{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:SMXYYZ5SZBZ65HZLJX6KFUBPFU","short_pith_number":"pith:SMXYYZ5S","canonical_record":{"source":{"id":"2505.23242","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-05-29T08:46:03Z","cross_cats_sorted":[],"title_canon_sha256":"6b54d3ddf685c410788ec83ff782e43093e2208e5c2a31c99319dc322fe276b2","abstract_canon_sha256":"06cc3486d0a194d34b046f346b8a431a3ae917306f6ae1d1806d3119f36c070d"},"schema_version":"1.0"},"canonical_sha256":"932f8c67b2c873ee9f2b4dfca2d02f2d194dd2eb02e8514afd783ba1f1e70879","source":{"kind":"arxiv","id":"2505.23242","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.23242","created_at":"2026-07-05T11:11:58Z"},{"alias_kind":"arxiv_version","alias_value":"2505.23242v1","created_at":"2026-07-05T11:11:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.23242","created_at":"2026-07-05T11:11:58Z"},{"alias_kind":"pith_short_12","alias_value":"SMXYYZ5SZBZ6","created_at":"2026-07-05T11:11:58Z"},{"alias_kind":"pith_short_16","alias_value":"SMXYYZ5SZBZ65HZL","created_at":"2026-07-05T11:11:58Z"},{"alias_kind":"pith_short_8","alias_value":"SMXYYZ5S","created_at":"2026-07-05T11:11:58Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:SMXYYZ5SZBZ65HZLJX6KFUBPFU","target":"record","payload":{"canonical_record":{"source":{"id":"2505.23242","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-05-29T08:46:03Z","cross_cats_sorted":[],"title_canon_sha256":"6b54d3ddf685c410788ec83ff782e43093e2208e5c2a31c99319dc322fe276b2","abstract_canon_sha256":"06cc3486d0a194d34b046f346b8a431a3ae917306f6ae1d1806d3119f36c070d"},"schema_version":"1.0"},"canonical_sha256":"932f8c67b2c873ee9f2b4dfca2d02f2d194dd2eb02e8514afd783ba1f1e70879","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:11:58.240295Z","signature_b64":"Tqio/hIgPzt1SyqL+m80uszJVw2/YBB16lEwLN3+JvbtB7PECC5vSGDnTy1uVtFFdnChFmZ0x35Zc3G+9KrJDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"932f8c67b2c873ee9f2b4dfca2d02f2d194dd2eb02e8514afd783ba1f1e70879","last_reissued_at":"2026-07-05T11:11:58.239710Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:11:58.239710Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2505.23242","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":"2026-07-05T11:11:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qv5tYHd+Wc7dK5iyeV/VA/SPw1QcRBignhvOW9iQas5whyHnuEwIigvCV+6WXIF04+1hhQWsF3UNJlBlqi3mBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T17:03:46.307117Z"},"content_sha256":"c719699069209dc3edf84a53274e501a87e6865923657f298ca941544dc5793b","schema_version":"1.0","event_id":"sha256:c719699069209dc3edf84a53274e501a87e6865923657f298ca941544dc5793b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:SMXYYZ5SZBZ65HZLJX6KFUBPFU","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"ChartMind: A Comprehensive Benchmark for Complex Real-world Multimodal Chart Question Answering","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Bihui Yu, Gaowei Wu, Jingxuan Wei, Junnan Zhu, Lei Wang, Nan Xu, Yanni Hao","submitted_at":"2025-05-29T08:46:03Z","abstract_excerpt":"Chart question answering (CQA) has become a critical multimodal task for evaluating the reasoning capabilities of vision-language models. While early approaches have shown promising performance by focusing on visual features or leveraging large-scale pre-training, most existing evaluations rely on rigid output formats and objective metrics, thus ignoring the complex, real-world demands of practical chart analysis. In this paper, we introduce ChartMind, a new benchmark designed for complex CQA tasks in real-world settings. ChartMind covers seven task categories, incorporates multilingual contex"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.23242","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/2505.23242/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":"2026-07-05T11:11:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"uCS9UU6VEHVNzwm5EsSn4lKOUFH9hcdBHEXaysCaTbtMOcGAZZ3ly1iG24fQ/1QuBdURNo1Aeea/djMILQsOAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T17:03:46.308037Z"},"content_sha256":"1ad32f0c98f5960fc561c7a171ef83e84c3466b133310e53e1bc9b3808c9cb86","schema_version":"1.0","event_id":"sha256:1ad32f0c98f5960fc561c7a171ef83e84c3466b133310e53e1bc9b3808c9cb86"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SMXYYZ5SZBZ65HZLJX6KFUBPFU/bundle.json","state_url":"https://pith.science/pith/SMXYYZ5SZBZ65HZLJX6KFUBPFU/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SMXYYZ5SZBZ65HZLJX6KFUBPFU/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":"2026-08-03T17:03:46Z","links":{"resolver":"https://pith.science/pith/SMXYYZ5SZBZ65HZLJX6KFUBPFU","bundle":"https://pith.science/pith/SMXYYZ5SZBZ65HZLJX6KFUBPFU/bundle.json","state":"https://pith.science/pith/SMXYYZ5SZBZ65HZLJX6KFUBPFU/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SMXYYZ5SZBZ65HZLJX6KFUBPFU/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:SMXYYZ5SZBZ65HZLJX6KFUBPFU","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":"06cc3486d0a194d34b046f346b8a431a3ae917306f6ae1d1806d3119f36c070d","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-05-29T08:46:03Z","title_canon_sha256":"6b54d3ddf685c410788ec83ff782e43093e2208e5c2a31c99319dc322fe276b2"},"schema_version":"1.0","source":{"id":"2505.23242","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.23242","created_at":"2026-07-05T11:11:58Z"},{"alias_kind":"arxiv_version","alias_value":"2505.23242v1","created_at":"2026-07-05T11:11:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.23242","created_at":"2026-07-05T11:11:58Z"},{"alias_kind":"pith_short_12","alias_value":"SMXYYZ5SZBZ6","created_at":"2026-07-05T11:11:58Z"},{"alias_kind":"pith_short_16","alias_value":"SMXYYZ5SZBZ65HZL","created_at":"2026-07-05T11:11:58Z"},{"alias_kind":"pith_short_8","alias_value":"SMXYYZ5S","created_at":"2026-07-05T11:11:58Z"}],"graph_snapshots":[{"event_id":"sha256:1ad32f0c98f5960fc561c7a171ef83e84c3466b133310e53e1bc9b3808c9cb86","target":"graph","created_at":"2026-07-05T11:11:58Z","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/2505.23242/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Chart question answering (CQA) has become a critical multimodal task for evaluating the reasoning capabilities of vision-language models. While early approaches have shown promising performance by focusing on visual features or leveraging large-scale pre-training, most existing evaluations rely on rigid output formats and objective metrics, thus ignoring the complex, real-world demands of practical chart analysis. In this paper, we introduce ChartMind, a new benchmark designed for complex CQA tasks in real-world settings. ChartMind covers seven task categories, incorporates multilingual contex","authors_text":"Bihui Yu, Gaowei Wu, Jingxuan Wei, Junnan Zhu, Lei Wang, Nan Xu, Yanni Hao","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-05-29T08:46:03Z","title":"ChartMind: A Comprehensive Benchmark for Complex Real-world Multimodal Chart Question Answering"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.23242","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:c719699069209dc3edf84a53274e501a87e6865923657f298ca941544dc5793b","target":"record","created_at":"2026-07-05T11:11:58Z","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":"06cc3486d0a194d34b046f346b8a431a3ae917306f6ae1d1806d3119f36c070d","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-05-29T08:46:03Z","title_canon_sha256":"6b54d3ddf685c410788ec83ff782e43093e2208e5c2a31c99319dc322fe276b2"},"schema_version":"1.0","source":{"id":"2505.23242","kind":"arxiv","version":1}},"canonical_sha256":"932f8c67b2c873ee9f2b4dfca2d02f2d194dd2eb02e8514afd783ba1f1e70879","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"932f8c67b2c873ee9f2b4dfca2d02f2d194dd2eb02e8514afd783ba1f1e70879","first_computed_at":"2026-07-05T11:11:58.239710Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:11:58.239710Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Tqio/hIgPzt1SyqL+m80uszJVw2/YBB16lEwLN3+JvbtB7PECC5vSGDnTy1uVtFFdnChFmZ0x35Zc3G+9KrJDg==","signature_status":"signed_v1","signed_at":"2026-07-05T11:11:58.240295Z","signed_message":"canonical_sha256_bytes"},"source_id":"2505.23242","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c719699069209dc3edf84a53274e501a87e6865923657f298ca941544dc5793b","sha256:1ad32f0c98f5960fc561c7a171ef83e84c3466b133310e53e1bc9b3808c9cb86"],"state_sha256":"7798c069e56ba9c1b8e194c570cfd5fbf414ede531961d09bf494893599d80db"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"uLuYPp7qN5mid18Qq23hqQsCGxuaQamb1YsRRmNcKTPWBoQTES91ad7YU0b+68TpwAvsObgSdiogZtpjQzRtAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-03T17:03:46.314956Z","bundle_sha256":"7cc3113c89864407d3b6976d2b301f2d13774e9e41e395852594323a647dbcea"}}