14244ff01d1148fdeb5338431667c199840db72","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e0a20dce49a9b3aa4c1d0179a14244ff01d1148fdeb5338431667c199840db72","first_computed_at":"2026-07-05T09:18:22.545381Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:18:22.545381Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"SV+3v+2jmJC7CJYJ3lFohknXoX75ESoVN4+1Kq1fCJF7Ka6UrH3CevvkcwXyfGFwYtJdsgYHcnUMHVXUB0gLDA==","signature_status":"signed_v1","signed_at":"2026-07-05T09:18:22.545899Z","signed_message":"canonical_sha256_bytes"},"source_id":"2401.17244","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4e19221fe0c202314808d98e5e9987f956ee05eee2b6fd374e93d5d0b36fe093","sha256:6b18892aa25c4b8cedb4792cae9c63420a6abc934722b8f0466360e39903411c"],"state_sha256":"f76ca125284d2d21cd61b6ccef723ea500ef64b0774308b12cae05b2a03446f9"}