{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:OVJ3SOYNI7IWLJ65RSA5VPLCOF","short_pith_number":"pith:OVJ3SOYN","canonical_record":{"source":{"id":"1905.11623","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-05-28T06:04:25Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"971195d468472685dc2f7e4598c07e9fda6b624a664f4b1f0292238fe188d3f8","abstract_canon_sha256":"39d44d29acf71e3c63ed004b33d4628725aada7b9e91bcd590ce0698508f8b36"},"schema_version":"1.0"},"canonical_sha256":"7553b93b0d47d165a7dd8c81dabd62714238afa128d9544cb25684ae9867ce81","source":{"kind":"arxiv","id":"1905.11623","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1905.11623","created_at":"2026-07-05T00:46:13Z"},{"alias_kind":"arxiv_version","alias_value":"1905.11623v2","created_at":"2026-07-05T00:46:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1905.11623","created_at":"2026-07-05T00:46:13Z"},{"alias_kind":"pith_short_12","alias_value":"OVJ3SOYNI7IW","created_at":"2026-07-05T00:46:13Z"},{"alias_kind":"pith_short_16","alias_value":"OVJ3SOYNI7IWLJ65","created_at":"2026-07-05T00:46:13Z"},{"alias_kind":"pith_short_8","alias_value":"OVJ3SOYN","created_at":"2026-07-05T00:46:13Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:OVJ3SOYNI7IWLJ65RSA5VPLCOF","target":"record","payload":{"canonical_record":{"source":{"id":"1905.11623","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-05-28T06:04:25Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"971195d468472685dc2f7e4598c07e9fda6b624a664f4b1f0292238fe188d3f8","abstract_canon_sha256":"39d44d29acf71e3c63ed004b33d4628725aada7b9e91bcd590ce0698508f8b36"},"schema_version":"1.0"},"canonical_sha256":"7553b93b0d47d165a7dd8c81dabd62714238afa128d9544cb25684ae9867ce81","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:46:13.224653Z","signature_b64":"MoKySgFaFI2scux5tzAzpVGDUttT9k5N7id7XXHNfUDKdbLtjUzALIl/1E/CV8cZFJ7HHt+PiGdky+VCJDmAAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7553b93b0d47d165a7dd8c81dabd62714238afa128d9544cb25684ae9867ce81","last_reissued_at":"2026-07-05T00:46:13.224178Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:46:13.224178Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1905.11623","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":"2026-07-05T00:46:13Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BK2PByoHd3G+XAxIX3lsz3gt2J4gfcp1a4Lap2BLwQRObrKR/4McBraqLLNe/jsDfT0JTWNQjaS+GbZSggvOBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T15:47:39.762837Z"},"content_sha256":"6dcfd9d47de95a0878aa9cb0f75d6226c0a74a9bb89672477aeec80d2f7cba62","schema_version":"1.0","event_id":"sha256:6dcfd9d47de95a0878aa9cb0f75d6226c0a74a9bb89672477aeec80d2f7cba62"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:OVJ3SOYNI7IWLJ65RSA5VPLCOF","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Solving NP-Hard Problems on Graphs with Extended AlphaGo Zero","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Issei Sato, Kenshin Abe, Masashi Sugiyama, Zijian Xu","submitted_at":"2019-05-28T06:04:25Z","abstract_excerpt":"There have been increasing challenges to solve combinatorial optimization problems by machine learning. Khalil et al. proposed an end-to-end reinforcement learning framework, S2V-DQN, which automatically learns graph embeddings to construct solutions to a wide range of problems. To improve the generalization ability of their Q-learning method, we propose a novel learning strategy based on AlphaGo Zero which is a Go engine that achieved a superhuman level without the domain knowledge of the game. Our framework is redesigned for combinatorial problems, where the final reward might take any real "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1905.11623","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/1905.11623/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":"2026-07-05T00:46:13Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xVocqjLGhxCei0Ykk0h6w43L+CdBh0mZFN+O3pEnS8mJtcjSdbXRfw3qZLJ1AatSB0Gha9+6SGbJM/LAcI07DQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T15:47:39.763209Z"},"content_sha256":"efb4b751ab24e811f57fb482692cf7a5197a1bbd1cd8e8e44e4c48bdee728436","schema_version":"1.0","event_id":"sha256:efb4b751ab24e811f57fb482692cf7a5197a1bbd1cd8e8e44e4c48bdee728436"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/OVJ3SOYNI7IWLJ65RSA5VPLCOF/bundle.json","state_url":"https://pith.science/pith/OVJ3SOYNI7IWLJ65RSA5VPLCOF/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/OVJ3SOYNI7IWLJ65RSA5VPLCOF/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":"2026-07-06T15:47:39Z","links":{"resolver":"https://pith.science/pith/OVJ3SOYNI7IWLJ65RSA5VPLCOF","bundle":"https://pith.science/pith/OVJ3SOYNI7IWLJ65RSA5VPLCOF/bundle.json","state":"https://pith.science/pith/OVJ3SOYNI7IWLJ65RSA5VPLCOF/state.json","well_known_bundle":"https://pith.science/.well-known/pith/OVJ3SOYNI7IWLJ65RSA5VPLCOF/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:OVJ3SOYNI7IWLJ65RSA5VPLCOF","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":"39d44d29acf71e3c63ed004b33d4628725aada7b9e91bcd590ce0698508f8b36","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-05-28T06:04:25Z","title_canon_sha256":"971195d468472685dc2f7e4598c07e9fda6b624a664f4b1f0292238fe188d3f8"},"schema_version":"1.0","source":{"id":"1905.11623","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1905.11623","created_at":"2026-07-05T00:46:13Z"},{"alias_kind":"arxiv_version","alias_value":"1905.11623v2","created_at":"2026-07-05T00:46:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1905.11623","created_at":"2026-07-05T00:46:13Z"},{"alias_kind":"pith_short_12","alias_value":"OVJ3SOYNI7IW","created_at":"2026-07-05T00:46:13Z"},{"alias_kind":"pith_short_16","alias_value":"OVJ3SOYNI7IWLJ65","created_at":"2026-07-05T00:46:13Z"},{"alias_kind":"pith_short_8","alias_value":"OVJ3SOYN","created_at":"2026-07-05T00:46:13Z"}],"graph_snapshots":[{"event_id":"sha256:efb4b751ab24e811f57fb482692cf7a5197a1bbd1cd8e8e44e4c48bdee728436","target":"graph","created_at":"2026-07-05T00:46:13Z","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/1905.11623/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"There have been increasing challenges to solve combinatorial optimization problems by machine learning. Khalil et al. proposed an end-to-end reinforcement learning framework, S2V-DQN, which automatically learns graph embeddings to construct solutions to a wide range of problems. To improve the generalization ability of their Q-learning method, we propose a novel learning strategy based on AlphaGo Zero which is a Go engine that achieved a superhuman level without the domain knowledge of the game. Our framework is redesigned for combinatorial problems, where the final reward might take any real ","authors_text":"Issei Sato, Kenshin Abe, Masashi Sugiyama, Zijian Xu","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-05-28T06:04:25Z","title":"Solving NP-Hard Problems on Graphs with Extended AlphaGo Zero"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1905.11623","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":"sha256:6dcfd9d47de95a0878aa9cb0f75d6226c0a74a9bb89672477aeec80d2f7cba62","target":"record","created_at":"2026-07-05T00:46:13Z","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":"39d44d29acf71e3c63ed004b33d4628725aada7b9e91bcd590ce0698508f8b36","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-05-28T06:04:25Z","title_canon_sha256":"971195d468472685dc2f7e4598c07e9fda6b624a664f4b1f0292238fe188d3f8"},"schema_version":"1.0","source":{"id":"1905.11623","kind":"arxiv","version":2}},"canonical_sha256":"7553b93b0d47d165a7dd8c81dabd62714238afa128d9544cb25684ae9867ce81","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7553b93b0d47d165a7dd8c81dabd62714238afa128d9544cb25684ae9867ce81","first_computed_at":"2026-07-05T00:46:13.224178Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:46:13.224178Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"MoKySgFaFI2scux5tzAzpVGDUttT9k5N7id7XXHNfUDKdbLtjUzALIl/1E/CV8cZFJ7HHt+PiGdky+VCJDmAAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T00:46:13.224653Z","signed_message":"canonical_sha256_bytes"},"source_id":"1905.11623","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6dcfd9d47de95a0878aa9cb0f75d6226c0a74a9bb89672477aeec80d2f7cba62","sha256:efb4b751ab24e811f57fb482692cf7a5197a1bbd1cd8e8e44e4c48bdee728436"],"state_sha256":"352a4041f72c888ea61deefcee4f0c1573b116527b482dd444ea6719acdd02f5"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Q+aSBZcD1l2kv3+l3a/engBe9Lzr6sjvRbQ6QL1hbQ8r9AnkVi5jy62EVlMBq5VERpek7lfWDCM1WQMyFVGJDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T15:47:39.765283Z","bundle_sha256":"9f904e5297ba9ebd5ff8fbe1df010afc725978b42a6e2e307cdd464b81104561"}}