{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:RJV2PFI35EZFBOUTOABJ3FPOD3","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":"babc5a8a297d417a532f41f887dcfdeff0db21aa98e2eca94fc62954da6c983a","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-03-28T16:46:53Z","title_canon_sha256":"14072cc5dd072788012bda8773e63cb0c74cf266d3c0da81023f2969c3fcdb72"},"schema_version":"1.0","source":{"id":"2403.19561","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.19561","created_at":"2026-07-05T08:14:22Z"},{"alias_kind":"arxiv_version","alias_value":"2403.19561v3","created_at":"2026-07-05T08:14:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.19561","created_at":"2026-07-05T08:14:22Z"},{"alias_kind":"pith_short_12","alias_value":"RJV2PFI35EZF","created_at":"2026-07-05T08:14:22Z"},{"alias_kind":"pith_short_16","alias_value":"RJV2PFI35EZFBOUT","created_at":"2026-07-05T08:14:22Z"},{"alias_kind":"pith_short_8","alias_value":"RJV2PFI3","created_at":"2026-07-05T08:14:22Z"}],"graph_snapshots":[{"event_id":"sha256:4eae4a8e64aaf5b4319779fccec8c0061be0e2054404732a7520cd45726eb6b8","target":"graph","created_at":"2026-07-05T08:14:22Z","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/2403.19561/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The end-to-end neural combinatorial optimization (NCO) method shows promising performance in solving complex combinatorial optimization problems without the need for expert design. However, existing methods struggle with large-scale problems, hindering their practical applicability. To overcome this limitation, this work proposes a novel Self-Improved Learning (SIL) method for better scalability of neural combinatorial optimization. Specifically, we develop an efficient self-improved mechanism that enables direct model training on large-scale problem instances without any labeled data. Powered","authors_text":"Fu Luo, Mingxuan Yuan, Qingfu Zhang, Xialiang Tong, Xi Lin, Zhenkun Wang","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-03-28T16:46:53Z","title":"Self-Improved Learning for Scalable Neural Combinatorial Optimization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.19561","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:fe63f5123c234daab85dc60478be441ab6889ad86a14c744f89011d52694279b","target":"record","created_at":"2026-07-05T08:14:22Z","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":"babc5a8a297d417a532f41f887dcfdeff0db21aa98e2eca94fc62954da6c983a","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-03-28T16:46:53Z","title_canon_sha256":"14072cc5dd072788012bda8773e63cb0c74cf266d3c0da81023f2969c3fcdb72"},"schema_version":"1.0","source":{"id":"2403.19561","kind":"arxiv","version":3}},"canonical_sha256":"8a6ba7951be93250ba9370029d95ee1eedc60d48dc0005572555a21920d141be","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8a6ba7951be93250ba9370029d95ee1eedc60d48dc0005572555a21920d141be","first_computed_at":"2026-07-05T08:14:22.947343Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:14:22.947343Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"gPQTzMKBZ2bssoa5lmXX7MxenHG13Ivqz3TFcYII6pWGDIfUEZilNYLExHJ7s7Uv6Cz4p9XMw5KSzo0a4UmnAw==","signature_status":"signed_v1","signed_at":"2026-07-05T08:14:22.947866Z","signed_message":"canonical_sha256_bytes"},"source_id":"2403.19561","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:fe63f5123c234daab85dc60478be441ab6889ad86a14c744f89011d52694279b","sha256:4eae4a8e64aaf5b4319779fccec8c0061be0e2054404732a7520cd45726eb6b8"],"state_sha256":"c38f4ec8928f969184135b17bc9d29a91b87ce65983072282949f16a7252e835"}