{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:2P5ZLZG5K43UC6A7HPJNOFWGSE","short_pith_number":"pith:2P5ZLZG5","canonical_record":{"source":{"id":"2602.02709","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-02-02T19:23:33Z","cross_cats_sorted":[],"title_canon_sha256":"fdf5a09d287290788764d4ef03a2346256f1e2972bfebd3ce05e93f4c796c429","abstract_canon_sha256":"8a571bb0d78cf795dc71868e01fdc2ce4f8884fa864561fb4b00c2767698110b"},"schema_version":"1.0"},"canonical_sha256":"d3fb95e4dd573741781f3bd2d716c6910d8b299b5557a7a9bb426622bcc7cac0","source":{"kind":"arxiv","id":"2602.02709","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2602.02709","created_at":"2026-05-22T01:03:56Z"},{"alias_kind":"arxiv_version","alias_value":"2602.02709v3","created_at":"2026-05-22T01:03:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2602.02709","created_at":"2026-05-22T01:03:56Z"},{"alias_kind":"pith_short_12","alias_value":"2P5ZLZG5K43U","created_at":"2026-05-22T01:03:56Z"},{"alias_kind":"pith_short_16","alias_value":"2P5ZLZG5K43UC6A7","created_at":"2026-05-22T01:03:56Z"},{"alias_kind":"pith_short_8","alias_value":"2P5ZLZG5","created_at":"2026-05-22T01:03:56Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:2P5ZLZG5K43UC6A7HPJNOFWGSE","target":"record","payload":{"canonical_record":{"source":{"id":"2602.02709","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-02-02T19:23:33Z","cross_cats_sorted":[],"title_canon_sha256":"fdf5a09d287290788764d4ef03a2346256f1e2972bfebd3ce05e93f4c796c429","abstract_canon_sha256":"8a571bb0d78cf795dc71868e01fdc2ce4f8884fa864561fb4b00c2767698110b"},"schema_version":"1.0"},"canonical_sha256":"d3fb95e4dd573741781f3bd2d716c6910d8b299b5557a7a9bb426622bcc7cac0","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-22T01:03:56.097066Z","signature_b64":"eIY8MJfrAIJhmDkChqKBulTi+ngLqTIah0DhIuVMUmIMv5wQwnKVNtoZLDmgMTsFO1PUZVAgOVFNaTXqA9YEDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d3fb95e4dd573741781f3bd2d716c6910d8b299b5557a7a9bb426622bcc7cac0","last_reissued_at":"2026-05-22T01:03:56.096064Z","signature_status":"signed_v1","first_computed_at":"2026-05-22T01:03:56.096064Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2602.02709","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-22T01:03:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KWFTJq4AfwvEovk+ZG8RL3fhT8eI/4AZR5sMn/4ZRs0a/IHuRaOPgtnoIbzo4WZo4Xle63X5ZzsZlvDYy53jBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T05:18:58.568109Z"},"content_sha256":"eb619da6aedff48becaeadcb8626fb182c67b47271d6e2ff4d2cf95b44873068","schema_version":"1.0","event_id":"sha256:eb619da6aedff48becaeadcb8626fb182c67b47271d6e2ff4d2cf95b44873068"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:2P5ZLZG5K43UC6A7HPJNOFWGSE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"ATLAS: A Multi-LLM Training Framework for EvoDPO with Adaptive Reference Evolution","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Caleb Eunho Lee, Guang Lin, Jiyong Kwon, Madison Ann Sullivan, Ujin Jeon","submitted_at":"2026-02-02T19:23:33Z","abstract_excerpt":"Recent multi-LLM agent systems have shown promising capabilities for automated problem-solving, yet they predominantly rely on frozen agents or static fine-tuning pipelines. To address this limitation, our primary contribution is ATLAS (Adaptive Task-distributed Learning for Agentic Self-evolution), a multi-agent framework where specialized meta-agents collaboratively train and refine an active agent toward a domain-specific policy. A core challenge in iterative preference learning within these pipelines is the reliance on fixed reference models, which typically leads to overly conservative up"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2602.02709","kind":"arxiv","version":3},"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/2602.02709/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":"2026-05-22T01:03:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6pmCZPvkYZq9e2fQstO8oCRrfZnzsDMbaIlmYjxH/ckHWOJGD1Q1KyxhNSoNGRKk9Dhy2W90eR6ixLT4WEwtCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T05:18:58.568865Z"},"content_sha256":"a9ad560dd13f30f9c754ef63af85d9da825e26fa50a8fd8e809af1aec8269da1","schema_version":"1.0","event_id":"sha256:a9ad560dd13f30f9c754ef63af85d9da825e26fa50a8fd8e809af1aec8269da1"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2P5ZLZG5K43UC6A7HPJNOFWGSE/bundle.json","state_url":"https://pith.science/pith/2P5ZLZG5K43UC6A7HPJNOFWGSE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2P5ZLZG5K43UC6A7HPJNOFWGSE/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":"2026-05-31T05:18:58Z","links":{"resolver":"https://pith.science/pith/2P5ZLZG5K43UC6A7HPJNOFWGSE","bundle":"https://pith.science/pith/2P5ZLZG5K43UC6A7HPJNOFWGSE/bundle.json","state":"https://pith.science/pith/2P5ZLZG5K43UC6A7HPJNOFWGSE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2P5ZLZG5K43UC6A7HPJNOFWGSE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:2P5ZLZG5K43UC6A7HPJNOFWGSE","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":"8a571bb0d78cf795dc71868e01fdc2ce4f8884fa864561fb4b00c2767698110b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-02-02T19:23:33Z","title_canon_sha256":"fdf5a09d287290788764d4ef03a2346256f1e2972bfebd3ce05e93f4c796c429"},"schema_version":"1.0","source":{"id":"2602.02709","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2602.02709","created_at":"2026-05-22T01:03:56Z"},{"alias_kind":"arxiv_version","alias_value":"2602.02709v3","created_at":"2026-05-22T01:03:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2602.02709","created_at":"2026-05-22T01:03:56Z"},{"alias_kind":"pith_short_12","alias_value":"2P5ZLZG5K43U","created_at":"2026-05-22T01:03:56Z"},{"alias_kind":"pith_short_16","alias_value":"2P5ZLZG5K43UC6A7","created_at":"2026-05-22T01:03:56Z"},{"alias_kind":"pith_short_8","alias_value":"2P5ZLZG5","created_at":"2026-05-22T01:03:56Z"}],"graph_snapshots":[{"event_id":"sha256:a9ad560dd13f30f9c754ef63af85d9da825e26fa50a8fd8e809af1aec8269da1","target":"graph","created_at":"2026-05-22T01:03:56Z","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/2602.02709/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recent multi-LLM agent systems have shown promising capabilities for automated problem-solving, yet they predominantly rely on frozen agents or static fine-tuning pipelines. To address this limitation, our primary contribution is ATLAS (Adaptive Task-distributed Learning for Agentic Self-evolution), a multi-agent framework where specialized meta-agents collaboratively train and refine an active agent toward a domain-specific policy. A core challenge in iterative preference learning within these pipelines is the reliance on fixed reference models, which typically leads to overly conservative up","authors_text":"Caleb Eunho Lee, Guang Lin, Jiyong Kwon, Madison Ann Sullivan, Ujin Jeon","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-02-02T19:23:33Z","title":"ATLAS: A Multi-LLM Training Framework for EvoDPO with Adaptive Reference Evolution"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2602.02709","kind":"arxiv","version":3},"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:eb619da6aedff48becaeadcb8626fb182c67b47271d6e2ff4d2cf95b44873068","target":"record","created_at":"2026-05-22T01:03:56Z","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":"8a571bb0d78cf795dc71868e01fdc2ce4f8884fa864561fb4b00c2767698110b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-02-02T19:23:33Z","title_canon_sha256":"fdf5a09d287290788764d4ef03a2346256f1e2972bfebd3ce05e93f4c796c429"},"schema_version":"1.0","source":{"id":"2602.02709","kind":"arxiv","version":3}},"canonical_sha256":"d3fb95e4dd573741781f3bd2d716c6910d8b299b5557a7a9bb426622bcc7cac0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d3fb95e4dd573741781f3bd2d716c6910d8b299b5557a7a9bb426622bcc7cac0","first_computed_at":"2026-05-22T01:03:56.096064Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-22T01:03:56.096064Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"eIY8MJfrAIJhmDkChqKBulTi+ngLqTIah0DhIuVMUmIMv5wQwnKVNtoZLDmgMTsFO1PUZVAgOVFNaTXqA9YEDw==","signature_status":"signed_v1","signed_at":"2026-05-22T01:03:56.097066Z","signed_message":"canonical_sha256_bytes"},"source_id":"2602.02709","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:eb619da6aedff48becaeadcb8626fb182c67b47271d6e2ff4d2cf95b44873068","sha256:a9ad560dd13f30f9c754ef63af85d9da825e26fa50a8fd8e809af1aec8269da1"],"state_sha256":"8e8a993dc4178d055f8f531f026b60a7b2ae2c624173ee01abb4cbc3f6025caa"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"o1UviuAJVG3j3h7YbR2Js58UfX8n2AVJ62qmx+gkj5KrwXK+oXXU3ORgsuvWqwSAklvpkfCVqiXGZFIDF+4EDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-31T05:18:58.571725Z","bundle_sha256":"ffa6cf28bb8a18f743dd901c2176c1f13f58acb93aa85315c8cace9c4517f51b"}}