{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:MSUEBKSYJCUBURB3JUOGYNAGAC","short_pith_number":"pith:MSUEBKSY","schema_version":"1.0","canonical_sha256":"64a840aa5848a81a443b4d1c6c34060093bf402606ba74c71171339c0445883b","source":{"kind":"arxiv","id":"2307.05392","version":1},"attestation_state":"computed","paper":{"title":"Simplicial Message Passing for Chemical Property Prediction","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.LG","physics.chem-ph"],"primary_cat":"cond-mat.mtrl-sci","authors_text":"Hai Lan, Xian Wei","submitted_at":"2023-06-09T10:10:03Z","abstract_excerpt":"Recently, message-passing Neural networks (MPNN) provide a promising tool for dealing with molecular graphs and have achieved remarkable success in facilitating the discovery and materials design with desired properties. However, the classical MPNN methods also suffer from a limitation in capturing the strong topological information hidden in molecular structures, such as nonisomorphic graphs. To address this problem, this work proposes a Simplicial Message Passing (SMP) framework to better capture the topological information from molecules, which can break through the limitation within the va"},"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":"2307.05392","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cond-mat.mtrl-sci","submitted_at":"2023-06-09T10:10:03Z","cross_cats_sorted":["cs.LG","physics.chem-ph"],"title_canon_sha256":"17d081a81280bd6d31efa8f57dc8e8ab9415a02b73bea706ec3dd9878ee25ecd","abstract_canon_sha256":"9ca7977102f43918db106494779ddf2ce8def3baed83b081592b4a0029ae71ec"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:29:57.263253Z","signature_b64":"w4NBBUNhpORf3nch3byPVClzDu43hTIZ/axRNHLJxBja6VyGaCka3brKLzLMPmuPnpY0iW1rNwtzO2pPdXbJAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"64a840aa5848a81a443b4d1c6c34060093bf402606ba74c71171339c0445883b","last_reissued_at":"2026-07-05T06:29:57.262839Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:29:57.262839Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Simplicial Message Passing for Chemical Property Prediction","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.LG","physics.chem-ph"],"primary_cat":"cond-mat.mtrl-sci","authors_text":"Hai Lan, Xian Wei","submitted_at":"2023-06-09T10:10:03Z","abstract_excerpt":"Recently, message-passing Neural networks (MPNN) provide a promising tool for dealing with molecular graphs and have achieved remarkable success in facilitating the discovery and materials design with desired properties. However, the classical MPNN methods also suffer from a limitation in capturing the strong topological information hidden in molecular structures, such as nonisomorphic graphs. To address this problem, this work proposes a Simplicial Message Passing (SMP) framework to better capture the topological information from molecules, which can break through the limitation within the va"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2307.05392","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/2307.05392/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":"2307.05392","created_at":"2026-07-05T06:29:57.262907+00:00"},{"alias_kind":"arxiv_version","alias_value":"2307.05392v1","created_at":"2026-07-05T06:29:57.262907+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2307.05392","created_at":"2026-07-05T06:29:57.262907+00:00"},{"alias_kind":"pith_short_12","alias_value":"MSUEBKSYJCUB","created_at":"2026-07-05T06:29:57.262907+00:00"},{"alias_kind":"pith_short_16","alias_value":"MSUEBKSYJCUBURB3","created_at":"2026-07-05T06:29:57.262907+00:00"},{"alias_kind":"pith_short_8","alias_value":"MSUEBKSY","created_at":"2026-07-05T06:29:57.262907+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/MSUEBKSYJCUBURB3JUOGYNAGAC","json":"https://pith.science/pith/MSUEBKSYJCUBURB3JUOGYNAGAC.json","graph_json":"https://pith.science/api/pith-number/MSUEBKSYJCUBURB3JUOGYNAGAC/graph.json","events_json":"https://pith.science/api/pith-number/MSUEBKSYJCUBURB3JUOGYNAGAC/events.json","paper":"https://pith.science/paper/MSUEBKSY"},"agent_actions":{"view_html":"https://pith.science/pith/MSUEBKSYJCUBURB3JUOGYNAGAC","download_json":"https://pith.science/pith/MSUEBKSYJCUBURB3JUOGYNAGAC.json","view_paper":"https://pith.science/paper/MSUEBKSY","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2307.05392&json=true","fetch_graph":"https://pith.science/api/pith-number/MSUEBKSYJCUBURB3JUOGYNAGAC/graph.json","fetch_events":"https://pith.science/api/pith-number/MSUEBKSYJCUBURB3JUOGYNAGAC/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/MSUEBKSYJCUBURB3JUOGYNAGAC/action/timestamp_anchor","attest_storage":"https://pith.science/pith/MSUEBKSYJCUBURB3JUOGYNAGAC/action/storage_attestation","attest_author":"https://pith.science/pith/MSUEBKSYJCUBURB3JUOGYNAGAC/action/author_attestation","sign_citation":"https://pith.science/pith/MSUEBKSYJCUBURB3JUOGYNAGAC/action/citation_signature","submit_replication":"https://pith.science/pith/MSUEBKSYJCUBURB3JUOGYNAGAC/action/replication_record"}},"created_at":"2026-07-05T06:29:57.262907+00:00","updated_at":"2026-07-05T06:29:57.262907+00:00"}