{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:IDQGBKIHBKTVD27V3FIVAMSMBZ","short_pith_number":"pith:IDQGBKIH","schema_version":"1.0","canonical_sha256":"40e060a9070aa751ebf5d95150324c0e63b501dd2d6c69c044e686700dd8efaa","source":{"kind":"arxiv","id":"2302.03494","version":8},"attestation_state":"computed","paper":{"title":"A Categorical Archive of ChatGPT Failures","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.CL","authors_text":"Ali Borji","submitted_at":"2023-02-06T04:21:59Z","abstract_excerpt":"Large language models have been demonstrated to be valuable in different fields. ChatGPT, developed by OpenAI, has been trained using massive amounts of data and simulates human conversation by comprehending context and generating appropriate responses. It has garnered significant attention due to its ability to effectively answer a broad range of human inquiries, with fluent and comprehensive answers surpassing prior public chatbots in both security and usefulness. However, a comprehensive analysis of ChatGPT's failures is lacking, which is the focus of this study. Eleven categories of failur"},"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":"2302.03494","kind":"arxiv","version":8},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-02-06T04:21:59Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"6f78233567cb85f9a139e4a01282eeb5f63165e466e8c5f7c84b4fa8f49342ec","abstract_canon_sha256":"44dbb1154d2d01adc57a14ac57fd6a9c07674961d2b6de34d8f414667fb035b0"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:57:35.915872Z","signature_b64":"Azk1SkJ4UPY7MTTM9juElQ9d8erkuaR+RPuBE9usy2YJ+DqUXWmqAWusx1D3iUt0DpSApbi+SLTgfTo5+FJXDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"40e060a9070aa751ebf5d95150324c0e63b501dd2d6c69c044e686700dd8efaa","last_reissued_at":"2026-07-05T05:57:35.915449Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:57:35.915449Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Categorical Archive of ChatGPT Failures","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.CL","authors_text":"Ali Borji","submitted_at":"2023-02-06T04:21:59Z","abstract_excerpt":"Large language models have been demonstrated to be valuable in different fields. ChatGPT, developed by OpenAI, has been trained using massive amounts of data and simulates human conversation by comprehending context and generating appropriate responses. It has garnered significant attention due to its ability to effectively answer a broad range of human inquiries, with fluent and comprehensive answers surpassing prior public chatbots in both security and usefulness. However, a comprehensive analysis of ChatGPT's failures is lacking, which is the focus of this study. Eleven categories of failur"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2302.03494","kind":"arxiv","version":8},"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/2302.03494/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":"2302.03494","created_at":"2026-07-05T05:57:35.915507+00:00"},{"alias_kind":"arxiv_version","alias_value":"2302.03494v8","created_at":"2026-07-05T05:57:35.915507+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2302.03494","created_at":"2026-07-05T05:57:35.915507+00:00"},{"alias_kind":"pith_short_12","alias_value":"IDQGBKIHBKTV","created_at":"2026-07-05T05:57:35.915507+00:00"},{"alias_kind":"pith_short_16","alias_value":"IDQGBKIHBKTVD27V","created_at":"2026-07-05T05:57:35.915507+00:00"},{"alias_kind":"pith_short_8","alias_value":"IDQGBKIH","created_at":"2026-07-05T05:57:35.915507+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":9,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2606.12422","citing_title":"Creating and Evaluating K-12 GenAI Assessment Graders Through Context Engineering","ref_index":83,"is_internal_anchor":false},{"citing_arxiv_id":"2606.02211","citing_title":"Consistency Training while Mitigating Obfuscation via Rate Matching","ref_index":46,"is_internal_anchor":false},{"citing_arxiv_id":"2304.09655","citing_title":"How Secure is Code Generated by ChatGPT?","ref_index":21,"is_internal_anchor":false},{"citing_arxiv_id":"2403.03920","citing_title":"Enhancing Instructional Quality: Leveraging Computer-Assisted Textual Analysis to Generate In-Depth Insights from Educational Artifacts","ref_index":6,"is_internal_anchor":false},{"citing_arxiv_id":"2404.01535","citing_title":"Assessing, Exploiting, and Mitigating Syntactic Robustness Failures in LLM-Based Code Generation","ref_index":30,"is_internal_anchor":false},{"citing_arxiv_id":"2401.05561","citing_title":"TrustLLM: Trustworthiness in Large Language Models","ref_index":214,"is_internal_anchor":false},{"citing_arxiv_id":"2308.05374","citing_title":"Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment","ref_index":49,"is_internal_anchor":false},{"citing_arxiv_id":"2603.19282","citing_title":"Framing Effects in Independent-Agent Large Language Models: A Cross-Family Behavioral Analysis","ref_index":5,"is_internal_anchor":false},{"citing_arxiv_id":"2605.02765","citing_title":"U-Define: Designing User Workflows for Hard and Soft Constraints in LLM-Based Planning","ref_index":11,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/IDQGBKIHBKTVD27V3FIVAMSMBZ","json":"https://pith.science/pith/IDQGBKIHBKTVD27V3FIVAMSMBZ.json","graph_json":"https://pith.science/api/pith-number/IDQGBKIHBKTVD27V3FIVAMSMBZ/graph.json","events_json":"https://pith.science/api/pith-number/IDQGBKIHBKTVD27V3FIVAMSMBZ/events.json","paper":"https://pith.science/paper/IDQGBKIH"},"agent_actions":{"view_html":"https://pith.science/pith/IDQGBKIHBKTVD27V3FIVAMSMBZ","download_json":"https://pith.science/pith/IDQGBKIHBKTVD27V3FIVAMSMBZ.json","view_paper":"https://pith.science/paper/IDQGBKIH","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2302.03494&json=true","fetch_graph":"https://pith.science/api/pith-number/IDQGBKIHBKTVD27V3FIVAMSMBZ/graph.json","fetch_events":"https://pith.science/api/pith-number/IDQGBKIHBKTVD27V3FIVAMSMBZ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/IDQGBKIHBKTVD27V3FIVAMSMBZ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/IDQGBKIHBKTVD27V3FIVAMSMBZ/action/storage_attestation","attest_author":"https://pith.science/pith/IDQGBKIHBKTVD27V3FIVAMSMBZ/action/author_attestation","sign_citation":"https://pith.science/pith/IDQGBKIHBKTVD27V3FIVAMSMBZ/action/citation_signature","submit_replication":"https://pith.science/pith/IDQGBKIHBKTVD27V3FIVAMSMBZ/action/replication_record"}},"created_at":"2026-07-05T05:57:35.915507+00:00","updated_at":"2026-07-05T05:57:35.915507+00:00"}