{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:IJTE2XNKW732JCBW4PQBOYBGDD","short_pith_number":"pith:IJTE2XNK","schema_version":"1.0","canonical_sha256":"42664d5daab7f7a48836e3e017602618f0eb69b13bba4f68872987cbe382d3c6","source":{"kind":"arxiv","id":"2406.10057","version":3},"attestation_state":"computed","paper":{"title":"First Multi-Dimensional Evaluation of Flowchart Comprehension for Multimodal Large Language Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Enming Zhang, Huanyong Liu, Jiale Wang, Junhui Yu, Ruobing Yao","submitted_at":"2024-06-14T14:15:35Z","abstract_excerpt":"With the development of Multimodal Large Language Models (MLLMs) technology, its general capabilities are increasingly powerful. To evaluate the various abilities of MLLMs, numerous evaluation systems have emerged. But now there is still a lack of a comprehensive method to evaluate MLLMs in the tasks related to flowcharts, which are very important in daily life and work. We propose the first comprehensive method, FlowCE, to assess MLLMs across various dimensions for tasks related to flowcharts. It encompasses evaluating MLLMs' abilities in Reasoning, Localization Recognition, Information Extra"},"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":"2406.10057","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-06-14T14:15:35Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"b0515a1820c8f37d1ce3001bb3d6e0f4eb4cbbef8f9b1fbfe7ccf852b4366d46","abstract_canon_sha256":"9d948fd977c32fee7090820a20fcf5b253a53aa63a98cc42a1d7e597becf9725"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:31:30.190988Z","signature_b64":"hM9p2I3HtoywQ2KhyDs6dJvT2G0D7yfRRJ+mU7youGr6EDaRFFulAKVaiDC5Ydsm9CMCh+nefwwuno5VrPumDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"42664d5daab7f7a48836e3e017602618f0eb69b13bba4f68872987cbe382d3c6","last_reissued_at":"2026-07-05T09:31:30.190506Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:31:30.190506Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"First Multi-Dimensional Evaluation of Flowchart Comprehension for Multimodal Large Language Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Enming Zhang, Huanyong Liu, Jiale Wang, Junhui Yu, Ruobing Yao","submitted_at":"2024-06-14T14:15:35Z","abstract_excerpt":"With the development of Multimodal Large Language Models (MLLMs) technology, its general capabilities are increasingly powerful. To evaluate the various abilities of MLLMs, numerous evaluation systems have emerged. But now there is still a lack of a comprehensive method to evaluate MLLMs in the tasks related to flowcharts, which are very important in daily life and work. We propose the first comprehensive method, FlowCE, to assess MLLMs across various dimensions for tasks related to flowcharts. It encompasses evaluating MLLMs' abilities in Reasoning, Localization Recognition, Information Extra"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.10057","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/2406.10057/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":"2406.10057","created_at":"2026-07-05T09:31:30.190566+00:00"},{"alias_kind":"arxiv_version","alias_value":"2406.10057v3","created_at":"2026-07-05T09:31:30.190566+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.10057","created_at":"2026-07-05T09:31:30.190566+00:00"},{"alias_kind":"pith_short_12","alias_value":"IJTE2XNKW732","created_at":"2026-07-05T09:31:30.190566+00:00"},{"alias_kind":"pith_short_16","alias_value":"IJTE2XNKW732JCBW","created_at":"2026-07-05T09:31:30.190566+00:00"},{"alias_kind":"pith_short_8","alias_value":"IJTE2XNK","created_at":"2026-07-05T09:31:30.190566+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/IJTE2XNKW732JCBW4PQBOYBGDD","json":"https://pith.science/pith/IJTE2XNKW732JCBW4PQBOYBGDD.json","graph_json":"https://pith.science/api/pith-number/IJTE2XNKW732JCBW4PQBOYBGDD/graph.json","events_json":"https://pith.science/api/pith-number/IJTE2XNKW732JCBW4PQBOYBGDD/events.json","paper":"https://pith.science/paper/IJTE2XNK"},"agent_actions":{"view_html":"https://pith.science/pith/IJTE2XNKW732JCBW4PQBOYBGDD","download_json":"https://pith.science/pith/IJTE2XNKW732JCBW4PQBOYBGDD.json","view_paper":"https://pith.science/paper/IJTE2XNK","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2406.10057&json=true","fetch_graph":"https://pith.science/api/pith-number/IJTE2XNKW732JCBW4PQBOYBGDD/graph.json","fetch_events":"https://pith.science/api/pith-number/IJTE2XNKW732JCBW4PQBOYBGDD/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/IJTE2XNKW732JCBW4PQBOYBGDD/action/timestamp_anchor","attest_storage":"https://pith.science/pith/IJTE2XNKW732JCBW4PQBOYBGDD/action/storage_attestation","attest_author":"https://pith.science/pith/IJTE2XNKW732JCBW4PQBOYBGDD/action/author_attestation","sign_citation":"https://pith.science/pith/IJTE2XNKW732JCBW4PQBOYBGDD/action/citation_signature","submit_replication":"https://pith.science/pith/IJTE2XNKW732JCBW4PQBOYBGDD/action/replication_record"}},"created_at":"2026-07-05T09:31:30.190566+00:00","updated_at":"2026-07-05T09:31:30.190566+00:00"}