{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:LWINDPQUIM7UMXHMWCNVIXDH5X","short_pith_number":"pith:LWINDPQU","canonical_record":{"source":{"id":"2501.19278","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-01-31T16:42:31Z","cross_cats_sorted":[],"title_canon_sha256":"deb06ecf6c7dcc9582ff475bc5627818b7f9cce550030bd2bdc754f3720fb4f1","abstract_canon_sha256":"185472bc8b7beeedde11bd69e8466790e0ee993862b3567254c6584488a3905d"},"schema_version":"1.0"},"canonical_sha256":"5d90d1be14433f465cecb09b545c67ede9d84d33f05b5f343241f9e91d2a7212","source":{"kind":"arxiv","id":"2501.19278","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.19278","created_at":"2026-07-05T10:07:58Z"},{"alias_kind":"arxiv_version","alias_value":"2501.19278v1","created_at":"2026-07-05T10:07:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.19278","created_at":"2026-07-05T10:07:58Z"},{"alias_kind":"pith_short_12","alias_value":"LWINDPQUIM7U","created_at":"2026-07-05T10:07:58Z"},{"alias_kind":"pith_short_16","alias_value":"LWINDPQUIM7UMXHM","created_at":"2026-07-05T10:07:58Z"},{"alias_kind":"pith_short_8","alias_value":"LWINDPQU","created_at":"2026-07-05T10:07:58Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:LWINDPQUIM7UMXHMWCNVIXDH5X","target":"record","payload":{"canonical_record":{"source":{"id":"2501.19278","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-01-31T16:42:31Z","cross_cats_sorted":[],"title_canon_sha256":"deb06ecf6c7dcc9582ff475bc5627818b7f9cce550030bd2bdc754f3720fb4f1","abstract_canon_sha256":"185472bc8b7beeedde11bd69e8466790e0ee993862b3567254c6584488a3905d"},"schema_version":"1.0"},"canonical_sha256":"5d90d1be14433f465cecb09b545c67ede9d84d33f05b5f343241f9e91d2a7212","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:07:58.766895Z","signature_b64":"F82K7aAUZSJmJxESIFJDG64Q1dfgiZHc3v1BqvDva8/R+kkwyTyppOdJF6scrOnJhVfM1P8SD4DPhmVLLQiZDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5d90d1be14433f465cecb09b545c67ede9d84d33f05b5f343241f9e91d2a7212","last_reissued_at":"2026-07-05T10:07:58.766374Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:07:58.766374Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2501.19278","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:07:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cl9eKP2HUnfH163OuTi5qnNqIUzsxNp6SU4Az0jPHL7Q+1qmn6NoyhsXh5kYsa8OeYXoVrhVVaWK4hitHxBZBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T08:22:58.639814Z"},"content_sha256":"e967beb1f782363345de077333d5f19fb13233350c240e063a8ba24e9d22dec9","schema_version":"1.0","event_id":"sha256:e967beb1f782363345de077333d5f19fb13233350c240e063a8ba24e9d22dec9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:LWINDPQUIM7UMXHMWCNVIXDH5X","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Pheromone-based Learning of Optimal Reasoning Paths","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Aditya Tiwari, Anirudh Chari, Brian Zhou, Richard Lian, Suraj Reddy","submitted_at":"2025-01-31T16:42:31Z","abstract_excerpt":"Large Language Models (LLMs) have demonstrated remarkable reasoning capabilities through chain-of-thought prompting, yet discovering effective reasoning methods for complex problems remains challenging due to the vast space of possible intermediate steps. We introduce Ant Colony Optimization-guided Tree of Thought (ACO-ToT), a novel algorithm that combines ACO with LLMs to discover optimal reasoning paths for complex problems efficiently. Drawing inspiration from Hebbian learning in neurological systems, our method employs a collection of distinctly fine-tuned LLM \"ants\" to traverse and lay ph"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.19278","kind":"arxiv","version":1},"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/2501.19278/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":"2026-07-05T10:07:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"eorYCTUKluDRbZXj6AhzxDmTiGKxYRB09T5gQCaHr1+OS38G80Jh3dj1JlkSzVKisXpZxMx3rFZTJzf2zBCBDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T08:22:58.640318Z"},"content_sha256":"50f7acb677c52bb00e4243e25b238067074fa4f5c484b564cf1fd4c16983c2a7","schema_version":"1.0","event_id":"sha256:50f7acb677c52bb00e4243e25b238067074fa4f5c484b564cf1fd4c16983c2a7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LWINDPQUIM7UMXHMWCNVIXDH5X/bundle.json","state_url":"https://pith.science/pith/LWINDPQUIM7UMXHMWCNVIXDH5X/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LWINDPQUIM7UMXHMWCNVIXDH5X/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":"2026-08-10T08:22:58Z","links":{"resolver":"https://pith.science/pith/LWINDPQUIM7UMXHMWCNVIXDH5X","bundle":"https://pith.science/pith/LWINDPQUIM7UMXHMWCNVIXDH5X/bundle.json","state":"https://pith.science/pith/LWINDPQUIM7UMXHMWCNVIXDH5X/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LWINDPQUIM7UMXHMWCNVIXDH5X/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:LWINDPQUIM7UMXHMWCNVIXDH5X","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":"185472bc8b7beeedde11bd69e8466790e0ee993862b3567254c6584488a3905d","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-01-31T16:42:31Z","title_canon_sha256":"deb06ecf6c7dcc9582ff475bc5627818b7f9cce550030bd2bdc754f3720fb4f1"},"schema_version":"1.0","source":{"id":"2501.19278","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.19278","created_at":"2026-07-05T10:07:58Z"},{"alias_kind":"arxiv_version","alias_value":"2501.19278v1","created_at":"2026-07-05T10:07:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.19278","created_at":"2026-07-05T10:07:58Z"},{"alias_kind":"pith_short_12","alias_value":"LWINDPQUIM7U","created_at":"2026-07-05T10:07:58Z"},{"alias_kind":"pith_short_16","alias_value":"LWINDPQUIM7UMXHM","created_at":"2026-07-05T10:07:58Z"},{"alias_kind":"pith_short_8","alias_value":"LWINDPQU","created_at":"2026-07-05T10:07:58Z"}],"graph_snapshots":[{"event_id":"sha256:50f7acb677c52bb00e4243e25b238067074fa4f5c484b564cf1fd4c16983c2a7","target":"graph","created_at":"2026-07-05T10:07:58Z","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/2501.19278/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large Language Models (LLMs) have demonstrated remarkable reasoning capabilities through chain-of-thought prompting, yet discovering effective reasoning methods for complex problems remains challenging due to the vast space of possible intermediate steps. We introduce Ant Colony Optimization-guided Tree of Thought (ACO-ToT), a novel algorithm that combines ACO with LLMs to discover optimal reasoning paths for complex problems efficiently. Drawing inspiration from Hebbian learning in neurological systems, our method employs a collection of distinctly fine-tuned LLM \"ants\" to traverse and lay ph","authors_text":"Aditya Tiwari, Anirudh Chari, Brian Zhou, Richard Lian, Suraj Reddy","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-01-31T16:42:31Z","title":"Pheromone-based Learning of Optimal Reasoning Paths"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.19278","kind":"arxiv","version":1},"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:e967beb1f782363345de077333d5f19fb13233350c240e063a8ba24e9d22dec9","target":"record","created_at":"2026-07-05T10:07:58Z","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":"185472bc8b7beeedde11bd69e8466790e0ee993862b3567254c6584488a3905d","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-01-31T16:42:31Z","title_canon_sha256":"deb06ecf6c7dcc9582ff475bc5627818b7f9cce550030bd2bdc754f3720fb4f1"},"schema_version":"1.0","source":{"id":"2501.19278","kind":"arxiv","version":1}},"canonical_sha256":"5d90d1be14433f465cecb09b545c67ede9d84d33f05b5f343241f9e91d2a7212","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5d90d1be14433f465cecb09b545c67ede9d84d33f05b5f343241f9e91d2a7212","first_computed_at":"2026-07-05T10:07:58.766374Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:07:58.766374Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"F82K7aAUZSJmJxESIFJDG64Q1dfgiZHc3v1BqvDva8/R+kkwyTyppOdJF6scrOnJhVfM1P8SD4DPhmVLLQiZDA==","signature_status":"signed_v1","signed_at":"2026-07-05T10:07:58.766895Z","signed_message":"canonical_sha256_bytes"},"source_id":"2501.19278","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e967beb1f782363345de077333d5f19fb13233350c240e063a8ba24e9d22dec9","sha256:50f7acb677c52bb00e4243e25b238067074fa4f5c484b564cf1fd4c16983c2a7"],"state_sha256":"3f4c964f586fe04e0305e2e00cf9880744f007db1dd667de7c863951ea6704a2"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6u6RQW1xFGSpfhMeGjQBtG2sl5+u0HXEIsOz1gFa5OpGvgTeebd79AShWl8TlNxQklHbUrRTOXU4ud7OxPWyAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T08:22:58.648972Z","bundle_sha256":"ef08c1de30dd0f18f3cdb087312001c92610acbda1d454cf0e601892da8fb8bf"}}