{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:GDDQXPGS7IYZ6EJE6D2BTY7DZY","short_pith_number":"pith:GDDQXPGS","canonical_record":{"source":{"id":"2310.05035","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-10-08T06:36:26Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"c2fa157793b8978d9ca1175f15cda3d0089d2da88ebb4e7631249603897a6482","abstract_canon_sha256":"7fc4187df3f667e2906a49436b44e91a5edaa885bddd67e54d8dd07960cede27"},"schema_version":"1.0"},"canonical_sha256":"30c70bbcd2fa319f1124f0f419e3e3ce3b2e9821a336f619f54ad3b1d094c400","source":{"kind":"arxiv","id":"2310.05035","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2310.05035","created_at":"2026-07-05T06:59:01Z"},{"alias_kind":"arxiv_version","alias_value":"2310.05035v2","created_at":"2026-07-05T06:59:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.05035","created_at":"2026-07-05T06:59:01Z"},{"alias_kind":"pith_short_12","alias_value":"GDDQXPGS7IYZ","created_at":"2026-07-05T06:59:01Z"},{"alias_kind":"pith_short_16","alias_value":"GDDQXPGS7IYZ6EJE","created_at":"2026-07-05T06:59:01Z"},{"alias_kind":"pith_short_8","alias_value":"GDDQXPGS","created_at":"2026-07-05T06:59:01Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:GDDQXPGS7IYZ6EJE6D2BTY7DZY","target":"record","payload":{"canonical_record":{"source":{"id":"2310.05035","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-10-08T06:36:26Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"c2fa157793b8978d9ca1175f15cda3d0089d2da88ebb4e7631249603897a6482","abstract_canon_sha256":"7fc4187df3f667e2906a49436b44e91a5edaa885bddd67e54d8dd07960cede27"},"schema_version":"1.0"},"canonical_sha256":"30c70bbcd2fa319f1124f0f419e3e3ce3b2e9821a336f619f54ad3b1d094c400","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:59:01.126364Z","signature_b64":"rjVbrzgIheb3+rYgOR/TsVf8JDtvMKqRqv2v6vRqgJFtuU0jVXZlPoxH5QpE2sXXbWvHJSHMBXAise13umgHBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"30c70bbcd2fa319f1124f0f419e3e3ce3b2e9821a336f619f54ad3b1d094c400","last_reissued_at":"2026-07-05T06:59:01.125893Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:59:01.125893Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2310.05035","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":"2026-07-05T06:59:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TpbD48NLoXAcf+kxneVKQwaweoFTt0oLH3a7b4Nfqd84+O2FBgRyiGgY6aNoGrok9qAgtEou7I5gHP3+N//uCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T19:04:42.729855Z"},"content_sha256":"ec7c409c2d9efa4b72605e39f88393b4c250111b10346e9d90ca7ffd0a1acf47","schema_version":"1.0","event_id":"sha256:ec7c409c2d9efa4b72605e39f88393b4c250111b10346e9d90ca7ffd0a1acf47"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:GDDQXPGS7IYZ6EJE6D2BTY7DZY","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Self-Convinced Prompting: Few-Shot Question Answering with Repeated Introspection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Chen Jason Zhang, Haodi Zhang, Kaishun Wu, Min Cai, Rui Mao, Xinhe Zhang","submitted_at":"2023-10-08T06:36:26Z","abstract_excerpt":"While large language models (LLMs) such as ChatGPT and PaLM have demonstrated remarkable performance in various language understanding and generation tasks, their capabilities in complex reasoning and intricate knowledge utilization still fall short of human-level proficiency. Recent studies have established the effectiveness of prompts in steering LLMs towards generating desired outputs. Building on these insights, we introduce a novel framework that harnesses the potential of large-scale pre-trained language models, to iteratively enhance performance of the LLMs. Our framework incorporates t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.05035","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/2310.05035/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":"2026-07-05T06:59:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XVYhTP4Mq0PqcP0M8+85US720VmqIrzQykkFlwfj2Hkixt4Qok8A5pP/5n7jAZMtJzAckNapiclpqGqS/qprDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T19:04:42.730364Z"},"content_sha256":"3a486f68274ba51088ff71c2393818c077adf272fbec676a5c2bc4510aece5d8","schema_version":"1.0","event_id":"sha256:3a486f68274ba51088ff71c2393818c077adf272fbec676a5c2bc4510aece5d8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/GDDQXPGS7IYZ6EJE6D2BTY7DZY/bundle.json","state_url":"https://pith.science/pith/GDDQXPGS7IYZ6EJE6D2BTY7DZY/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/GDDQXPGS7IYZ6EJE6D2BTY7DZY/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":"2026-08-20T19:04:42Z","links":{"resolver":"https://pith.science/pith/GDDQXPGS7IYZ6EJE6D2BTY7DZY","bundle":"https://pith.science/pith/GDDQXPGS7IYZ6EJE6D2BTY7DZY/bundle.json","state":"https://pith.science/pith/GDDQXPGS7IYZ6EJE6D2BTY7DZY/state.json","well_known_bundle":"https://pith.science/.well-known/pith/GDDQXPGS7IYZ6EJE6D2BTY7DZY/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:GDDQXPGS7IYZ6EJE6D2BTY7DZY","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":"7fc4187df3f667e2906a49436b44e91a5edaa885bddd67e54d8dd07960cede27","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-10-08T06:36:26Z","title_canon_sha256":"c2fa157793b8978d9ca1175f15cda3d0089d2da88ebb4e7631249603897a6482"},"schema_version":"1.0","source":{"id":"2310.05035","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2310.05035","created_at":"2026-07-05T06:59:01Z"},{"alias_kind":"arxiv_version","alias_value":"2310.05035v2","created_at":"2026-07-05T06:59:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.05035","created_at":"2026-07-05T06:59:01Z"},{"alias_kind":"pith_short_12","alias_value":"GDDQXPGS7IYZ","created_at":"2026-07-05T06:59:01Z"},{"alias_kind":"pith_short_16","alias_value":"GDDQXPGS7IYZ6EJE","created_at":"2026-07-05T06:59:01Z"},{"alias_kind":"pith_short_8","alias_value":"GDDQXPGS","created_at":"2026-07-05T06:59:01Z"}],"graph_snapshots":[{"event_id":"sha256:3a486f68274ba51088ff71c2393818c077adf272fbec676a5c2bc4510aece5d8","target":"graph","created_at":"2026-07-05T06:59:01Z","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/2310.05035/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"While large language models (LLMs) such as ChatGPT and PaLM have demonstrated remarkable performance in various language understanding and generation tasks, their capabilities in complex reasoning and intricate knowledge utilization still fall short of human-level proficiency. Recent studies have established the effectiveness of prompts in steering LLMs towards generating desired outputs. Building on these insights, we introduce a novel framework that harnesses the potential of large-scale pre-trained language models, to iteratively enhance performance of the LLMs. Our framework incorporates t","authors_text":"Chen Jason Zhang, Haodi Zhang, Kaishun Wu, Min Cai, Rui Mao, Xinhe Zhang","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-10-08T06:36:26Z","title":"Self-Convinced Prompting: Few-Shot Question Answering with Repeated Introspection"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.05035","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:ec7c409c2d9efa4b72605e39f88393b4c250111b10346e9d90ca7ffd0a1acf47","target":"record","created_at":"2026-07-05T06:59:01Z","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":"7fc4187df3f667e2906a49436b44e91a5edaa885bddd67e54d8dd07960cede27","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-10-08T06:36:26Z","title_canon_sha256":"c2fa157793b8978d9ca1175f15cda3d0089d2da88ebb4e7631249603897a6482"},"schema_version":"1.0","source":{"id":"2310.05035","kind":"arxiv","version":2}},"canonical_sha256":"30c70bbcd2fa319f1124f0f419e3e3ce3b2e9821a336f619f54ad3b1d094c400","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"30c70bbcd2fa319f1124f0f419e3e3ce3b2e9821a336f619f54ad3b1d094c400","first_computed_at":"2026-07-05T06:59:01.125893Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:59:01.125893Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"rjVbrzgIheb3+rYgOR/TsVf8JDtvMKqRqv2v6vRqgJFtuU0jVXZlPoxH5QpE2sXXbWvHJSHMBXAise13umgHBw==","signature_status":"signed_v1","signed_at":"2026-07-05T06:59:01.126364Z","signed_message":"canonical_sha256_bytes"},"source_id":"2310.05035","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ec7c409c2d9efa4b72605e39f88393b4c250111b10346e9d90ca7ffd0a1acf47","sha256:3a486f68274ba51088ff71c2393818c077adf272fbec676a5c2bc4510aece5d8"],"state_sha256":"89a77ca0f1578c1eebfec42cd6968da0d5dbc0171b8c88908bd693800202a2a2"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"riVUTLEFOJn+UbWH/Rg6cGqeejpA/Dw4ZbxIlkOFRCXAK2LqvYMVFDq/v/3e5FKjJO+N4cZIqMOf/HWcbe/4Aw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-20T19:04:42.734136Z","bundle_sha256":"cce8550d4502dea20b8559b62d8652d2bd5dc7bdb2feb53ed9b2e25f36f96406"}}