{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:D5IHUZQ2BEBD2MJQUGHRMNM7BF","short_pith_number":"pith:D5IHUZQ2","canonical_record":{"source":{"id":"2409.12618","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-09-19T09:44:17Z","cross_cats_sorted":["cs.AI","cs.LG","cs.MA"],"title_canon_sha256":"eb8a0a1ea57ad9e7d800c240b9ffe7d01e530bc52bdcd84dfb3436d5cfec1456","abstract_canon_sha256":"02850672cae2d6181c45e5426285c552fc292ed9ab0e0b86b9de74af220026f2"},"schema_version":"1.0"},"canonical_sha256":"1f507a661a09023d3130a18f16359f096f2a5cab7dd055ffe0bb61a48c1f32b1","source":{"kind":"arxiv","id":"2409.12618","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2409.12618","created_at":"2026-07-05T09:14:23Z"},{"alias_kind":"arxiv_version","alias_value":"2409.12618v2","created_at":"2026-07-05T09:14:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.12618","created_at":"2026-07-05T09:14:23Z"},{"alias_kind":"pith_short_12","alias_value":"D5IHUZQ2BEBD","created_at":"2026-07-05T09:14:23Z"},{"alias_kind":"pith_short_16","alias_value":"D5IHUZQ2BEBD2MJQ","created_at":"2026-07-05T09:14:23Z"},{"alias_kind":"pith_short_8","alias_value":"D5IHUZQ2","created_at":"2026-07-05T09:14:23Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:D5IHUZQ2BEBD2MJQUGHRMNM7BF","target":"record","payload":{"canonical_record":{"source":{"id":"2409.12618","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-09-19T09:44:17Z","cross_cats_sorted":["cs.AI","cs.LG","cs.MA"],"title_canon_sha256":"eb8a0a1ea57ad9e7d800c240b9ffe7d01e530bc52bdcd84dfb3436d5cfec1456","abstract_canon_sha256":"02850672cae2d6181c45e5426285c552fc292ed9ab0e0b86b9de74af220026f2"},"schema_version":"1.0"},"canonical_sha256":"1f507a661a09023d3130a18f16359f096f2a5cab7dd055ffe0bb61a48c1f32b1","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:14:23.101013Z","signature_b64":"2v/eQu57o58m3J2Qp/1RxlcL4k8f0PBXAu6wQ5Kyo1jf8zHZ+w5kQdfHSNltYNKAFzTz87Rdp2WD4Et79leGBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1f507a661a09023d3130a18f16359f096f2a5cab7dd055ffe0bb61a48c1f32b1","last_reissued_at":"2026-07-05T09:14:23.100599Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:14:23.100599Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2409.12618","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":"2026-07-05T09:14:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LDoj1vSeBLEKZxWARQqH3u5tOBIlWJ12zcoEJZcxdW6toCoSBYmT3poUD01ZYOZjxsGXdy/4aDVA4JKfU/D4BA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T19:37:03.064554Z"},"content_sha256":"18257880bfc95358fa197e0481f564dbd8ad0d38696c2887b15764ff53df181e","schema_version":"1.0","event_id":"sha256:18257880bfc95358fa197e0481f564dbd8ad0d38696c2887b15764ff53df181e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:D5IHUZQ2BEBD2MJQUGHRMNM7BF","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Iteration of Thought: Leveraging Inner Dialogue for Autonomous Large Language Model Reasoning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.LG","cs.MA"],"primary_cat":"cs.CL","authors_text":"Ara Ghukasyan, Oktay Goktas, Santosh Kumar Radha, Yasamin Nouri Jelyani","submitted_at":"2024-09-19T09:44:17Z","abstract_excerpt":"Iterative human engagement is a common and effective means of leveraging the advanced language processing power of large language models (LLMs). Using well-structured prompts in a conversational manner, human users can effectively influence an LLM to develop more thoughtful and accurate responses. Motivated by this insight, we propose the Iteration of Thought (IoT) framework for enhancing LLM responses by generating \"thought\"-provoking prompts vis a vis an input query and the current iteration of an LLM's response. Unlike static or semi-static approaches, e.g. Chain of Thought (CoT) or Tree of"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.12618","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/2409.12618/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":"2026-07-05T09:14:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YNluoY+ldRSwUWJtYEiZfng8YesoBVa3wbSkju8FQGPrRzPr4ah/t/bViscl4vZ40Qh1QW6Yg6z2ifoUPN0LBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T19:37:03.065049Z"},"content_sha256":"6d3b851c9f7321f04474b2af32119e40ad26cd0cda894b6b55407ac68fc436b7","schema_version":"1.0","event_id":"sha256:6d3b851c9f7321f04474b2af32119e40ad26cd0cda894b6b55407ac68fc436b7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/D5IHUZQ2BEBD2MJQUGHRMNM7BF/bundle.json","state_url":"https://pith.science/pith/D5IHUZQ2BEBD2MJQUGHRMNM7BF/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/D5IHUZQ2BEBD2MJQUGHRMNM7BF/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":"2026-08-06T19:37:03Z","links":{"resolver":"https://pith.science/pith/D5IHUZQ2BEBD2MJQUGHRMNM7BF","bundle":"https://pith.science/pith/D5IHUZQ2BEBD2MJQUGHRMNM7BF/bundle.json","state":"https://pith.science/pith/D5IHUZQ2BEBD2MJQUGHRMNM7BF/state.json","well_known_bundle":"https://pith.science/.well-known/pith/D5IHUZQ2BEBD2MJQUGHRMNM7BF/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:D5IHUZQ2BEBD2MJQUGHRMNM7BF","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":"02850672cae2d6181c45e5426285c552fc292ed9ab0e0b86b9de74af220026f2","cross_cats_sorted":["cs.AI","cs.LG","cs.MA"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-09-19T09:44:17Z","title_canon_sha256":"eb8a0a1ea57ad9e7d800c240b9ffe7d01e530bc52bdcd84dfb3436d5cfec1456"},"schema_version":"1.0","source":{"id":"2409.12618","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2409.12618","created_at":"2026-07-05T09:14:23Z"},{"alias_kind":"arxiv_version","alias_value":"2409.12618v2","created_at":"2026-07-05T09:14:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.12618","created_at":"2026-07-05T09:14:23Z"},{"alias_kind":"pith_short_12","alias_value":"D5IHUZQ2BEBD","created_at":"2026-07-05T09:14:23Z"},{"alias_kind":"pith_short_16","alias_value":"D5IHUZQ2BEBD2MJQ","created_at":"2026-07-05T09:14:23Z"},{"alias_kind":"pith_short_8","alias_value":"D5IHUZQ2","created_at":"2026-07-05T09:14:23Z"}],"graph_snapshots":[{"event_id":"sha256:6d3b851c9f7321f04474b2af32119e40ad26cd0cda894b6b55407ac68fc436b7","target":"graph","created_at":"2026-07-05T09:14:23Z","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/2409.12618/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Iterative human engagement is a common and effective means of leveraging the advanced language processing power of large language models (LLMs). Using well-structured prompts in a conversational manner, human users can effectively influence an LLM to develop more thoughtful and accurate responses. Motivated by this insight, we propose the Iteration of Thought (IoT) framework for enhancing LLM responses by generating \"thought\"-provoking prompts vis a vis an input query and the current iteration of an LLM's response. Unlike static or semi-static approaches, e.g. Chain of Thought (CoT) or Tree of","authors_text":"Ara Ghukasyan, Oktay Goktas, Santosh Kumar Radha, Yasamin Nouri Jelyani","cross_cats":["cs.AI","cs.LG","cs.MA"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-09-19T09:44:17Z","title":"Iteration of Thought: Leveraging Inner Dialogue for Autonomous Large Language Model Reasoning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.12618","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":"sha256:18257880bfc95358fa197e0481f564dbd8ad0d38696c2887b15764ff53df181e","target":"record","created_at":"2026-07-05T09:14:23Z","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":"02850672cae2d6181c45e5426285c552fc292ed9ab0e0b86b9de74af220026f2","cross_cats_sorted":["cs.AI","cs.LG","cs.MA"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-09-19T09:44:17Z","title_canon_sha256":"eb8a0a1ea57ad9e7d800c240b9ffe7d01e530bc52bdcd84dfb3436d5cfec1456"},"schema_version":"1.0","source":{"id":"2409.12618","kind":"arxiv","version":2}},"canonical_sha256":"1f507a661a09023d3130a18f16359f096f2a5cab7dd055ffe0bb61a48c1f32b1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1f507a661a09023d3130a18f16359f096f2a5cab7dd055ffe0bb61a48c1f32b1","first_computed_at":"2026-07-05T09:14:23.100599Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:14:23.100599Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"2v/eQu57o58m3J2Qp/1RxlcL4k8f0PBXAu6wQ5Kyo1jf8zHZ+w5kQdfHSNltYNKAFzTz87Rdp2WD4Et79leGBg==","signature_status":"signed_v1","signed_at":"2026-07-05T09:14:23.101013Z","signed_message":"canonical_sha256_bytes"},"source_id":"2409.12618","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:18257880bfc95358fa197e0481f564dbd8ad0d38696c2887b15764ff53df181e","sha256:6d3b851c9f7321f04474b2af32119e40ad26cd0cda894b6b55407ac68fc436b7"],"state_sha256":"5a8f8d5ff66a0960d994a3f6426ac70bcc9c0f961b93adbfc2e9133658030cb7"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5+jnASfj1uPEs0YUY6H8iUsAIVjFmWzjpxegkX0WdJ285Zpx71Ylmn1TdgDb6ZnbFiL22t4BlaZGJroORlN1Cg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T19:37:03.068425Z","bundle_sha256":"ec3d49cf8d40534882e8f4f5721a8d8a1349175f5b70f4ebfe812abed123942a"}}