{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:KWJD64JH2UMK6XKQY2XTGFVDE5","short_pith_number":"pith:KWJD64JH","canonical_record":{"source":{"id":"2506.01116","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2025-06-01T18:45:49Z","cross_cats_sorted":["q-bio.QM"],"title_canon_sha256":"7f6d31ea669a9a9eafc5e6deee2e47ed7849f619fda8a7fd9a78ba5d5ada81f8","abstract_canon_sha256":"7e5fa78b99ea0fc412cd8c7fbe2610a5fb10b22db05036e96b0cafcefea959c0"},"schema_version":"1.0"},"canonical_sha256":"55923f7127d518af5d50c6af3316a32775504035f90b572c37397c33f9817d24","source":{"kind":"arxiv","id":"2506.01116","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.01116","created_at":"2026-07-05T11:13:46Z"},{"alias_kind":"arxiv_version","alias_value":"2506.01116v1","created_at":"2026-07-05T11:13:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.01116","created_at":"2026-07-05T11:13:46Z"},{"alias_kind":"pith_short_12","alias_value":"KWJD64JH2UMK","created_at":"2026-07-05T11:13:46Z"},{"alias_kind":"pith_short_16","alias_value":"KWJD64JH2UMK6XKQ","created_at":"2026-07-05T11:13:46Z"},{"alias_kind":"pith_short_8","alias_value":"KWJD64JH","created_at":"2026-07-05T11:13:46Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:KWJD64JH2UMK6XKQY2XTGFVDE5","target":"record","payload":{"canonical_record":{"source":{"id":"2506.01116","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2025-06-01T18:45:49Z","cross_cats_sorted":["q-bio.QM"],"title_canon_sha256":"7f6d31ea669a9a9eafc5e6deee2e47ed7849f619fda8a7fd9a78ba5d5ada81f8","abstract_canon_sha256":"7e5fa78b99ea0fc412cd8c7fbe2610a5fb10b22db05036e96b0cafcefea959c0"},"schema_version":"1.0"},"canonical_sha256":"55923f7127d518af5d50c6af3316a32775504035f90b572c37397c33f9817d24","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:13:46.722723Z","signature_b64":"llEDE0o2OLd2puIjBS1A5Yckrhy2vgwYxooH4Yy82RJxzybZfJi4bwcvPpM6Bm35AXoQwCWb1Z7LL3qXlzYaBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"55923f7127d518af5d50c6af3316a32775504035f90b572c37397c33f9817d24","last_reissued_at":"2026-07-05T11:13:46.722334Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:13:46.722334Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2506.01116","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:13:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aalpgMrCdhTDP4qmt5c0rF2hdXY7u3BtYtdRZhL+pVC9YzztocGpTT+St6LQQ48psll8Y/d5ArSK6xyF8FFtCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T10:30:17.065768Z"},"content_sha256":"ad135850d8bca0976b4eef0914619bc1f0534f54c7bc29697de9fd5cbfa0c6df","schema_version":"1.0","event_id":"sha256:ad135850d8bca0976b4eef0914619bc1f0534f54c7bc29697de9fd5cbfa0c6df"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:KWJD64JH2UMK6XKQY2XTGFVDE5","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"ChemAU: Harness the Reasoning of LLMs in Chemical Research with Adaptive Uncertainty Estimation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["q-bio.QM"],"primary_cat":"cs.AI","authors_text":"Ben Fei, Jiayi Song, Lipeng Ma, Qingyuan Zhou, Shuhao Li, Weidong Yang, Xinyi Liu, Yixuan Li","submitted_at":"2025-06-01T18:45:49Z","abstract_excerpt":"Large Language Models (LLMs) are widely used across various scenarios due to their exceptional reasoning capabilities and natural language understanding. While LLMs demonstrate strong performance in tasks involving mathematics and coding, their effectiveness diminishes significantly when applied to chemistry-related problems. Chemistry problems typically involve long and complex reasoning steps, which contain specific terminology, including specialized symbol systems and complex nomenclature conventions. These characteristics often cause general LLMs to experience hallucinations during the rea"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.01116","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/2506.01116/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:13:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ytI48xh6w+haSzKLaMyN8b/AKJSW5crOMSgw0V/qFVnC24LMutyehz3hpRgT0VJNxubWGx8HMU1ja9L27MERCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T10:30:17.066395Z"},"content_sha256":"d69b217768a8038327670f1959aa9c00d2f39f3b5d8127038e9d650f5fd1482d","schema_version":"1.0","event_id":"sha256:d69b217768a8038327670f1959aa9c00d2f39f3b5d8127038e9d650f5fd1482d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/KWJD64JH2UMK6XKQY2XTGFVDE5/bundle.json","state_url":"https://pith.science/pith/KWJD64JH2UMK6XKQY2XTGFVDE5/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/KWJD64JH2UMK6XKQY2XTGFVDE5/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-09T10:30:17Z","links":{"resolver":"https://pith.science/pith/KWJD64JH2UMK6XKQY2XTGFVDE5","bundle":"https://pith.science/pith/KWJD64JH2UMK6XKQY2XTGFVDE5/bundle.json","state":"https://pith.science/pith/KWJD64JH2UMK6XKQY2XTGFVDE5/state.json","well_known_bundle":"https://pith.science/.well-known/pith/KWJD64JH2UMK6XKQY2XTGFVDE5/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:KWJD64JH2UMK6XKQY2XTGFVDE5","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":"7e5fa78b99ea0fc412cd8c7fbe2610a5fb10b22db05036e96b0cafcefea959c0","cross_cats_sorted":["q-bio.QM"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2025-06-01T18:45:49Z","title_canon_sha256":"7f6d31ea669a9a9eafc5e6deee2e47ed7849f619fda8a7fd9a78ba5d5ada81f8"},"schema_version":"1.0","source":{"id":"2506.01116","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.01116","created_at":"2026-07-05T11:13:46Z"},{"alias_kind":"arxiv_version","alias_value":"2506.01116v1","created_at":"2026-07-05T11:13:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.01116","created_at":"2026-07-05T11:13:46Z"},{"alias_kind":"pith_short_12","alias_value":"KWJD64JH2UMK","created_at":"2026-07-05T11:13:46Z"},{"alias_kind":"pith_short_16","alias_value":"KWJD64JH2UMK6XKQ","created_at":"2026-07-05T11:13:46Z"},{"alias_kind":"pith_short_8","alias_value":"KWJD64JH","created_at":"2026-07-05T11:13:46Z"}],"graph_snapshots":[{"event_id":"sha256:d69b217768a8038327670f1959aa9c00d2f39f3b5d8127038e9d650f5fd1482d","target":"graph","created_at":"2026-07-05T11:13:46Z","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/2506.01116/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large Language Models (LLMs) are widely used across various scenarios due to their exceptional reasoning capabilities and natural language understanding. While LLMs demonstrate strong performance in tasks involving mathematics and coding, their effectiveness diminishes significantly when applied to chemistry-related problems. Chemistry problems typically involve long and complex reasoning steps, which contain specific terminology, including specialized symbol systems and complex nomenclature conventions. These characteristics often cause general LLMs to experience hallucinations during the rea","authors_text":"Ben Fei, Jiayi Song, Lipeng Ma, Qingyuan Zhou, Shuhao Li, Weidong Yang, Xinyi Liu, Yixuan Li","cross_cats":["q-bio.QM"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2025-06-01T18:45:49Z","title":"ChemAU: Harness the Reasoning of LLMs in Chemical Research with Adaptive Uncertainty Estimation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.01116","kind":"arxiv","version":1},"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:ad135850d8bca0976b4eef0914619bc1f0534f54c7bc29697de9fd5cbfa0c6df","target":"record","created_at":"2026-07-05T11:13:46Z","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":"7e5fa78b99ea0fc412cd8c7fbe2610a5fb10b22db05036e96b0cafcefea959c0","cross_cats_sorted":["q-bio.QM"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2025-06-01T18:45:49Z","title_canon_sha256":"7f6d31ea669a9a9eafc5e6deee2e47ed7849f619fda8a7fd9a78ba5d5ada81f8"},"schema_version":"1.0","source":{"id":"2506.01116","kind":"arxiv","version":1}},"canonical_sha256":"55923f7127d518af5d50c6af3316a32775504035f90b572c37397c33f9817d24","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"55923f7127d518af5d50c6af3316a32775504035f90b572c37397c33f9817d24","first_computed_at":"2026-07-05T11:13:46.722334Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:13:46.722334Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"llEDE0o2OLd2puIjBS1A5Yckrhy2vgwYxooH4Yy82RJxzybZfJi4bwcvPpM6Bm35AXoQwCWb1Z7LL3qXlzYaBA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:13:46.722723Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.01116","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ad135850d8bca0976b4eef0914619bc1f0534f54c7bc29697de9fd5cbfa0c6df","sha256:d69b217768a8038327670f1959aa9c00d2f39f3b5d8127038e9d650f5fd1482d"],"state_sha256":"9f787be35cedc57bbf13619c74b858aa0d706558832c34fe8d45c785e30289a1"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jxRnKgIlEcNZ7aaU1O7akDrRLVGgvCxVsphhZSeXEPFiCIXSzJG/zq2cr3yoYVDKj7ws7+gy7Lon5arocTUsDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T10:30:17.071913Z","bundle_sha256":"7d85a4a01270537ffb81ce1fc188ee3d8b9f7d4d1bb138ba3d5eb101097f03b7"}}