{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:VBFQQXGDQMGSSOSDFP52JHU23Y","short_pith_number":"pith:VBFQQXGD","canonical_record":{"source":{"id":"2304.03262","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.AI","submitted_at":"2023-04-06T17:47:29Z","cross_cats_sorted":[],"title_canon_sha256":"27691f8a2b493f4b705d747187cb365d9ea8d61b6df670459c7af085d99797c6","abstract_canon_sha256":"b868a2e765435f7b6391e3a1450db690371df0236f9f87f5e871344d2eea0ab5"},"schema_version":"1.0"},"canonical_sha256":"a84b085cc3830d293a432bfba49e9ade3af8e59800d6f5890092d088f12de38f","source":{"kind":"arxiv","id":"2304.03262","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2304.03262","created_at":"2026-07-05T06:02:09Z"},{"alias_kind":"arxiv_version","alias_value":"2304.03262v2","created_at":"2026-07-05T06:02:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2304.03262","created_at":"2026-07-05T06:02:09Z"},{"alias_kind":"pith_short_12","alias_value":"VBFQQXGDQMGS","created_at":"2026-07-05T06:02:09Z"},{"alias_kind":"pith_short_16","alias_value":"VBFQQXGDQMGSSOSD","created_at":"2026-07-05T06:02:09Z"},{"alias_kind":"pith_short_8","alias_value":"VBFQQXGD","created_at":"2026-07-05T06:02:09Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:VBFQQXGDQMGSSOSDFP52JHU23Y","target":"record","payload":{"canonical_record":{"source":{"id":"2304.03262","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.AI","submitted_at":"2023-04-06T17:47:29Z","cross_cats_sorted":[],"title_canon_sha256":"27691f8a2b493f4b705d747187cb365d9ea8d61b6df670459c7af085d99797c6","abstract_canon_sha256":"b868a2e765435f7b6391e3a1450db690371df0236f9f87f5e871344d2eea0ab5"},"schema_version":"1.0"},"canonical_sha256":"a84b085cc3830d293a432bfba49e9ade3af8e59800d6f5890092d088f12de38f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:02:09.513212Z","signature_b64":"rHBa27ZLfQjy4C1mqJbjGM93AhpsO9yzZ1Fr/BH91+6YanTmrqeULlDNcdJkAfLHeEdMhaYgo0hWfBMQ1mneDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a84b085cc3830d293a432bfba49e9ade3af8e59800d6f5890092d088f12de38f","last_reissued_at":"2026-07-05T06:02:09.512823Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:02:09.512823Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2304.03262","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T06:02:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dXqREVFPjvSGBK9aYsGkwohnRKOF+ZumP/CGPKtsCpIbFcqL5URbprdEt1XhcfIENA5D8TExuCBDFYM3ya5YCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-01T12:58:12.026619Z"},"content_sha256":"6ecab809d1efd15cefa78785007bb65879d8a285cab7f506595a299f3f4af4be","schema_version":"1.0","event_id":"sha256:6ecab809d1efd15cefa78785007bb65879d8a285cab7f506595a299f3f4af4be"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:VBFQQXGDQMGSSOSDFP52JHU23Y","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"When do you need Chain-of-Thought Prompting for ChatGPT?","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Heng Huang, Jiuhai Chen, Lichang Chen, Tianyi Zhou","submitted_at":"2023-04-06T17:47:29Z","abstract_excerpt":"Chain-of-Thought (CoT) prompting can effectively elicit complex multi-step reasoning from Large Language Models~(LLMs). For example, by simply adding CoT instruction ``Let's think step-by-step'' to each input query of MultiArith dataset, GPT-3's accuracy can be improved from 17.7\\% to 78.7\\%. However, it is not clear whether CoT is still effective on more recent instruction finetuned (IFT) LLMs such as ChatGPT. Surprisingly, on ChatGPT, CoT is no longer effective for certain tasks such as arithmetic reasoning while still keeping effective on other reasoning tasks. Moreover, on the former tasks"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2304.03262","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/2304.03262/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T06:02:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sq6maWdGDLZnZ9UUUXNdaBpO62Hry1vqCic9DFQ8jd6nDDqgPlhL8es3dyVna0d+zcdSR0di/iIyJNYS2KROBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-01T12:58:12.026909Z"},"content_sha256":"96b35954118c8c899a9f5ddee50cb57740c7315224d2220c793eecab9d6da684","schema_version":"1.0","event_id":"sha256:96b35954118c8c899a9f5ddee50cb57740c7315224d2220c793eecab9d6da684"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VBFQQXGDQMGSSOSDFP52JHU23Y/bundle.json","state_url":"https://pith.science/pith/VBFQQXGDQMGSSOSDFP52JHU23Y/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VBFQQXGDQMGSSOSDFP52JHU23Y/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-01T12:58:12Z","links":{"resolver":"https://pith.science/pith/VBFQQXGDQMGSSOSDFP52JHU23Y","bundle":"https://pith.science/pith/VBFQQXGDQMGSSOSDFP52JHU23Y/bundle.json","state":"https://pith.science/pith/VBFQQXGDQMGSSOSDFP52JHU23Y/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VBFQQXGDQMGSSOSDFP52JHU23Y/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:VBFQQXGDQMGSSOSDFP52JHU23Y","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":"b868a2e765435f7b6391e3a1450db690371df0236f9f87f5e871344d2eea0ab5","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.AI","submitted_at":"2023-04-06T17:47:29Z","title_canon_sha256":"27691f8a2b493f4b705d747187cb365d9ea8d61b6df670459c7af085d99797c6"},"schema_version":"1.0","source":{"id":"2304.03262","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2304.03262","created_at":"2026-07-05T06:02:09Z"},{"alias_kind":"arxiv_version","alias_value":"2304.03262v2","created_at":"2026-07-05T06:02:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2304.03262","created_at":"2026-07-05T06:02:09Z"},{"alias_kind":"pith_short_12","alias_value":"VBFQQXGDQMGS","created_at":"2026-07-05T06:02:09Z"},{"alias_kind":"pith_short_16","alias_value":"VBFQQXGDQMGSSOSD","created_at":"2026-07-05T06:02:09Z"},{"alias_kind":"pith_short_8","alias_value":"VBFQQXGD","created_at":"2026-07-05T06:02:09Z"}],"graph_snapshots":[{"event_id":"sha256:96b35954118c8c899a9f5ddee50cb57740c7315224d2220c793eecab9d6da684","target":"graph","created_at":"2026-07-05T06:02:09Z","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/2304.03262/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Chain-of-Thought (CoT) prompting can effectively elicit complex multi-step reasoning from Large Language Models~(LLMs). For example, by simply adding CoT instruction ``Let's think step-by-step'' to each input query of MultiArith dataset, GPT-3's accuracy can be improved from 17.7\\% to 78.7\\%. However, it is not clear whether CoT is still effective on more recent instruction finetuned (IFT) LLMs such as ChatGPT. Surprisingly, on ChatGPT, CoT is no longer effective for certain tasks such as arithmetic reasoning while still keeping effective on other reasoning tasks. Moreover, on the former tasks","authors_text":"Heng Huang, Jiuhai Chen, Lichang Chen, Tianyi Zhou","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.AI","submitted_at":"2023-04-06T17:47:29Z","title":"When do you need Chain-of-Thought Prompting for ChatGPT?"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2304.03262","kind":"arxiv","version":2},"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":"sha256:6ecab809d1efd15cefa78785007bb65879d8a285cab7f506595a299f3f4af4be","target":"record","created_at":"2026-07-05T06:02:09Z","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":"b868a2e765435f7b6391e3a1450db690371df0236f9f87f5e871344d2eea0ab5","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.AI","submitted_at":"2023-04-06T17:47:29Z","title_canon_sha256":"27691f8a2b493f4b705d747187cb365d9ea8d61b6df670459c7af085d99797c6"},"schema_version":"1.0","source":{"id":"2304.03262","kind":"arxiv","version":2}},"canonical_sha256":"a84b085cc3830d293a432bfba49e9ade3af8e59800d6f5890092d088f12de38f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a84b085cc3830d293a432bfba49e9ade3af8e59800d6f5890092d088f12de38f","first_computed_at":"2026-07-05T06:02:09.512823Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:02:09.512823Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"rHBa27ZLfQjy4C1mqJbjGM93AhpsO9yzZ1Fr/BH91+6YanTmrqeULlDNcdJkAfLHeEdMhaYgo0hWfBMQ1mneDg==","signature_status":"signed_v1","signed_at":"2026-07-05T06:02:09.513212Z","signed_message":"canonical_sha256_bytes"},"source_id":"2304.03262","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6ecab809d1efd15cefa78785007bb65879d8a285cab7f506595a299f3f4af4be","sha256:96b35954118c8c899a9f5ddee50cb57740c7315224d2220c793eecab9d6da684"],"state_sha256":"9a204392af173dcff94f24d50766dda4f868a6cb45efc6c0e07d608b2243583e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DgPqGhJ/Kz2Hgyc/aLNLIooEJEjNTHf96utrvHWsjF8195ZO26Ucd9JOEW0mbZpRb2RIQBZ/vra3zGAgBtEUCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-01T12:58:12.030196Z","bundle_sha256":"650cde1a5c44920519d57908b4a3a5cd4ae3707d2269554c90aaa233b71a7b94"}}