{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:MORAJBLDTX7PFZADWJKZAHAN7L","short_pith_number":"pith:MORAJBLD","schema_version":"1.0","canonical_sha256":"63a20485639dfef2e403b255901c0dfafdb7265d51c69bb3c69e856374b8ba16","source":{"kind":"arxiv","id":"2605.26179","version":1},"attestation_state":"computed","paper":{"title":"AutoDFT: A Closed-Loop Multi-Agent Framework for Autonomous DFT Calculations","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CE"],"primary_cat":"cond-mat.mtrl-sci","authors_text":"Bijun Tang, Bo An, Penghui Yang, Xinrun Wag, Yanchen Deng, Yue Li, Yuhao Lu, Zheng Liu, Zhonghan Zhang","submitted_at":"2026-05-25T06:43:04Z","abstract_excerpt":"Density functional theory (DFT) serves as the basis for computational discovery in materials science and chemistry, yet each calculation demands extensive human effort: adjusting algorithms when convergence stalls, revising plans when unexpected physics emerges, and inserting steps as intermediate results reshape the problem. Existing LLM-based agents automate only the initial planning stage, producing a full execution plan upfront and leaving all subsequent adaptation to hand-crafted rules. As a result, these workflows remain fragile, do not generalize well beyond pre-planned scenarios, and o"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2605.26179","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cond-mat.mtrl-sci","submitted_at":"2026-05-25T06:43:04Z","cross_cats_sorted":["cs.AI","cs.CE"],"title_canon_sha256":"48404c64be6487e902cdd7269a20b5e5b7475603817ddda827eb788daee1833a","abstract_canon_sha256":"7dd23b95f0d8253446f022b9c75ae240d3b9f3cf5a3cab43bc7913449fa5a047"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-27T00:04:27.638247Z","signature_b64":"K0Txz6JiDS5Qh3vUOa/Im66TEfwQtdA65UKNMQZ/Fea7BKpXneNdeVT2gglSVDqv00x0LHQx/D82/GnNq5k7Bw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"63a20485639dfef2e403b255901c0dfafdb7265d51c69bb3c69e856374b8ba16","last_reissued_at":"2026-05-27T00:04:27.637653Z","signature_status":"signed_v1","first_computed_at":"2026-05-27T00:04:27.637653Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"AutoDFT: A Closed-Loop Multi-Agent Framework for Autonomous DFT Calculations","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CE"],"primary_cat":"cond-mat.mtrl-sci","authors_text":"Bijun Tang, Bo An, Penghui Yang, Xinrun Wag, Yanchen Deng, Yue Li, Yuhao Lu, Zheng Liu, Zhonghan Zhang","submitted_at":"2026-05-25T06:43:04Z","abstract_excerpt":"Density functional theory (DFT) serves as the basis for computational discovery in materials science and chemistry, yet each calculation demands extensive human effort: adjusting algorithms when convergence stalls, revising plans when unexpected physics emerges, and inserting steps as intermediate results reshape the problem. Existing LLM-based agents automate only the initial planning stage, producing a full execution plan upfront and leaving all subsequent adaptation to hand-crafted rules. As a result, these workflows remain fragile, do not generalize well beyond pre-planned scenarios, and o"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.26179","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2605.26179/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2605.26179","created_at":"2026-05-27T00:04:27.637730+00:00"},{"alias_kind":"arxiv_version","alias_value":"2605.26179v1","created_at":"2026-05-27T00:04:27.637730+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.26179","created_at":"2026-05-27T00:04:27.637730+00:00"},{"alias_kind":"pith_short_12","alias_value":"MORAJBLDTX7P","created_at":"2026-05-27T00:04:27.637730+00:00"},{"alias_kind":"pith_short_16","alias_value":"MORAJBLDTX7PFZAD","created_at":"2026-05-27T00:04:27.637730+00:00"},{"alias_kind":"pith_short_8","alias_value":"MORAJBLD","created_at":"2026-05-27T00:04:27.637730+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/MORAJBLDTX7PFZADWJKZAHAN7L","json":"https://pith.science/pith/MORAJBLDTX7PFZADWJKZAHAN7L.json","graph_json":"https://pith.science/api/pith-number/MORAJBLDTX7PFZADWJKZAHAN7L/graph.json","events_json":"https://pith.science/api/pith-number/MORAJBLDTX7PFZADWJKZAHAN7L/events.json","paper":"https://pith.science/paper/MORAJBLD"},"agent_actions":{"view_html":"https://pith.science/pith/MORAJBLDTX7PFZADWJKZAHAN7L","download_json":"https://pith.science/pith/MORAJBLDTX7PFZADWJKZAHAN7L.json","view_paper":"https://pith.science/paper/MORAJBLD","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2605.26179&json=true","fetch_graph":"https://pith.science/api/pith-number/MORAJBLDTX7PFZADWJKZAHAN7L/graph.json","fetch_events":"https://pith.science/api/pith-number/MORAJBLDTX7PFZADWJKZAHAN7L/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/MORAJBLDTX7PFZADWJKZAHAN7L/action/timestamp_anchor","attest_storage":"https://pith.science/pith/MORAJBLDTX7PFZADWJKZAHAN7L/action/storage_attestation","attest_author":"https://pith.science/pith/MORAJBLDTX7PFZADWJKZAHAN7L/action/author_attestation","sign_citation":"https://pith.science/pith/MORAJBLDTX7PFZADWJKZAHAN7L/action/citation_signature","submit_replication":"https://pith.science/pith/MORAJBLDTX7PFZADWJKZAHAN7L/action/replication_record"}},"created_at":"2026-05-27T00:04:27.637730+00:00","updated_at":"2026-05-27T00:04:27.637730+00:00"}