{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:3USDT2GDGM42GG65J5F5RTPGFC","short_pith_number":"pith:3USDT2GD","canonical_record":{"source":{"id":"2501.02552","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-01-05T14:09:12Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"88fd90423e430088e38e5969b9bedc9ac634619302506b78745254059597f7a0","abstract_canon_sha256":"b17c07f598da30f88856abdcaad768d22358b46a1c4f9382fde57875e7377419"},"schema_version":"1.0"},"canonical_sha256":"dd2439e8c33339a31bdd4f4bd8cde6288de2dc4af43b26fa167681df96c610ff","source":{"kind":"arxiv","id":"2501.02552","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.02552","created_at":"2026-07-05T09:57:08Z"},{"alias_kind":"arxiv_version","alias_value":"2501.02552v1","created_at":"2026-07-05T09:57:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.02552","created_at":"2026-07-05T09:57:08Z"},{"alias_kind":"pith_short_12","alias_value":"3USDT2GDGM42","created_at":"2026-07-05T09:57:08Z"},{"alias_kind":"pith_short_16","alias_value":"3USDT2GDGM42GG65","created_at":"2026-07-05T09:57:08Z"},{"alias_kind":"pith_short_8","alias_value":"3USDT2GD","created_at":"2026-07-05T09:57:08Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:3USDT2GDGM42GG65J5F5RTPGFC","target":"record","payload":{"canonical_record":{"source":{"id":"2501.02552","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-01-05T14:09:12Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"88fd90423e430088e38e5969b9bedc9ac634619302506b78745254059597f7a0","abstract_canon_sha256":"b17c07f598da30f88856abdcaad768d22358b46a1c4f9382fde57875e7377419"},"schema_version":"1.0"},"canonical_sha256":"dd2439e8c33339a31bdd4f4bd8cde6288de2dc4af43b26fa167681df96c610ff","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:57:08.993991Z","signature_b64":"6rTjE7dEfKJRNUPbJgijaHe/VvNoVDJKBa5iWUNY7HYX7QllnINEwwdK2T/Eia9LDE8ewpj5a5RnvbbZVyFeCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"dd2439e8c33339a31bdd4f4bd8cde6288de2dc4af43b26fa167681df96c610ff","last_reissued_at":"2026-07-05T09:57:08.993581Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:57:08.993581Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2501.02552","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":"2026-07-05T09:57:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gmDhU9MgK5NTFwLjHIGs5KfZ+pdnsSTQtALpzrQSbRRZ5+jTwM7sgynzqLMDLBWzX8arAS+fS0SLuYrAd7xmCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T02:31:49.397831Z"},"content_sha256":"6006d1bb6d7ee5794d141e487ff0e04adf0ad60e0ba629dcba23aa0dd94838ba","schema_version":"1.0","event_id":"sha256:6006d1bb6d7ee5794d141e487ff0e04adf0ad60e0ba629dcba23aa0dd94838ba"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:3USDT2GDGM42GG65J5F5RTPGFC","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Multi-LLM Collaborative Caption Generation in Scientific Documents","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.CL","authors_text":"Chieh-Yang Huang, Clyde Lee Giles, Hong-Jun Choi, Jaeyoung Kim, Jongho Lee, Ryan Rossi, Sungchul Choi, Sungchul Kim, Ting-Hao 'Kenneth' Huang, Ting-Yao Hsu, Tong Yu","submitted_at":"2025-01-05T14:09:12Z","abstract_excerpt":"Scientific figure captioning is a complex task that requires generating contextually appropriate descriptions of visual content. However, existing methods often fall short by utilizing incomplete information, treating the task solely as either an image-to-text or text summarization problem. This limitation hinders the generation of high-quality captions that fully capture the necessary details. Moreover, existing data sourced from arXiv papers contain low-quality captions, posing significant challenges for training large language models (LLMs). In this paper, we introduce a framework called Mu"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.02552","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/2501.02552/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":"2026-07-05T09:57:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"P4YTZwEd0pDJhB0puNDOg27eLfOD9PSGNT8tK859e7naaepbHfzScBEU32DwH+pXdoAoeOYp2P5QmgWM5YDGDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T02:31:49.398309Z"},"content_sha256":"5e226f1d26cda1ee9ed458a5136ab1c8f19dc400d2271df444153b346933e283","schema_version":"1.0","event_id":"sha256:5e226f1d26cda1ee9ed458a5136ab1c8f19dc400d2271df444153b346933e283"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/3USDT2GDGM42GG65J5F5RTPGFC/bundle.json","state_url":"https://pith.science/pith/3USDT2GDGM42GG65J5F5RTPGFC/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/3USDT2GDGM42GG65J5F5RTPGFC/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":"2026-08-05T02:31:49Z","links":{"resolver":"https://pith.science/pith/3USDT2GDGM42GG65J5F5RTPGFC","bundle":"https://pith.science/pith/3USDT2GDGM42GG65J5F5RTPGFC/bundle.json","state":"https://pith.science/pith/3USDT2GDGM42GG65J5F5RTPGFC/state.json","well_known_bundle":"https://pith.science/.well-known/pith/3USDT2GDGM42GG65J5F5RTPGFC/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:3USDT2GDGM42GG65J5F5RTPGFC","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":"b17c07f598da30f88856abdcaad768d22358b46a1c4f9382fde57875e7377419","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-01-05T14:09:12Z","title_canon_sha256":"88fd90423e430088e38e5969b9bedc9ac634619302506b78745254059597f7a0"},"schema_version":"1.0","source":{"id":"2501.02552","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.02552","created_at":"2026-07-05T09:57:08Z"},{"alias_kind":"arxiv_version","alias_value":"2501.02552v1","created_at":"2026-07-05T09:57:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.02552","created_at":"2026-07-05T09:57:08Z"},{"alias_kind":"pith_short_12","alias_value":"3USDT2GDGM42","created_at":"2026-07-05T09:57:08Z"},{"alias_kind":"pith_short_16","alias_value":"3USDT2GDGM42GG65","created_at":"2026-07-05T09:57:08Z"},{"alias_kind":"pith_short_8","alias_value":"3USDT2GD","created_at":"2026-07-05T09:57:08Z"}],"graph_snapshots":[{"event_id":"sha256:5e226f1d26cda1ee9ed458a5136ab1c8f19dc400d2271df444153b346933e283","target":"graph","created_at":"2026-07-05T09:57:08Z","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/2501.02552/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Scientific figure captioning is a complex task that requires generating contextually appropriate descriptions of visual content. However, existing methods often fall short by utilizing incomplete information, treating the task solely as either an image-to-text or text summarization problem. This limitation hinders the generation of high-quality captions that fully capture the necessary details. Moreover, existing data sourced from arXiv papers contain low-quality captions, posing significant challenges for training large language models (LLMs). In this paper, we introduce a framework called Mu","authors_text":"Chieh-Yang Huang, Clyde Lee Giles, Hong-Jun Choi, Jaeyoung Kim, Jongho Lee, Ryan Rossi, Sungchul Choi, Sungchul Kim, Ting-Hao 'Kenneth' Huang, Ting-Yao Hsu, Tong Yu","cross_cats":["cs.CV"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-01-05T14:09:12Z","title":"Multi-LLM Collaborative Caption Generation in Scientific Documents"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.02552","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":"sha256:6006d1bb6d7ee5794d141e487ff0e04adf0ad60e0ba629dcba23aa0dd94838ba","target":"record","created_at":"2026-07-05T09:57:08Z","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":"b17c07f598da30f88856abdcaad768d22358b46a1c4f9382fde57875e7377419","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-01-05T14:09:12Z","title_canon_sha256":"88fd90423e430088e38e5969b9bedc9ac634619302506b78745254059597f7a0"},"schema_version":"1.0","source":{"id":"2501.02552","kind":"arxiv","version":1}},"canonical_sha256":"dd2439e8c33339a31bdd4f4bd8cde6288de2dc4af43b26fa167681df96c610ff","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"dd2439e8c33339a31bdd4f4bd8cde6288de2dc4af43b26fa167681df96c610ff","first_computed_at":"2026-07-05T09:57:08.993581Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:57:08.993581Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"6rTjE7dEfKJRNUPbJgijaHe/VvNoVDJKBa5iWUNY7HYX7QllnINEwwdK2T/Eia9LDE8ewpj5a5RnvbbZVyFeCw==","signature_status":"signed_v1","signed_at":"2026-07-05T09:57:08.993991Z","signed_message":"canonical_sha256_bytes"},"source_id":"2501.02552","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6006d1bb6d7ee5794d141e487ff0e04adf0ad60e0ba629dcba23aa0dd94838ba","sha256:5e226f1d26cda1ee9ed458a5136ab1c8f19dc400d2271df444153b346933e283"],"state_sha256":"61d1960f5aa786ec3e357c7e924be81a48a8035f0b7509d628a9e240de556b77"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tRCotHvVsxokF6b9btMmuPocSv94i8ksbJXRtg5TPZq2bRqTrbmE5nc+k/BWR7ziIIGGheoRlhX3NP0tWQvGDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T02:31:49.402599Z","bundle_sha256":"415e9ce9caec38205586876e5d38b21c3e8980404c97953d61c0db6539b30e38"}}