{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:GKARKMBPZRQR4CDFZ3HGTXK7RY","short_pith_number":"pith:GKARKMBP","canonical_record":{"source":{"id":"2311.13569","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-11-13T12:24:54Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"d8784d4752241135e8cebc60a995c3667c49ee228b063c50d4acbda4a89d8397","abstract_canon_sha256":"9c05fc75b5a8c3f66a64fe2757aca1db0f1ee1eff81612463281a613e02e4f15"},"schema_version":"1.0"},"canonical_sha256":"328115302fcc611e0865cece69dd5f8e18d9f22480dfeefa50bffbf9a5d9e346","source":{"kind":"arxiv","id":"2311.13569","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.13569","created_at":"2026-07-05T08:23:57Z"},{"alias_kind":"arxiv_version","alias_value":"2311.13569v2","created_at":"2026-07-05T08:23:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.13569","created_at":"2026-07-05T08:23:57Z"},{"alias_kind":"pith_short_12","alias_value":"GKARKMBPZRQR","created_at":"2026-07-05T08:23:57Z"},{"alias_kind":"pith_short_16","alias_value":"GKARKMBPZRQR4CDF","created_at":"2026-07-05T08:23:57Z"},{"alias_kind":"pith_short_8","alias_value":"GKARKMBP","created_at":"2026-07-05T08:23:57Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:GKARKMBPZRQR4CDFZ3HGTXK7RY","target":"record","payload":{"canonical_record":{"source":{"id":"2311.13569","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-11-13T12:24:54Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"d8784d4752241135e8cebc60a995c3667c49ee228b063c50d4acbda4a89d8397","abstract_canon_sha256":"9c05fc75b5a8c3f66a64fe2757aca1db0f1ee1eff81612463281a613e02e4f15"},"schema_version":"1.0"},"canonical_sha256":"328115302fcc611e0865cece69dd5f8e18d9f22480dfeefa50bffbf9a5d9e346","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:23:57.677630Z","signature_b64":"9V9gCUjel1A7p4H0ryCbXNADaqcSkZ8Pg8LkZwCZg22H+vOGEGjZpVqzp695WmDM/DESCzzkzw0pl/xYUPiyBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"328115302fcc611e0865cece69dd5f8e18d9f22480dfeefa50bffbf9a5d9e346","last_reissued_at":"2026-07-05T08:23:57.677116Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:23:57.677116Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2311.13569","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":"2026-07-05T08:23:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mFS3noR/AYF+9Up0QdzJh9+VFOC9He80iFboQnTaLnWU2HIru9Hjxhb1a696InH/fqu0xRvnvAML7zWgsBnmDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T07:57:22.765268Z"},"content_sha256":"b781200f77fc5837c1dd3eb165ae4c47c60481c477cca0680dee314ca46f5564","schema_version":"1.0","event_id":"sha256:b781200f77fc5837c1dd3eb165ae4c47c60481c477cca0680dee314ca46f5564"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:GKARKMBPZRQR4CDFZ3HGTXK7RY","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Combinatorial Optimization with Policy Adaptation using Latent Space Search","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Alexandre Laterre, Arnu Pretorius, Clement Bonnet, Felix Chalumeau, Nathan Grinsztajn, Shikha Surana, Thomas D. Barrett","submitted_at":"2023-11-13T12:24:54Z","abstract_excerpt":"Combinatorial Optimization underpins many real-world applications and yet, designing performant algorithms to solve these complex, typically NP-hard, problems remains a significant research challenge. Reinforcement Learning (RL) provides a versatile framework for designing heuristics across a broad spectrum of problem domains. However, despite notable progress, RL has not yet supplanted industrial solvers as the go-to solution. Current approaches emphasize pre-training heuristics that construct solutions but often rely on search procedures with limited variance, such as stochastically sampling"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.13569","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/2311.13569/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":"2026-07-05T08:23:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FIglt44jyVqTPVI2YDK/bCphrQ00vgl3ZF0Hmp6GBJhFE5jV4e/yMFUHTJwwDJSLb7c0rJWs/TNLNj4vn8wsDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T07:57:22.765648Z"},"content_sha256":"5979e41f18f422b85c3c3ade04619b2bcc2851a62165151903d25b4e7a96ce0b","schema_version":"1.0","event_id":"sha256:5979e41f18f422b85c3c3ade04619b2bcc2851a62165151903d25b4e7a96ce0b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/GKARKMBPZRQR4CDFZ3HGTXK7RY/bundle.json","state_url":"https://pith.science/pith/GKARKMBPZRQR4CDFZ3HGTXK7RY/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/GKARKMBPZRQR4CDFZ3HGTXK7RY/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":"2026-07-07T07:57:22Z","links":{"resolver":"https://pith.science/pith/GKARKMBPZRQR4CDFZ3HGTXK7RY","bundle":"https://pith.science/pith/GKARKMBPZRQR4CDFZ3HGTXK7RY/bundle.json","state":"https://pith.science/pith/GKARKMBPZRQR4CDFZ3HGTXK7RY/state.json","well_known_bundle":"https://pith.science/.well-known/pith/GKARKMBPZRQR4CDFZ3HGTXK7RY/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:GKARKMBPZRQR4CDFZ3HGTXK7RY","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":"9c05fc75b5a8c3f66a64fe2757aca1db0f1ee1eff81612463281a613e02e4f15","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-11-13T12:24:54Z","title_canon_sha256":"d8784d4752241135e8cebc60a995c3667c49ee228b063c50d4acbda4a89d8397"},"schema_version":"1.0","source":{"id":"2311.13569","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.13569","created_at":"2026-07-05T08:23:57Z"},{"alias_kind":"arxiv_version","alias_value":"2311.13569v2","created_at":"2026-07-05T08:23:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.13569","created_at":"2026-07-05T08:23:57Z"},{"alias_kind":"pith_short_12","alias_value":"GKARKMBPZRQR","created_at":"2026-07-05T08:23:57Z"},{"alias_kind":"pith_short_16","alias_value":"GKARKMBPZRQR4CDF","created_at":"2026-07-05T08:23:57Z"},{"alias_kind":"pith_short_8","alias_value":"GKARKMBP","created_at":"2026-07-05T08:23:57Z"}],"graph_snapshots":[{"event_id":"sha256:5979e41f18f422b85c3c3ade04619b2bcc2851a62165151903d25b4e7a96ce0b","target":"graph","created_at":"2026-07-05T08:23:57Z","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/2311.13569/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Combinatorial Optimization underpins many real-world applications and yet, designing performant algorithms to solve these complex, typically NP-hard, problems remains a significant research challenge. Reinforcement Learning (RL) provides a versatile framework for designing heuristics across a broad spectrum of problem domains. However, despite notable progress, RL has not yet supplanted industrial solvers as the go-to solution. Current approaches emphasize pre-training heuristics that construct solutions but often rely on search procedures with limited variance, such as stochastically sampling","authors_text":"Alexandre Laterre, Arnu Pretorius, Clement Bonnet, Felix Chalumeau, Nathan Grinsztajn, Shikha Surana, Thomas D. Barrett","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-11-13T12:24:54Z","title":"Combinatorial Optimization with Policy Adaptation using Latent Space Search"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.13569","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:b781200f77fc5837c1dd3eb165ae4c47c60481c477cca0680dee314ca46f5564","target":"record","created_at":"2026-07-05T08:23:57Z","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":"9c05fc75b5a8c3f66a64fe2757aca1db0f1ee1eff81612463281a613e02e4f15","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-11-13T12:24:54Z","title_canon_sha256":"d8784d4752241135e8cebc60a995c3667c49ee228b063c50d4acbda4a89d8397"},"schema_version":"1.0","source":{"id":"2311.13569","kind":"arxiv","version":2}},"canonical_sha256":"328115302fcc611e0865cece69dd5f8e18d9f22480dfeefa50bffbf9a5d9e346","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"328115302fcc611e0865cece69dd5f8e18d9f22480dfeefa50bffbf9a5d9e346","first_computed_at":"2026-07-05T08:23:57.677116Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:23:57.677116Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"9V9gCUjel1A7p4H0ryCbXNADaqcSkZ8Pg8LkZwCZg22H+vOGEGjZpVqzp695WmDM/DESCzzkzw0pl/xYUPiyBg==","signature_status":"signed_v1","signed_at":"2026-07-05T08:23:57.677630Z","signed_message":"canonical_sha256_bytes"},"source_id":"2311.13569","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b781200f77fc5837c1dd3eb165ae4c47c60481c477cca0680dee314ca46f5564","sha256:5979e41f18f422b85c3c3ade04619b2bcc2851a62165151903d25b4e7a96ce0b"],"state_sha256":"d18b11c42f8a3813b5733f9c37142ddd0e0f6050ff22e647f66ef200db5d9e69"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"p/WZlv/jqJeQ1T8wk9RcdbLDla2nxPUKXkjq2cxGHtFRyC9UJrH3CQxtVwg/EzNml59taE7Rx0BeALc+XoBRBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T07:57:22.767635Z","bundle_sha256":"ff71cb29e32d7249d45d923e21b663e3787424f30e4cacfa5f040fb7fa1d1ebf"}}