{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:URDMQ2CUGGA32GWNROVMLJCAPJ","short_pith_number":"pith:URDMQ2CU","schema_version":"1.0","canonical_sha256":"a446c868543181bd1acd8baac5a4407a67e7f570bb2e91625b766e17ab3205a1","source":{"kind":"arxiv","id":"2509.09286","version":1},"attestation_state":"computed","paper":{"title":"Visual Programmability: A Guide for Code-as-Thought in Chart Understanding","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Bohao Tang, Ethan Chern, Fei Zhang, Jiadi Su, Pengfei Liu, Yan Ma, Ya Zhang, Zhixin Wang, Zhulin Hu","submitted_at":"2025-09-11T09:22:16Z","abstract_excerpt":"Chart understanding presents a critical test to the reasoning capabilities of Vision-Language Models (VLMs). Prior approaches face critical limitations: some rely on external tools, making them brittle and constrained by a predefined toolkit, while others fine-tune specialist models that often adopt a single reasoning strategy, such as text-based chain-of-thought (CoT). The intermediate steps of text-based reasoning are difficult to verify, which complicates the use of reinforcement-learning signals that reward factual accuracy. To address this, we propose a Code-as-Thought (CaT) approach to r"},"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":"2509.09286","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-09-11T09:22:16Z","cross_cats_sorted":[],"title_canon_sha256":"7f2bbe7f814726a0545f73cfd973931a36be6e3fbf2151c320f10fd7a101eea3","abstract_canon_sha256":"521dd3c71b3ae506ff32a279639d00571a2ed6c58f7b6b1a8d563efc88e1005a"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T12:09:33.135700Z","signature_b64":"d14yH9Ldt3LY/MraDQraRJqJ6SK/ZQZNRlwhEbLRE7OiQudiDN8QAVtzcEt6aqGtidiAiIZxUAS2cwftOlIJCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a446c868543181bd1acd8baac5a4407a67e7f570bb2e91625b766e17ab3205a1","last_reissued_at":"2026-07-05T12:09:33.135169Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T12:09:33.135169Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Visual Programmability: A Guide for Code-as-Thought in Chart Understanding","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Bohao Tang, Ethan Chern, Fei Zhang, Jiadi Su, Pengfei Liu, Yan Ma, Ya Zhang, Zhixin Wang, Zhulin Hu","submitted_at":"2025-09-11T09:22:16Z","abstract_excerpt":"Chart understanding presents a critical test to the reasoning capabilities of Vision-Language Models (VLMs). Prior approaches face critical limitations: some rely on external tools, making them brittle and constrained by a predefined toolkit, while others fine-tune specialist models that often adopt a single reasoning strategy, such as text-based chain-of-thought (CoT). The intermediate steps of text-based reasoning are difficult to verify, which complicates the use of reinforcement-learning signals that reward factual accuracy. To address this, we propose a Code-as-Thought (CaT) approach to r"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2509.09286","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/2509.09286/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":"2509.09286","created_at":"2026-07-05T12:09:33.135238+00:00"},{"alias_kind":"arxiv_version","alias_value":"2509.09286v1","created_at":"2026-07-05T12:09:33.135238+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2509.09286","created_at":"2026-07-05T12:09:33.135238+00:00"},{"alias_kind":"pith_short_12","alias_value":"URDMQ2CUGGA3","created_at":"2026-07-05T12:09:33.135238+00:00"},{"alias_kind":"pith_short_16","alias_value":"URDMQ2CUGGA32GWN","created_at":"2026-07-05T12:09:33.135238+00:00"},{"alias_kind":"pith_short_8","alias_value":"URDMQ2CU","created_at":"2026-07-05T12:09:33.135238+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/URDMQ2CUGGA32GWNROVMLJCAPJ","json":"https://pith.science/pith/URDMQ2CUGGA32GWNROVMLJCAPJ.json","graph_json":"https://pith.science/api/pith-number/URDMQ2CUGGA32GWNROVMLJCAPJ/graph.json","events_json":"https://pith.science/api/pith-number/URDMQ2CUGGA32GWNROVMLJCAPJ/events.json","paper":"https://pith.science/paper/URDMQ2CU"},"agent_actions":{"view_html":"https://pith.science/pith/URDMQ2CUGGA32GWNROVMLJCAPJ","download_json":"https://pith.science/pith/URDMQ2CUGGA32GWNROVMLJCAPJ.json","view_paper":"https://pith.science/paper/URDMQ2CU","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2509.09286&json=true","fetch_graph":"https://pith.science/api/pith-number/URDMQ2CUGGA32GWNROVMLJCAPJ/graph.json","fetch_events":"https://pith.science/api/pith-number/URDMQ2CUGGA32GWNROVMLJCAPJ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/URDMQ2CUGGA32GWNROVMLJCAPJ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/URDMQ2CUGGA32GWNROVMLJCAPJ/action/storage_attestation","attest_author":"https://pith.science/pith/URDMQ2CUGGA32GWNROVMLJCAPJ/action/author_attestation","sign_citation":"https://pith.science/pith/URDMQ2CUGGA32GWNROVMLJCAPJ/action/citation_signature","submit_replication":"https://pith.science/pith/URDMQ2CUGGA32GWNROVMLJCAPJ/action/replication_record"}},"created_at":"2026-07-05T12:09:33.135238+00:00","updated_at":"2026-07-05T12:09:33.135238+00:00"}