{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:Q2AKUTI7INKKGD4WLDIYFS7Y45","short_pith_number":"pith:Q2AKUTI7","canonical_record":{"source":{"id":"2505.17115","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.MA","submitted_at":"2025-05-21T15:48:13Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"59f4ea49aabb55cb8023b2cb57c481fb76ce9552bb2afa38c7cff2e1cee6eef7","abstract_canon_sha256":"809775d8f5efa1a247287757ea35c0d1692b23cf8c4c364d76b3aaf6258e56c2"},"schema_version":"1.0"},"canonical_sha256":"8680aa4d1f4354a30f9658d182cbf8e74835ee083e7ef02b0996a425779c135b","source":{"kind":"arxiv","id":"2505.17115","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.17115","created_at":"2026-07-05T11:12:32Z"},{"alias_kind":"arxiv_version","alias_value":"2505.17115v2","created_at":"2026-07-05T11:12:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.17115","created_at":"2026-07-05T11:12:32Z"},{"alias_kind":"pith_short_12","alias_value":"Q2AKUTI7INKK","created_at":"2026-07-05T11:12:32Z"},{"alias_kind":"pith_short_16","alias_value":"Q2AKUTI7INKKGD4W","created_at":"2026-07-05T11:12:32Z"},{"alias_kind":"pith_short_8","alias_value":"Q2AKUTI7","created_at":"2026-07-05T11:12:32Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:Q2AKUTI7INKKGD4WLDIYFS7Y45","target":"record","payload":{"canonical_record":{"source":{"id":"2505.17115","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.MA","submitted_at":"2025-05-21T15:48:13Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"59f4ea49aabb55cb8023b2cb57c481fb76ce9552bb2afa38c7cff2e1cee6eef7","abstract_canon_sha256":"809775d8f5efa1a247287757ea35c0d1692b23cf8c4c364d76b3aaf6258e56c2"},"schema_version":"1.0"},"canonical_sha256":"8680aa4d1f4354a30f9658d182cbf8e74835ee083e7ef02b0996a425779c135b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:12:32.855917Z","signature_b64":"VLF8JS6rpVWfPDSwoTw1niFEhzC5vudT8UIMaodgeFH7T3MM/jK8G6yGIUghc2HKTIee65cAfHoqD/uqnqZPBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8680aa4d1f4354a30f9658d182cbf8e74835ee083e7ef02b0996a425779c135b","last_reissued_at":"2026-07-05T11:12:32.855355Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:12:32.855355Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2505.17115","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":"2026-07-05T11:12:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KzuwTOKXRHemSpG+iheWg9XvcK8e0K8Qa9Rul765fCGUKpPpIvJZ9tViLru9F1KxmlwgDxqLJUb95Jip8ENfBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T06:26:59.601201Z"},"content_sha256":"681274f2418ac6225c53562d25b2fd2823c94520a01aeb93050fa90df3112340","schema_version":"1.0","event_id":"sha256:681274f2418ac6225c53562d25b2fd2823c94520a01aeb93050fa90df3112340"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:Q2AKUTI7INKKGD4WLDIYFS7Y45","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.MA","authors_text":"Heng Zhou, Lei Bai, Peiqin Zhuang, Rui Su, Ying Zhu","submitted_at":"2025-05-21T15:48:13Z","abstract_excerpt":"Recently, many approaches, such as Chain-of-Thought (CoT) prompting and Multi-Agent Debate (MAD), have been proposed to further enrich Large Language Models' (LLMs) complex problem-solving capacities in reasoning scenarios. However, these methods may fail to solve complex problems due to the lack of ability to find optimal solutions. Swarm Intelligence has been serving as a powerful tool for finding optima in the field of traditional optimization problems. To this end, we propose integrating swarm intelligence into the reasoning process by introducing a novel Agent-based Swarm Intelligence (AS"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.17115","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/2505.17115/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":"2026-07-05T11:12:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZkaG4wBA56tpgxx48gfUtBM3J1EFNVjyXFaTZx6YrIZ9ziThmPwhKi5hrcNTDrFlnOh7B9kRaQJxJeRQPHDqAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T06:26:59.601710Z"},"content_sha256":"edc5c7fa0290cca7ca419784dac551c2794489fd7aae40f76278f54e21598651","schema_version":"1.0","event_id":"sha256:edc5c7fa0290cca7ca419784dac551c2794489fd7aae40f76278f54e21598651"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/Q2AKUTI7INKKGD4WLDIYFS7Y45/bundle.json","state_url":"https://pith.science/pith/Q2AKUTI7INKKGD4WLDIYFS7Y45/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/Q2AKUTI7INKKGD4WLDIYFS7Y45/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":"2026-08-04T06:26:59Z","links":{"resolver":"https://pith.science/pith/Q2AKUTI7INKKGD4WLDIYFS7Y45","bundle":"https://pith.science/pith/Q2AKUTI7INKKGD4WLDIYFS7Y45/bundle.json","state":"https://pith.science/pith/Q2AKUTI7INKKGD4WLDIYFS7Y45/state.json","well_known_bundle":"https://pith.science/.well-known/pith/Q2AKUTI7INKKGD4WLDIYFS7Y45/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:Q2AKUTI7INKKGD4WLDIYFS7Y45","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":"809775d8f5efa1a247287757ea35c0d1692b23cf8c4c364d76b3aaf6258e56c2","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.MA","submitted_at":"2025-05-21T15:48:13Z","title_canon_sha256":"59f4ea49aabb55cb8023b2cb57c481fb76ce9552bb2afa38c7cff2e1cee6eef7"},"schema_version":"1.0","source":{"id":"2505.17115","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.17115","created_at":"2026-07-05T11:12:32Z"},{"alias_kind":"arxiv_version","alias_value":"2505.17115v2","created_at":"2026-07-05T11:12:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.17115","created_at":"2026-07-05T11:12:32Z"},{"alias_kind":"pith_short_12","alias_value":"Q2AKUTI7INKK","created_at":"2026-07-05T11:12:32Z"},{"alias_kind":"pith_short_16","alias_value":"Q2AKUTI7INKKGD4W","created_at":"2026-07-05T11:12:32Z"},{"alias_kind":"pith_short_8","alias_value":"Q2AKUTI7","created_at":"2026-07-05T11:12:32Z"}],"graph_snapshots":[{"event_id":"sha256:edc5c7fa0290cca7ca419784dac551c2794489fd7aae40f76278f54e21598651","target":"graph","created_at":"2026-07-05T11:12:32Z","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/2505.17115/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recently, many approaches, such as Chain-of-Thought (CoT) prompting and Multi-Agent Debate (MAD), have been proposed to further enrich Large Language Models' (LLMs) complex problem-solving capacities in reasoning scenarios. However, these methods may fail to solve complex problems due to the lack of ability to find optimal solutions. Swarm Intelligence has been serving as a powerful tool for finding optima in the field of traditional optimization problems. To this end, we propose integrating swarm intelligence into the reasoning process by introducing a novel Agent-based Swarm Intelligence (AS","authors_text":"Heng Zhou, Lei Bai, Peiqin Zhuang, Rui Su, Ying Zhu","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.MA","submitted_at":"2025-05-21T15:48:13Z","title":"Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.17115","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":"sha256:681274f2418ac6225c53562d25b2fd2823c94520a01aeb93050fa90df3112340","target":"record","created_at":"2026-07-05T11:12:32Z","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":"809775d8f5efa1a247287757ea35c0d1692b23cf8c4c364d76b3aaf6258e56c2","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.MA","submitted_at":"2025-05-21T15:48:13Z","title_canon_sha256":"59f4ea49aabb55cb8023b2cb57c481fb76ce9552bb2afa38c7cff2e1cee6eef7"},"schema_version":"1.0","source":{"id":"2505.17115","kind":"arxiv","version":2}},"canonical_sha256":"8680aa4d1f4354a30f9658d182cbf8e74835ee083e7ef02b0996a425779c135b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8680aa4d1f4354a30f9658d182cbf8e74835ee083e7ef02b0996a425779c135b","first_computed_at":"2026-07-05T11:12:32.855355Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:12:32.855355Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"VLF8JS6rpVWfPDSwoTw1niFEhzC5vudT8UIMaodgeFH7T3MM/jK8G6yGIUghc2HKTIee65cAfHoqD/uqnqZPBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:12:32.855917Z","signed_message":"canonical_sha256_bytes"},"source_id":"2505.17115","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:681274f2418ac6225c53562d25b2fd2823c94520a01aeb93050fa90df3112340","sha256:edc5c7fa0290cca7ca419784dac551c2794489fd7aae40f76278f54e21598651"],"state_sha256":"d0fb21fdb5c561c2c8721d88cf6f989c068c0602610961ba07c584cabe040a4f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zb2qT6yrcjpR6hmmnhPmLMARh4cmIbUtsY2FxCjeUM9DJrrXG0NQslKzOj4YFLcleJ23Qiv5Az7b7r6cvD+PDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T06:26:59.605044Z","bundle_sha256":"1497e7e4406d084cb94d7d36ed3cb3926fba34d8821f41cda27dfb30a3991db3"}}