{"as_of":"2026-08-15T13:47:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:d90eb757e92b31982dcfe38ea8f20ae47498ca906b743870282da94b318ba9d9","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":4,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":4,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-15T06:32:42.880941+00:00","state":"measured"},{"denominator":4,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":4,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T20:59:08.464091Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-12T04:48:09.620840Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1911.04936","last_updated":"2019-11-12T15:39:21Z","snapshot_observed_at":"2026-07-06T08:36:24.990567Z","submitted_at":"2019-11-12T15:39:21Z","title":"Combinatorial Optimization by Graph Pointer Networks and Hierarchical Reinforcement Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1911.04936","snapshot_observed_at":"2026-08-12T20:59:08.464091Z","title":"Combinatorial opti- mization by graph pointer networks and hierarchical reinforcement learning","venue":null,"work_id":null,"year":1911},"citing_paper":{"arxiv_id":"2411.09238","last_updated":"2025-05-16T07:31:51Z","snapshot_observed_at":"2026-08-12T20:49:53.368493Z","submitted_at":"2024-11-14T07:13:08Z","title":"Beyond the Heatmap: A Rigorous Evaluation of Component Impact in MCTS-Based TSP Solvers","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-12T20:59:08.464091Z"},"links":{"cited_paper":"/paper/1911.04936","citing_paper":"/paper/2411.09238"},"observation_digest":"sha256:4456c8edfbeb1ee437c56e81eb4dec0c4afeb0034d15ff7fa4bd7385ebe406dd","observation_id":"6739ac9f-30b6-4037-860c-b3135aea0171","resolution":{"observed_at":"2026-08-12T20:59:08.464091Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1911.04936","last_updated":"2019-11-12T15:39:21Z","snapshot_observed_at":"2026-07-06T08:36:24.990567Z","submitted_at":"2019-11-12T15:39:21Z","title":"Combinatorial Optimization by Graph Pointer Networks and Hierarchical Reinforcement Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1911.04936","snapshot_observed_at":"2026-08-12T10:28:09.782242Z","title":"Combinatorial opti- mization by graph pointer networks and hierarchical reinforcement learning","venue":null,"work_id":null,"year":1911},"citing_paper":{"arxiv_id":"2411.19285","last_updated":"2024-12-30T03:25:23Z","snapshot_observed_at":"2026-08-14T22:25:30.765266Z","submitted_at":"2024-11-28T17:31:15Z","title":"BPQP: A Differentiable Convex Optimization Framework for Efficient End-to-End Learning","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-12T10:28:09.782242Z"},"links":{"cited_paper":"/paper/1911.04936","citing_paper":"/paper/2411.19285"},"observation_digest":"sha256:2700e5f0678d192ae66169698ae5a25380fde220a75d7b30fa09aa185238a989","observation_id":"2a4a682e-e25f-412b-b90a-1b4abe196fdd","resolution":{"observed_at":"2026-08-12T10:28:09.782242Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1911.04936","last_updated":"2019-11-12T15:39:21Z","snapshot_observed_at":"2026-07-06T08:36:24.990567Z","submitted_at":"2019-11-12T15:39:21Z","title":"Combinatorial Optimization by Graph Pointer Networks and Hierarchical Reinforcement Learning","version":1},"cited_work":{"arxiv_id":"1911.04936","doi":null,"metadata_source":"pith","pith_arxiv_id":"1911.04936","snapshot_observed_at":"2026-08-12T04:48:09.620840Z","title":"Combinatorial Optimization by Graph Pointer Networks and Hierarchical Reinforcement Learning","venue":"cs.LG","work_id":"ae6024bf-029a-49bd-9126-e42beea2786c","year":2019},"citing_paper":{"arxiv_id":"2412.01038","last_updated":"2024-12-02T01:43:46Z","snapshot_observed_at":"2026-08-14T09:50:49.534052Z","submitted_at":"2024-12-02T01:43:46Z","title":"Using Reinforcement Learning to Guide Graph State Generation for Photonic Quantum Computers","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-12T04:48:09.411389Z"},"links":{"cited_paper":"/paper/1911.04936","citing_paper":"/paper/2412.01038"},"observation_digest":"sha256:fdf006d335ec492614fb30a45eec4c47f83caf14d89b5c37c6c2821a54893867","observation_id":"12e83c14-6fb5-42a9-9f10-1408586ded25","resolution":{"observed_at":"2026-08-12T04:48:09.625176Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1911.04936","last_updated":"2019-11-12T15:39:21Z","snapshot_observed_at":"2026-07-06T08:36:24.990567Z","submitted_at":"2019-11-12T15:39:21Z","title":"Combinatorial Optimization by Graph Pointer Networks and Hierarchical Reinforcement Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1911.04936","snapshot_observed_at":"2026-07-31T01:52:58.913509Z","title":"arXiv preprint arXiv:1911.04936 , year=","venue":null,"work_id":null,"year":1911},"citing_paper":{"arxiv_id":"2607.25082","last_updated":"2026-07-29T02:00:40Z","snapshot_observed_at":"2026-08-08T10:30:37.919779Z","submitted_at":"2026-07-27T21:20:13Z","title":"PLATO: Pointer Learner for Agent and Task Openness","version":2},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-07-31T01:52:58.913509Z"},"links":{"cited_paper":"/paper/1911.04936","citing_paper":"/paper/2607.25082"},"observation_digest":"sha256:3f472ad6e6682d9d706c0122e72fc0693b21f77420d645469771cbfee386a743","observation_id":"3517046f-c9e6-4bd7-835e-e914cf08e85e","resolution":{"observed_at":"2026-07-31T01:52:58.913509Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/1911.04936/citation-record","integrity":"/paper/1911.04936/integrity","json":"/paper/1911.04936/citation-record.json","paper":"/paper/1911.04936"},"outbound":[],"paper":{"arxiv_id":"1911.04936","last_updated":"2019-11-12T15:39:21Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T08:36:24.990567Z","submitted_at":"2019-11-12T15:39:21Z","title":"Combinatorial Optimization by Graph Pointer Networks and Hierarchical Reinforcement Learning"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"thesis":"As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:1911.04936."}