{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:UFFLJPPZXHN2JYVKGYDSVM54MD","short_pith_number":"pith:UFFLJPPZ","canonical_record":{"source":{"id":"1704.01665","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-04-05T23:08:07Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"c003a31abd2285e3a61e8de56a1bb7f60580297222e01a62a6185bf657a43f67","abstract_canon_sha256":"3b3d92c9b13a98e32975444a1ca01e9bed9ba5f5a2496a3f49cefa24eca263c9"},"schema_version":"1.0"},"canonical_sha256":"a14ab4bdf9b9dba4e2aa36072ab3bc60fd77e0922e81a2feb4403bae780f6edc","source":{"kind":"arxiv","id":"1704.01665","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1704.01665","created_at":"2026-05-18T00:22:49Z"},{"alias_kind":"arxiv_version","alias_value":"1704.01665v4","created_at":"2026-05-18T00:22:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1704.01665","created_at":"2026-05-18T00:22:49Z"},{"alias_kind":"pith_short_12","alias_value":"UFFLJPPZXHN2","created_at":"2026-05-18T12:31:46Z"},{"alias_kind":"pith_short_16","alias_value":"UFFLJPPZXHN2JYVK","created_at":"2026-05-18T12:31:46Z"},{"alias_kind":"pith_short_8","alias_value":"UFFLJPPZ","created_at":"2026-05-18T12:31:46Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:UFFLJPPZXHN2JYVKGYDSVM54MD","target":"record","payload":{"canonical_record":{"source":{"id":"1704.01665","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-04-05T23:08:07Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"c003a31abd2285e3a61e8de56a1bb7f60580297222e01a62a6185bf657a43f67","abstract_canon_sha256":"3b3d92c9b13a98e32975444a1ca01e9bed9ba5f5a2496a3f49cefa24eca263c9"},"schema_version":"1.0"},"canonical_sha256":"a14ab4bdf9b9dba4e2aa36072ab3bc60fd77e0922e81a2feb4403bae780f6edc","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:22:49.345339Z","signature_b64":"MaEGoZ4wngp9YKVcWABsDZmOqs78EOpWLMxQ5Yvf/YWF20o6nkESBBcKr0qgDmgqupAhdv7spLe9cdW8oRRrBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a14ab4bdf9b9dba4e2aa36072ab3bc60fd77e0922e81a2feb4403bae780f6edc","last_reissued_at":"2026-05-18T00:22:49.344885Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:22:49.344885Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1704.01665","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:22:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6cOFSM4MZacqYP3GA/ioKhapfym+ft2waJsdhHfD+Hp5gOWGbKIAWljhxdeygw3DTa7nyr6QaVDxK2xiyHVFBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T13:17:25.510108Z"},"content_sha256":"48248b827004e1097cbb3231037ce4248b82fa0677c7583195b6bb0c4a4619c4","schema_version":"1.0","event_id":"sha256:48248b827004e1097cbb3231037ce4248b82fa0677c7583195b6bb0c4a4619c4"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:UFFLJPPZXHN2JYVKGYDSVM54MD","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Learning Combinatorial Optimization Algorithms over Graphs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Bistra Dilkina, Elias B. Khalil, Hanjun Dai, Le Song, Yuyu Zhang","submitted_at":"2017-04-05T23:08:07Z","abstract_excerpt":"The design of good heuristics or approximation algorithms for NP-hard combinatorial optimization problems often requires significant specialized knowledge and trial-and-error. Can we automate this challenging, tedious process, and learn the algorithms instead? In many real-world applications, it is typically the case that the same optimization problem is solved again and again on a regular basis, maintaining the same problem structure but differing in the data. This provides an opportunity for learning heuristic algorithms that exploit the structure of such recurring problems. In this paper, w"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1704.01665","kind":"arxiv","version":4},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"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":"2026-05-18T00:22:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"el18/SzPxfUn0KXqkLKsQn/1MZM/WTIhmvZ6kbC4SYrxyoQIGpmQUFsfVWQiIz8ZYCw99EPTzQ09O5f1atZeBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T13:17:25.510753Z"},"content_sha256":"040bfd4e6b77c86d1c5b74ace8935b6ed7d37e40f404884e9aae4de4485dbdda","schema_version":"1.0","event_id":"sha256:040bfd4e6b77c86d1c5b74ace8935b6ed7d37e40f404884e9aae4de4485dbdda"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/UFFLJPPZXHN2JYVKGYDSVM54MD/bundle.json","state_url":"https://pith.science/pith/UFFLJPPZXHN2JYVKGYDSVM54MD/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/UFFLJPPZXHN2JYVKGYDSVM54MD/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":"2026-05-27T13:17:25Z","links":{"resolver":"https://pith.science/pith/UFFLJPPZXHN2JYVKGYDSVM54MD","bundle":"https://pith.science/pith/UFFLJPPZXHN2JYVKGYDSVM54MD/bundle.json","state":"https://pith.science/pith/UFFLJPPZXHN2JYVKGYDSVM54MD/state.json","well_known_bundle":"https://pith.science/.well-known/pith/UFFLJPPZXHN2JYVKGYDSVM54MD/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:UFFLJPPZXHN2JYVKGYDSVM54MD","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":"3b3d92c9b13a98e32975444a1ca01e9bed9ba5f5a2496a3f49cefa24eca263c9","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-04-05T23:08:07Z","title_canon_sha256":"c003a31abd2285e3a61e8de56a1bb7f60580297222e01a62a6185bf657a43f67"},"schema_version":"1.0","source":{"id":"1704.01665","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1704.01665","created_at":"2026-05-18T00:22:49Z"},{"alias_kind":"arxiv_version","alias_value":"1704.01665v4","created_at":"2026-05-18T00:22:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1704.01665","created_at":"2026-05-18T00:22:49Z"},{"alias_kind":"pith_short_12","alias_value":"UFFLJPPZXHN2","created_at":"2026-05-18T12:31:46Z"},{"alias_kind":"pith_short_16","alias_value":"UFFLJPPZXHN2JYVK","created_at":"2026-05-18T12:31:46Z"},{"alias_kind":"pith_short_8","alias_value":"UFFLJPPZ","created_at":"2026-05-18T12:31:46Z"}],"graph_snapshots":[{"event_id":"sha256:040bfd4e6b77c86d1c5b74ace8935b6ed7d37e40f404884e9aae4de4485dbdda","target":"graph","created_at":"2026-05-18T00:22:49Z","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"},"paper":{"abstract_excerpt":"The design of good heuristics or approximation algorithms for NP-hard combinatorial optimization problems often requires significant specialized knowledge and trial-and-error. Can we automate this challenging, tedious process, and learn the algorithms instead? In many real-world applications, it is typically the case that the same optimization problem is solved again and again on a regular basis, maintaining the same problem structure but differing in the data. This provides an opportunity for learning heuristic algorithms that exploit the structure of such recurring problems. In this paper, w","authors_text":"Bistra Dilkina, Elias B. Khalil, Hanjun Dai, Le Song, Yuyu Zhang","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-04-05T23:08:07Z","title":"Learning Combinatorial Optimization Algorithms over Graphs"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1704.01665","kind":"arxiv","version":4},"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":"sha256:48248b827004e1097cbb3231037ce4248b82fa0677c7583195b6bb0c4a4619c4","target":"record","created_at":"2026-05-18T00:22:49Z","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":"3b3d92c9b13a98e32975444a1ca01e9bed9ba5f5a2496a3f49cefa24eca263c9","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-04-05T23:08:07Z","title_canon_sha256":"c003a31abd2285e3a61e8de56a1bb7f60580297222e01a62a6185bf657a43f67"},"schema_version":"1.0","source":{"id":"1704.01665","kind":"arxiv","version":4}},"canonical_sha256":"a14ab4bdf9b9dba4e2aa36072ab3bc60fd77e0922e81a2feb4403bae780f6edc","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a14ab4bdf9b9dba4e2aa36072ab3bc60fd77e0922e81a2feb4403bae780f6edc","first_computed_at":"2026-05-18T00:22:49.344885Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:22:49.344885Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"MaEGoZ4wngp9YKVcWABsDZmOqs78EOpWLMxQ5Yvf/YWF20o6nkESBBcKr0qgDmgqupAhdv7spLe9cdW8oRRrBw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:22:49.345339Z","signed_message":"canonical_sha256_bytes"},"source_id":"1704.01665","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:48248b827004e1097cbb3231037ce4248b82fa0677c7583195b6bb0c4a4619c4","sha256:040bfd4e6b77c86d1c5b74ace8935b6ed7d37e40f404884e9aae4de4485dbdda"],"state_sha256":"b2de0f6c6928fcb53f4b45ac3ebdfa00a9139097f5e03e51785cb3426f10860d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KK9xc+yhwGTDDXpoIGO/xrogBsTsKGtAiJF+iHa5AkGfmteOvEIklPyhIv46ergXmDYM2xt931326OkLwA/HCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-27T13:17:25.514204Z","bundle_sha256":"f9903ba76dc3c55ca1ab1fa56bfaaa066079a04bdafcb9acd8e8299b0896f69d"}}