{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:HQ6LNWNU7RMA6FSF26HORW3GVB","short_pith_number":"pith:HQ6LNWNU","canonical_record":{"source":{"id":"2407.04903","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-07-06T00:40:53Z","cross_cats_sorted":["cs.AI","cs.CV"],"title_canon_sha256":"8b90565966051a20ff2e12868f50b1a714d6491cd5b91cd726afb001852c8977","abstract_canon_sha256":"fd54616726ed427ea7781a7b9c4403fd62af8f85374dfa29168896a929e41153"},"schema_version":"1.0"},"canonical_sha256":"3c3cb6d9b4fc580f1645d78ee8db66a8475ef66fd893c3e3a2636f5adba76a27","source":{"kind":"arxiv","id":"2407.04903","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.04903","created_at":"2026-07-05T10:17:09Z"},{"alias_kind":"arxiv_version","alias_value":"2407.04903v3","created_at":"2026-07-05T10:17:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.04903","created_at":"2026-07-05T10:17:09Z"},{"alias_kind":"pith_short_12","alias_value":"HQ6LNWNU7RMA","created_at":"2026-07-05T10:17:09Z"},{"alias_kind":"pith_short_16","alias_value":"HQ6LNWNU7RMA6FSF","created_at":"2026-07-05T10:17:09Z"},{"alias_kind":"pith_short_8","alias_value":"HQ6LNWNU","created_at":"2026-07-05T10:17:09Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:HQ6LNWNU7RMA6FSF26HORW3GVB","target":"record","payload":{"canonical_record":{"source":{"id":"2407.04903","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-07-06T00:40:53Z","cross_cats_sorted":["cs.AI","cs.CV"],"title_canon_sha256":"8b90565966051a20ff2e12868f50b1a714d6491cd5b91cd726afb001852c8977","abstract_canon_sha256":"fd54616726ed427ea7781a7b9c4403fd62af8f85374dfa29168896a929e41153"},"schema_version":"1.0"},"canonical_sha256":"3c3cb6d9b4fc580f1645d78ee8db66a8475ef66fd893c3e3a2636f5adba76a27","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:17:09.593561Z","signature_b64":"xlUSKld/yypozrlYO3FUv6XHMkTUF1CDAoyxUwq84H+RXuBbcXRY0U1QJCcas0a+97LccxX0JNVLhPZ7hA95Cg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3c3cb6d9b4fc580f1645d78ee8db66a8475ef66fd893c3e3a2636f5adba76a27","last_reissued_at":"2026-07-05T10:17:09.593020Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:17:09.593020Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2407.04903","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:17:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/yqCZKW75lpyi7gXEzTEx6CazMV8vc2GIOOM16TB2SlXNgSBNKnr+9Zxu12LULzrcacDbpP9VH57fHgktasZCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-02T17:45:03.542736Z"},"content_sha256":"c28f3dcf11a35e0f1e901fa99fde76d5602532e04b88a38e86d4bf61b3db5dfa","schema_version":"1.0","event_id":"sha256:c28f3dcf11a35e0f1e901fa99fde76d5602532e04b88a38e86d4bf61b3db5dfa"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:HQ6LNWNU7RMA6FSF26HORW3GVB","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"MMSci: A Dataset for Graduate-Level Multi-Discipline Multimodal Scientific Understanding","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CV"],"primary_cat":"cs.CL","authors_text":"Byungju Lee, Hyeonjung Kim, Jin Hyuk Lim, Kyuri Choi, Linda Ruth Petzold, Ryan Hsieh, Stephen D. Wilson, Sungyoung Ji, Wanrong Zhu, William Yang Wang, Woosang Lim, Xianjun Yang, Xifeng Yan, Zekun Li","submitted_at":"2024-07-06T00:40:53Z","abstract_excerpt":"Scientific figure interpretation is a crucial capability for AI-driven scientific assistants built on advanced Large Vision Language Models. However, current datasets and benchmarks primarily focus on simple charts or other relatively straightforward figures from limited science domains. To address this gap, we present a comprehensive dataset compiled from peer-reviewed Nature Communications articles covering 72 scientific fields, encompassing complex visualizations such as schematic diagrams, microscopic images, and experimental data which require graduate-level expertise to interpret. We eva"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.04903","kind":"arxiv","version":3},"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/2407.04903/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":"2026-07-05T10:17:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wV/8OhhhYMLOjEkSrbtGKl5olIPEW+s6x9PLUMXqZhHJHoUCeF+vkkwtpURZ2gl0Zz66fH5Bmy42SLsU67SZAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-02T17:45:03.543272Z"},"content_sha256":"1e73d43ed03679a9c5897eb574cf877060d84bf1569402116fd19d8cf00b2fbe","schema_version":"1.0","event_id":"sha256:1e73d43ed03679a9c5897eb574cf877060d84bf1569402116fd19d8cf00b2fbe"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HQ6LNWNU7RMA6FSF26HORW3GVB/bundle.json","state_url":"https://pith.science/pith/HQ6LNWNU7RMA6FSF26HORW3GVB/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HQ6LNWNU7RMA6FSF26HORW3GVB/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":"2026-08-02T17:45:03Z","links":{"resolver":"https://pith.science/pith/HQ6LNWNU7RMA6FSF26HORW3GVB","bundle":"https://pith.science/pith/HQ6LNWNU7RMA6FSF26HORW3GVB/bundle.json","state":"https://pith.science/pith/HQ6LNWNU7RMA6FSF26HORW3GVB/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HQ6LNWNU7RMA6FSF26HORW3GVB/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:HQ6LNWNU7RMA6FSF26HORW3GVB","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":"fd54616726ed427ea7781a7b9c4403fd62af8f85374dfa29168896a929e41153","cross_cats_sorted":["cs.AI","cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-07-06T00:40:53Z","title_canon_sha256":"8b90565966051a20ff2e12868f50b1a714d6491cd5b91cd726afb001852c8977"},"schema_version":"1.0","source":{"id":"2407.04903","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.04903","created_at":"2026-07-05T10:17:09Z"},{"alias_kind":"arxiv_version","alias_value":"2407.04903v3","created_at":"2026-07-05T10:17:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.04903","created_at":"2026-07-05T10:17:09Z"},{"alias_kind":"pith_short_12","alias_value":"HQ6LNWNU7RMA","created_at":"2026-07-05T10:17:09Z"},{"alias_kind":"pith_short_16","alias_value":"HQ6LNWNU7RMA6FSF","created_at":"2026-07-05T10:17:09Z"},{"alias_kind":"pith_short_8","alias_value":"HQ6LNWNU","created_at":"2026-07-05T10:17:09Z"}],"graph_snapshots":[{"event_id":"sha256:1e73d43ed03679a9c5897eb574cf877060d84bf1569402116fd19d8cf00b2fbe","target":"graph","created_at":"2026-07-05T10:17:09Z","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/2407.04903/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Scientific figure interpretation is a crucial capability for AI-driven scientific assistants built on advanced Large Vision Language Models. However, current datasets and benchmarks primarily focus on simple charts or other relatively straightforward figures from limited science domains. To address this gap, we present a comprehensive dataset compiled from peer-reviewed Nature Communications articles covering 72 scientific fields, encompassing complex visualizations such as schematic diagrams, microscopic images, and experimental data which require graduate-level expertise to interpret. We eva","authors_text":"Byungju Lee, Hyeonjung Kim, Jin Hyuk Lim, Kyuri Choi, Linda Ruth Petzold, Ryan Hsieh, Stephen D. Wilson, Sungyoung Ji, Wanrong Zhu, William Yang Wang, Woosang Lim, Xianjun Yang, Xifeng Yan, Zekun Li","cross_cats":["cs.AI","cs.CV"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-07-06T00:40:53Z","title":"MMSci: A Dataset for Graduate-Level Multi-Discipline Multimodal Scientific Understanding"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.04903","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:c28f3dcf11a35e0f1e901fa99fde76d5602532e04b88a38e86d4bf61b3db5dfa","target":"record","created_at":"2026-07-05T10:17:09Z","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":"fd54616726ed427ea7781a7b9c4403fd62af8f85374dfa29168896a929e41153","cross_cats_sorted":["cs.AI","cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-07-06T00:40:53Z","title_canon_sha256":"8b90565966051a20ff2e12868f50b1a714d6491cd5b91cd726afb001852c8977"},"schema_version":"1.0","source":{"id":"2407.04903","kind":"arxiv","version":3}},"canonical_sha256":"3c3cb6d9b4fc580f1645d78ee8db66a8475ef66fd893c3e3a2636f5adba76a27","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3c3cb6d9b4fc580f1645d78ee8db66a8475ef66fd893c3e3a2636f5adba76a27","first_computed_at":"2026-07-05T10:17:09.593020Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:17:09.593020Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"xlUSKld/yypozrlYO3FUv6XHMkTUF1CDAoyxUwq84H+RXuBbcXRY0U1QJCcas0a+97LccxX0JNVLhPZ7hA95Cg==","signature_status":"signed_v1","signed_at":"2026-07-05T10:17:09.593561Z","signed_message":"canonical_sha256_bytes"},"source_id":"2407.04903","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c28f3dcf11a35e0f1e901fa99fde76d5602532e04b88a38e86d4bf61b3db5dfa","sha256:1e73d43ed03679a9c5897eb574cf877060d84bf1569402116fd19d8cf00b2fbe"],"state_sha256":"e69b1a249b43d22ce5db2b17380c1bb7efdb3de6096355d301cb9722c761d21a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LXWo2hi8xZ/7wi56bQ9nOWTMFyPx0UaqrGynD6xdh/uVRreW7dng4bk53RceQph7tIebsIaLbg+VdC60beozAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-02T17:45:03.548666Z","bundle_sha256":"aaff0baa388ad5b6d010d3c2f0757f7a307a7cd54e5ffdee9c96afeecf04dd5d"}}