{"as_of":"2026-08-19T07:40:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:c0dace37b0ed4d439c8fb959f6a76183ab31065926bf036813b3d189abb08021","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":"2026-08-19T06:32:44.657259+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":"2026-08-11T12:47:55.012740Z","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":"2026-07-01T22:36:17.190952Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2405.01906","last_updated":"2026-06-28T14:19:00Z","snapshot_observed_at":"2026-08-16T13:55:43.357953Z","submitted_at":"2024-05-03T08:00:19Z","title":"Instance-Conditioned Adaptation for Large-scale Generalization of Neural Routing Solver","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.01906","snapshot_observed_at":"2026-08-11T12:47:55.012740Z","title":"& Zhang, Q","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.13858","last_updated":"2026-06-08T07:38:07Z","snapshot_observed_at":"2026-08-18T21:22:10.338619Z","submitted_at":"2024-12-18T13:52:50Z","title":"IDEQ -- Improving Diffusion Models for the Traveling Salesman Problem (TSP) by Leveraging the Structure of the Solution Space","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-11T12:47:55.012740Z"},"links":{"cited_paper":"/paper/2405.01906","citing_paper":"/paper/2412.13858"},"observation_digest":"sha256:f9757bcdb00209d1b4c3aa84cb3eb61b6f728c48534d80639c48ec510c61498c","observation_id":"a158c5fd-bddd-4921-934c-4aa7b09c23c8","resolution":{"observed_at":"2026-08-11T12:47:55.012740Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.01906","last_updated":"2026-06-28T14:19:00Z","snapshot_observed_at":"2026-08-16T13:55:43.357953Z","submitted_at":"2024-05-03T08:00:19Z","title":"Instance-Conditioned Adaptation for Large-scale Generalization of Neural Routing Solver","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.01906","snapshot_observed_at":"2026-08-07T06:00:42.215927Z","title":", author Lin, X","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.06634","last_updated":"2025-06-07T03:00:05Z","snapshot_observed_at":"2026-08-14T07:35:24.265012Z","submitted_at":"2025-06-07T03:00:05Z","title":"GELD: A Unified Neural Model for Efficiently Solving Traveling Salesman Problems Across Different Scales","version":1},"reference_index":58,"source":"arxiv_source","source_observed_at":"2026-08-07T06:00:42.215927Z"},"links":{"cited_paper":"/paper/2405.01906","citing_paper":"/paper/2506.06634"},"observation_digest":"sha256:1a862d723b165eeab335d374aa3fb15cd7f3e8a4fb881214229f9781ac1c6ec6","observation_id":"29b4d384-fb40-4eef-b02d-2c070d405636","resolution":{"observed_at":"2026-08-07T06:00:42.215927Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.01906","last_updated":"2026-06-28T14:19:00Z","snapshot_observed_at":"2026-08-16T13:55:43.357953Z","submitted_at":"2024-05-03T08:00:19Z","title":"Instance-Conditioned Adaptation for Large-scale Generalization of Neural Routing Solver","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.01906","snapshot_observed_at":"2026-08-04T14:51:25.220183Z","title":"Instance-conditioned adaptation for large-scale generalization of neural routing solver","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.23413","last_updated":"2026-08-11T17:09:30Z","snapshot_observed_at":"2026-08-16T17:46:42.769294Z","submitted_at":"2025-09-27T17:11:09Z","title":"URS: A Unified Neural Routing Solver for Cross-Problem Zero-Shot Generalization","version":2},"reference_index":64,"source":"arxiv_source","source_observed_at":"2026-08-04T14:51:25.220183Z"},"links":{"cited_paper":"/paper/2405.01906","citing_paper":"/paper/2509.23413"},"observation_digest":"sha256:262e047e9cc190bf513d9d428246ab358e40b02c5a06f38409bfb89e7704f36e","observation_id":"680f7d34-c441-45ad-a6ad-2644958eb77f","resolution":{"observed_at":"2026-08-04T14:51:25.220183Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.01906","last_updated":"2026-06-28T14:19:00Z","snapshot_observed_at":"2026-08-16T13:55:43.357953Z","submitted_at":"2024-05-03T08:00:19Z","title":"Instance-Conditioned Adaptation for Large-scale Generalization of Neural Routing Solver","version":3},"cited_work":{"arxiv_id":"2405.01906","doi":null,"metadata_source":"pith","pith_arxiv_id":"2405.01906","snapshot_observed_at":"2026-07-01T22:36:17.190952Z","title":"Instance-Conditioned Adaptation for Large-scale Generalization of Neural Routing Solver","venue":"cs.AI","work_id":"ae4adfa5-70af-4079-82fd-f0ba81586ee0","year":2024},"citing_paper":{"arxiv_id":"2606.02136","last_updated":"2026-06-01T12:03:59Z","snapshot_observed_at":"2026-08-18T07:57:24.380735Z","submitted_at":"2026-06-01T12:03:59Z","title":"Edge-aware Decoding for Neural Asymmetric Routing","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-06-28T15:15:25.470560Z"},"links":{"cited_paper":"/paper/2405.01906","citing_paper":"/paper/2606.02136"},"observation_digest":"sha256:1aaabe626c420fa859378bb2dec45cbcd774ba4cc9f3f593b1ae6fea78011509","observation_id":"ac24cc2f-b54a-420f-8dc1-13dad364d276","resolution":{"observed_at":"2026-07-01T22:36:17.192536Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2405.01906/citation-record","integrity":"/paper/2405.01906/integrity","json":"/paper/2405.01906/citation-record.json","paper":"/paper/2405.01906"},"outbound":[],"paper":{"arxiv_id":"2405.01906","last_updated":"2026-06-28T14:19:00Z","latest_version":3,"primary_category":"cs.AI","snapshot_observed_at":"2026-08-16T13:55:43.357953Z","submitted_at":"2024-05-03T08:00:19Z","title":"Instance-Conditioned Adaptation for Large-scale Generalization of Neural Routing Solver"},"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":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"thesis":"As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2405.01906."}