{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:L2KT4KH7ZMCRHRHS6WYFMCLYOC","short_pith_number":"pith:L2KT4KH7","schema_version":"1.0","canonical_sha256":"5e953e28ffcb0513c4f2f5b056097870a9f7581c9ae2723e6db07fa0ccd52a87","source":{"kind":"arxiv","id":"2312.01150","version":4},"attestation_state":"computed","paper":{"title":"Pointer Networks Trained Better via Evolutionary Algorithms","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.NE","authors_text":"Bingdong Li, Haobo Fu, Ke Tang, Muyao Zhong, Peng Yang, Shengcai Liu","submitted_at":"2023-12-02T14:38:58Z","abstract_excerpt":"Pointer Network (PtrNet) is a specific neural network for solving Combinatorial Optimization Problems (COPs). While PtrNets offer real-time feed-forward inference for complex COPs instances, its quality of the results tends to be less satisfactory. One possible reason is that such issue suffers from the lack of global search ability of the gradient descent, which is frequently employed in traditional PtrNet training methods including both supervised learning and reinforcement learning. To improve the performance of PtrNet, this paper delves deeply into the advantages of training PtrNet with Ev"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2312.01150","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2023-12-02T14:38:58Z","cross_cats_sorted":[],"title_canon_sha256":"ae0687d44d087235f29d0de560a5c97d0530be293d70095f1cdf6eed7a9a6941","abstract_canon_sha256":"a61aa2088c9a63368923af048628c44be8611502667461c1a7358adbcf06e445"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:54:34.598723Z","signature_b64":"8xXG/y9ZiiX5NaLtaGGC+so5D3xc/ZipJHoxLtP93kKhzdK7TkID3hfwkVnrYFgMCktSrIUTjgamxCBldrlKDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5e953e28ffcb0513c4f2f5b056097870a9f7581c9ae2723e6db07fa0ccd52a87","last_reissued_at":"2026-07-05T07:54:34.598212Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:54:34.598212Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Pointer Networks Trained Better via Evolutionary Algorithms","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.NE","authors_text":"Bingdong Li, Haobo Fu, Ke Tang, Muyao Zhong, Peng Yang, Shengcai Liu","submitted_at":"2023-12-02T14:38:58Z","abstract_excerpt":"Pointer Network (PtrNet) is a specific neural network for solving Combinatorial Optimization Problems (COPs). While PtrNets offer real-time feed-forward inference for complex COPs instances, its quality of the results tends to be less satisfactory. One possible reason is that such issue suffers from the lack of global search ability of the gradient descent, which is frequently employed in traditional PtrNet training methods including both supervised learning and reinforcement learning. To improve the performance of PtrNet, this paper delves deeply into the advantages of training PtrNet with Ev"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2312.01150","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2312.01150/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2312.01150","created_at":"2026-07-05T07:54:34.598275+00:00"},{"alias_kind":"arxiv_version","alias_value":"2312.01150v4","created_at":"2026-07-05T07:54:34.598275+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2312.01150","created_at":"2026-07-05T07:54:34.598275+00:00"},{"alias_kind":"pith_short_12","alias_value":"L2KT4KH7ZMCR","created_at":"2026-07-05T07:54:34.598275+00:00"},{"alias_kind":"pith_short_16","alias_value":"L2KT4KH7ZMCRHRHS","created_at":"2026-07-05T07:54:34.598275+00:00"},{"alias_kind":"pith_short_8","alias_value":"L2KT4KH7","created_at":"2026-07-05T07:54:34.598275+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/L2KT4KH7ZMCRHRHS6WYFMCLYOC","json":"https://pith.science/pith/L2KT4KH7ZMCRHRHS6WYFMCLYOC.json","graph_json":"https://pith.science/api/pith-number/L2KT4KH7ZMCRHRHS6WYFMCLYOC/graph.json","events_json":"https://pith.science/api/pith-number/L2KT4KH7ZMCRHRHS6WYFMCLYOC/events.json","paper":"https://pith.science/paper/L2KT4KH7"},"agent_actions":{"view_html":"https://pith.science/pith/L2KT4KH7ZMCRHRHS6WYFMCLYOC","download_json":"https://pith.science/pith/L2KT4KH7ZMCRHRHS6WYFMCLYOC.json","view_paper":"https://pith.science/paper/L2KT4KH7","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2312.01150&json=true","fetch_graph":"https://pith.science/api/pith-number/L2KT4KH7ZMCRHRHS6WYFMCLYOC/graph.json","fetch_events":"https://pith.science/api/pith-number/L2KT4KH7ZMCRHRHS6WYFMCLYOC/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/L2KT4KH7ZMCRHRHS6WYFMCLYOC/action/timestamp_anchor","attest_storage":"https://pith.science/pith/L2KT4KH7ZMCRHRHS6WYFMCLYOC/action/storage_attestation","attest_author":"https://pith.science/pith/L2KT4KH7ZMCRHRHS6WYFMCLYOC/action/author_attestation","sign_citation":"https://pith.science/pith/L2KT4KH7ZMCRHRHS6WYFMCLYOC/action/citation_signature","submit_replication":"https://pith.science/pith/L2KT4KH7ZMCRHRHS6WYFMCLYOC/action/replication_record"}},"created_at":"2026-07-05T07:54:34.598275+00:00","updated_at":"2026-07-05T07:54:34.598275+00:00"}