{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:STLZZINNXLAEEXSWYQKVIKTVSU","short_pith_number":"pith:STLZZINN","schema_version":"1.0","canonical_sha256":"94d79ca1adbac0425e56c415542a75953b243205838cc6b57a1db486ee686b89","source":{"kind":"arxiv","id":"2305.15038","version":2},"attestation_state":"computed","paper":{"title":"Is GPT-4 a Good Data Analyst?","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Lidong Bing, Liying Cheng, Xingxuan Li","submitted_at":"2023-05-24T11:26:59Z","abstract_excerpt":"As large language models (LLMs) have demonstrated their powerful capabilities in plenty of domains and tasks, including context understanding, code generation, language generation, data storytelling, etc., many data analysts may raise concerns if their jobs will be replaced by artificial intelligence (AI). This controversial topic has drawn great attention in public. However, we are still at a stage of divergent opinions without any definitive conclusion. Motivated by this, we raise the research question of \"is GPT-4 a good data analyst?\" in this work and aim to answer it by conducting head-to"},"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":"2305.15038","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-05-24T11:26:59Z","cross_cats_sorted":[],"title_canon_sha256":"bd0f4a028f8a5fcf1850dcbe3fd1ac317022bce875eadab04cc976045dff5bbe","abstract_canon_sha256":"eeb9ec9042789c00889d262c886354030be6aa48de680c91a5aa78ffd044dc9e"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:03:25.988819Z","signature_b64":"TjFLbDUaeu1l+ih+n+EmobyWwPZHmmUNjvLKThg6Qm/2ez4exZ/D0JctCQb4crjUHH2Rm1lZ/n4G+axlD/DmAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"94d79ca1adbac0425e56c415542a75953b243205838cc6b57a1db486ee686b89","last_reissued_at":"2026-07-05T07:03:25.988351Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:03:25.988351Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Is GPT-4 a Good Data Analyst?","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Lidong Bing, Liying Cheng, Xingxuan Li","submitted_at":"2023-05-24T11:26:59Z","abstract_excerpt":"As large language models (LLMs) have demonstrated their powerful capabilities in plenty of domains and tasks, including context understanding, code generation, language generation, data storytelling, etc., many data analysts may raise concerns if their jobs will be replaced by artificial intelligence (AI). This controversial topic has drawn great attention in public. However, we are still at a stage of divergent opinions without any definitive conclusion. Motivated by this, we raise the research question of \"is GPT-4 a good data analyst?\" in this work and aim to answer it by conducting head-to"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.15038","kind":"arxiv","version":2},"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/2305.15038/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":"2305.15038","created_at":"2026-07-05T07:03:25.988406+00:00"},{"alias_kind":"arxiv_version","alias_value":"2305.15038v2","created_at":"2026-07-05T07:03:25.988406+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.15038","created_at":"2026-07-05T07:03:25.988406+00:00"},{"alias_kind":"pith_short_12","alias_value":"STLZZINNXLAE","created_at":"2026-07-05T07:03:25.988406+00:00"},{"alias_kind":"pith_short_16","alias_value":"STLZZINNXLAEEXSW","created_at":"2026-07-05T07:03:25.988406+00:00"},{"alias_kind":"pith_short_8","alias_value":"STLZZINN","created_at":"2026-07-05T07:03:25.988406+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":2,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2606.10692","citing_title":"Do LLMsMakeNeural Distinguishers Wise?","ref_index":15,"is_internal_anchor":false},{"citing_arxiv_id":"2605.30042","citing_title":"Learning to Choose: An Empowerment-Guided Multi-Agent System with semantic communication for Adaptive Method Selection","ref_index":5,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/STLZZINNXLAEEXSWYQKVIKTVSU","json":"https://pith.science/pith/STLZZINNXLAEEXSWYQKVIKTVSU.json","graph_json":"https://pith.science/api/pith-number/STLZZINNXLAEEXSWYQKVIKTVSU/graph.json","events_json":"https://pith.science/api/pith-number/STLZZINNXLAEEXSWYQKVIKTVSU/events.json","paper":"https://pith.science/paper/STLZZINN"},"agent_actions":{"view_html":"https://pith.science/pith/STLZZINNXLAEEXSWYQKVIKTVSU","download_json":"https://pith.science/pith/STLZZINNXLAEEXSWYQKVIKTVSU.json","view_paper":"https://pith.science/paper/STLZZINN","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2305.15038&json=true","fetch_graph":"https://pith.science/api/pith-number/STLZZINNXLAEEXSWYQKVIKTVSU/graph.json","fetch_events":"https://pith.science/api/pith-number/STLZZINNXLAEEXSWYQKVIKTVSU/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/STLZZINNXLAEEXSWYQKVIKTVSU/action/timestamp_anchor","attest_storage":"https://pith.science/pith/STLZZINNXLAEEXSWYQKVIKTVSU/action/storage_attestation","attest_author":"https://pith.science/pith/STLZZINNXLAEEXSWYQKVIKTVSU/action/author_attestation","sign_citation":"https://pith.science/pith/STLZZINNXLAEEXSWYQKVIKTVSU/action/citation_signature","submit_replication":"https://pith.science/pith/STLZZINNXLAEEXSWYQKVIKTVSU/action/replication_record"}},"created_at":"2026-07-05T07:03:25.988406+00:00","updated_at":"2026-07-05T07:03:25.988406+00:00"}