{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:JGK7I3YMDCHLRUBVYFAISMU2YW","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":"602d87d438de43eda349c54f1705d06159eb027c2a70636473b703aca1fdecb8","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-01-01T15:26:23Z","title_canon_sha256":"d5778339f7e95052903c714e53f1e22e65ba1c2956d665c965f103d3a53843ff"},"schema_version":"1.0","source":{"id":"2401.02982","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2401.02982","created_at":"2026-07-05T08:31:46Z"},{"alias_kind":"arxiv_version","alias_value":"2401.02982v4","created_at":"2026-07-05T08:31:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2401.02982","created_at":"2026-07-05T08:31:46Z"},{"alias_kind":"pith_short_12","alias_value":"JGK7I3YMDCHL","created_at":"2026-07-05T08:31:46Z"},{"alias_kind":"pith_short_16","alias_value":"JGK7I3YMDCHLRUBV","created_at":"2026-07-05T08:31:46Z"},{"alias_kind":"pith_short_8","alias_value":"JGK7I3YM","created_at":"2026-07-05T08:31:46Z"}],"graph_snapshots":[{"event_id":"sha256:88d0c7a16f10b589f3bf9f63aa37f2959ca13b91697c75346c58de612a6916a0","target":"graph","created_at":"2026-07-05T08:31:46Z","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/2401.02982/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large Language Models (LLMs) have demonstrated impressive capabilities across a wide range of tasks. However, their proficiency and reliability in the specialized domain of financial data analysis, particularly focusing on data-driven thinking, remain uncertain. To bridge this gap, we introduce \\texttt{FinDABench}, a comprehensive benchmark designed to evaluate the financial data analysis capabilities of LLMs within this context. \\texttt{FinDABench} assesses LLMs across three dimensions: 1) \\textbf{Foundational Ability}, evaluating the models' ability to perform financial numerical calculation","authors_text":"Aimin Zhou, Chenghao Jia, Chong Yang, Jie Zhou, Man Lan, Qingquan Wu, Shangqing Zhao, Shu Liu, Xinlin Zhuang, Zhaoguang Long","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-01-01T15:26:23Z","title":"FinDABench: Benchmarking Financial Data Analysis Ability of Large Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2401.02982","kind":"arxiv","version":4},"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":"sha256:4349a42d08de476d5244f6bf4db064551059bf1b4ab2dade9ead13432a606b22","target":"record","created_at":"2026-07-05T08:31:46Z","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":"602d87d438de43eda349c54f1705d06159eb027c2a70636473b703aca1fdecb8","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-01-01T15:26:23Z","title_canon_sha256":"d5778339f7e95052903c714e53f1e22e65ba1c2956d665c965f103d3a53843ff"},"schema_version":"1.0","source":{"id":"2401.02982","kind":"arxiv","version":4}},"canonical_sha256":"4995f46f0c188eb8d035c14089329ac59d5ae74001ac24eb6d38d189ab7f5b59","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4995f46f0c188eb8d035c14089329ac59d5ae74001ac24eb6d38d189ab7f5b59","first_computed_at":"2026-07-05T08:31:46.283686Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:31:46.283686Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"6R/E1O1snFC9gtumHTn7oVsqT6Fw1qFEDEAXIm4MjQ3VyszWB6D+UMAhNxJDlhyw8wS2F4cobN0LE7iZ7D86BA==","signature_status":"signed_v1","signed_at":"2026-07-05T08:31:46.284180Z","signed_message":"canonical_sha256_bytes"},"source_id":"2401.02982","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4349a42d08de476d5244f6bf4db064551059bf1b4ab2dade9ead13432a606b22","sha256:88d0c7a16f10b589f3bf9f63aa37f2959ca13b91697c75346c58de612a6916a0"],"state_sha256":"6e525b02fbdd623b2cfa5dea60ea0eb5f6f53a0882ac6226cef847832d8fcaf8"}