{"as_of":"2026-08-08T18:19:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:0ee90eb9258815430335a9c7275316a5e331c9fcb82f69dc995eb5fd59bfc33a","coverage":[{"denominator":50,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":50,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T05:05:26.549203Z","state":"measured"},{"denominator":50,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":50,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2508.02510/citation-record","integrity":"/paper/2508.02510/integrity","json":"/paper/2508.02510/citation-record.json","paper":"/paper/2508.02510"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:05:30.815873Z","title":"Attention, filling in the gaps for generalization in routing problems","venue":null,"work_id":"daa90daa-2732-4e22-85c7-a86ba94fd3e3","year":2022},"citing_paper":{"arxiv_id":"2508.02510","last_updated":"2025-08-04T15:17:08Z","snapshot_observed_at":"2026-08-06T05:05:21.355196Z","submitted_at":"2025-08-04T15:17:08Z","title":"On Distributional Dependent Performance of Classical and Neural Routing Solvers","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T05:05:22.548848Z"},"links":{"citing_paper":"/paper/2508.02510"},"observation_digest":"sha256:7cd3468fe66c66ea793ed7ecd4b08d3c6188dfbafdcc6adafe8f50a0ddcf5ea0","observation_id":"6dab9385-362b-4b0e-81ce-91485929e3c4","resolution":{"observed_at":"2026-08-06T05:05:30.821583Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:05:30.795183Z","title":"Le, Mohammad Norouzi, and Samy Bengio","venue":null,"work_id":"5c054a17-a653-4acc-8453-2f529d3573b7","year":2017},"citing_paper":{"arxiv_id":"2508.02510","last_updated":"2025-08-04T15:17:08Z","snapshot_observed_at":"2026-08-06T05:05:21.355196Z","submitted_at":"2025-08-04T15:17:08Z","title":"On Distributional Dependent Performance of Classical and Neural Routing Solvers","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T05:05:22.618226Z"},"links":{"citing_paper":"/paper/2508.02510"},"observation_digest":"sha256:409834a367571cdaa5cacd7c74c2fcfbddf6d50cd8893849ba0819460c091d5f","observation_id":"abd3b694-001e-41cf-b811-8ec560d673df","resolution":{"observed_at":"2026-08-06T05:05:30.801510Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:05:22.683701Z","title":"Machine learning for combinatorial optimization: A methodological tour d’horizon","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2508.02510","last_updated":"2025-08-04T15:17:08Z","snapshot_observed_at":"2026-08-06T05:05:21.355196Z","submitted_at":"2025-08-04T15:17:08Z","title":"On Distributional Dependent Performance of Classical and Neural Routing Solvers","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T05:05:22.683701Z"},"links":{"citing_paper":"/paper/2508.02510"},"observation_digest":"sha256:93338904b8e93eedc99f79c125438b102b252cbae3682300cff53507993348ac","observation_id":"77171ea6-7f5a-4c6a-a93b-f07619ebbad3","resolution":{"observed_at":"2026-08-06T05:05:22.683701Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:05:30.775110Z","title":"RouteFinder: Towards Foundation Models for Vehicle Routing Problems, June 2024","venue":null,"work_id":"6b70cbc5-fabc-49d0-aebc-9fcd49293e1d","year":2024},"citing_paper":{"arxiv_id":"2508.02510","last_updated":"2025-08-04T15:17:08Z","snapshot_observed_at":"2026-08-06T05:05:21.355196Z","submitted_at":"2025-08-04T15:17:08Z","title":"On Distributional Dependent Performance of Classical and Neural Routing Solvers","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T05:05:22.786247Z"},"links":{"citing_paper":"/paper/2508.02510"},"observation_digest":"sha256:5936fdebc7ba8e0d45d1fe051a71f17491ac2998b47f30e652b6dff5497a7af8","observation_id":"6fca3fcb-9df3-47c3-91a3-078bc9f97d2c","resolution":{"observed_at":"2026-08-06T05:05:30.782807Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.07686","last_updated":"2023-01-19T15:27:33Z","snapshot_observed_at":"2026-08-06T21:41:30.278907Z","submitted_at":"2022-10-14T10:23:23Z","title":"Learning Generalizable Models for Vehicle Routing Problems via Knowledge Distillation","version":2},"cited_work":{"arxiv_id":"2210.07686","doi":null,"metadata_source":"pith","pith_arxiv_id":"2210.07686","snapshot_observed_at":"2026-08-06T05:05:27.537536Z","title":"Learning Generalizable Models for Vehicle Routing Problems via Knowledge Distillation","venue":"cs.LG","work_id":"ed77db65-b1b8-4692-8ad0-c4e749cee1d4","year":2022},"citing_paper":{"arxiv_id":"2508.02510","last_updated":"2025-08-04T15:17:08Z","snapshot_observed_at":"2026-08-06T05:05:21.355196Z","submitted_at":"2025-08-04T15:17:08Z","title":"On Distributional Dependent Performance of Classical and Neural Routing Solvers","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T05:05:22.882967Z"},"links":{"cited_paper":"/paper/2210.07686","citing_paper":"/paper/2508.02510"},"observation_digest":"sha256:e65bf94e57703bad6587fb3f20609c0ac9ff290f61fb9ccd5444c135ae17aff7","observation_id":"9051150d-00f7-4e59-a142-e3135d3abf06","resolution":{"observed_at":"2026-08-06T05:05:27.637253Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:05:30.756102Z","title":"Evolving diverse tsp instances by means of novel and creative mutation operators","venue":null,"work_id":"71d3ab64-633b-4d73-9517-f0d1923b4d0c","year":2019},"citing_paper":{"arxiv_id":"2508.02510","last_updated":"2025-08-04T15:17:08Z","snapshot_observed_at":"2026-08-06T05:05:21.355196Z","submitted_at":"2025-08-04T15:17:08Z","title":"On Distributional Dependent Performance of Classical and Neural Routing Solvers","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T05:05:22.954395Z"},"links":{"citing_paper":"/paper/2508.02510"},"observation_digest":"sha256:b3b171341961f625a14ab1ba9e3d48c22a968830a9ae136bb48e91428b1e127b","observation_id":"9a78767b-ebd4-441d-99c1-82c3ea1310c8","resolution":{"observed_at":"2026-08-06T05:05:30.761902Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:05:30.737367Z","title":"The Transformer Network for the Traveling Salesman Problem, March 2021","venue":null,"work_id":"44030734-c822-446e-88b4-9f2c94aabe75","year":2021},"citing_paper":{"arxiv_id":"2508.02510","last_updated":"2025-08-04T15:17:08Z","snapshot_observed_at":"2026-08-06T05:05:21.355196Z","submitted_at":"2025-08-04T15:17:08Z","title":"On Distributional Dependent Performance of Classical and Neural Routing Solvers","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T05:05:23.055584Z"},"links":{"citing_paper":"/paper/2508.02510"},"observation_digest":"sha256:e414e8f50c31542cef594bc85067bec4c72d46b94e90606a688e4b7e45bed512","observation_id":"ea591b05-795e-4b93-9f27-15f90e6dc824","resolution":{"observed_at":"2026-08-06T05:05:30.742524Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:05:30.717476Z","title":"Combinatorial Optimization with Policy Adaptation using Latent Space Search","venue":null,"work_id":"b3b06e82-2434-46b2-b178-b213b1207c03","year":2023},"citing_paper":{"arxiv_id":"2508.02510","last_updated":"2025-08-04T15:17:08Z","snapshot_observed_at":"2026-08-06T05:05:21.355196Z","submitted_at":"2025-08-04T15:17:08Z","title":"On Distributional Dependent Performance of Classical and Neural Routing Solvers","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T05:05:23.133925Z"},"links":{"citing_paper":"/paper/2508.02510"},"observation_digest":"sha256:52509a68523c3c386b32f6c2dbe13923f6afc2da7acf99f9e0fc1bd2d32a59a7","observation_id":"3ff6f570-3722-4aaf-8ec0-241630c771bb","resolution":{"observed_at":"2026-08-06T05:05:30.723126Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:05:23.205256Z","title":"Simulation-guided Beam Search for Neural Combinatorial Optimization","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2508.02510","last_updated":"2025-08-04T15:17:08Z","snapshot_observed_at":"2026-08-06T05:05:21.355196Z","submitted_at":"2025-08-04T15:17:08Z","title":"On Distributional Dependent Performance of Classical and Neural Routing Solvers","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T05:05:23.205256Z"},"links":{"citing_paper":"/paper/2508.02510"},"observation_digest":"sha256:5666ec381c160fb6814bde591d6d8df877612791fbe017a059af95cfb7d8c51c","observation_id":"fd4a9706-57ab-412b-834f-b35999c08a96","resolution":{"observed_at":"2026-08-06T05:05:23.205256Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/978-3-319-93031-2_12","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T11:07:33.414567Z","title":"Learning Heuristics for the TSP by Policy Gradient","venue":"Lecture notes in computer science","work_id":"ae4b07d8-83a3-43e9-a999-6d74208c7403","year":2018},"citing_paper":{"arxiv_id":"2508.02510","last_updated":"2025-08-04T15:17:08Z","snapshot_observed_at":"2026-08-06T05:05:21.355196Z","submitted_at":"2025-08-04T15:17:08Z","title":"On Distributional Dependent Performance of Classical and Neural Routing Solvers","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T05:05:23.298183Z"},"links":{"citing_paper":"/paper/2508.02510"},"observation_digest":"sha256:8f2532547220f7cd00f7f8a4bfdc3a725bb8ba3490fd4a22cb9f59062d0a5b56","observation_id":"2dc5f487-2f9b-46c9-abfc-d1e37484a461","resolution":{"observed_at":"2026-08-06T05:05:27.181834Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:05:30.687332Z","title":"BQ-NCO: Bisimulation Quotienting for Efficient Neural Combinatorial Optimization","venue":null,"work_id":"a8edadd2-e809-4070-9e18-02db7c4fe384","year":2023},"citing_paper":{"arxiv_id":"2508.02510","last_updated":"2025-08-04T15:17:08Z","snapshot_observed_at":"2026-08-06T05:05:21.355196Z","submitted_at":"2025-08-04T15:17:08Z","title":"On Distributional Dependent Performance of Classical and Neural Routing Solvers","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T05:05:23.386389Z"},"links":{"citing_paper":"/paper/2508.02510"},"observation_digest":"sha256:26dfb06d7eba874541fcb98e3c2142b150179733cacfedf08239b66397a18f6f","observation_id":"c626c519-dc7f-416c-b58d-7e5a588fa1fb","resolution":{"observed_at":"2026-08-06T05:05:30.694143Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2309.17089","last_updated":"2023-09-29T09:36:37Z","snapshot_observed_at":"2026-08-07T13:02:58.068201Z","submitted_at":"2023-09-29T09:36:37Z","title":"Too Big, so Fail? -- Enabling Neural Construction Methods to Solve Large-Scale Routing Problems","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.17089","snapshot_observed_at":"2026-08-06T05:05:23.481216Z","title":"Falkner and Lars Schmidt-Thieme","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2508.02510","last_updated":"2025-08-04T15:17:08Z","snapshot_observed_at":"2026-08-06T05:05:21.355196Z","submitted_at":"2025-08-04T15:17:08Z","title":"On Distributional Dependent Performance of Classical and Neural Routing Solvers","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T05:05:23.481216Z"},"links":{"cited_paper":"/paper/2309.17089","citing_paper":"/paper/2508.02510"},"observation_digest":"sha256:c400b2b17d3be3652274444def52ef3f14000e0e14dc707f4f90193d472ca833","observation_id":"b8062873-b87b-4bca-86ae-29ac4a6b4138","resolution":{"observed_at":"2026-08-06T05:05:23.481216Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:05:30.668041Z","title":"Learning to control local search for combinatorial optimization","venue":null,"work_id":"3824d287-946a-4821-a637-20ae13d77125","year":2022},"citing_paper":{"arxiv_id":"2508.02510","last_updated":"2025-08-04T15:17:08Z","snapshot_observed_at":"2026-08-06T05:05:21.355196Z","submitted_at":"2025-08-04T15:17:08Z","title":"On Distributional Dependent Performance of Classical and Neural Routing Solvers","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T05:05:23.545085Z"},"links":{"citing_paper":"/paper/2508.02510"},"observation_digest":"sha256:1b158499ea32ff819843c5b5a9e1f2c2362702478fde2286481d30b0495e6f37","observation_id":"2672ef13-9fa9-408a-93b8-174730a8b594","resolution":{"observed_at":"2026-08-06T05:05:30.674111Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:05:23.605407Z","title":"Generalize a Small Pre-trained Model to Arbitrarily Large TSP Instances","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2508.02510","last_updated":"2025-08-04T15:17:08Z","snapshot_observed_at":"2026-08-06T05:05:21.355196Z","submitted_at":"2025-08-04T15:17:08Z","title":"On Distributional Dependent Performance of Classical and Neural Routing Solvers","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T05:05:23.605407Z"},"links":{"citing_paper":"/paper/2508.02510"},"observation_digest":"sha256:b88fcab8e2ba380615c974c1176954c37f37aae6348d34cc2e2860d4920d3ec0","observation_id":"e9d2286d-ff3d-4b30-b5c3-4f0f5170ec3d","resolution":{"observed_at":"2026-08-06T05:05:23.605407Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:05:30.648208Z","title":"Generalization of neural combinatorial solvers through the lens of adversarial robustness","venue":null,"work_id":"2d209ea8-d876-4b59-8f22-27c85bea8e2f","year":2022},"citing_paper":{"arxiv_id":"2508.02510","last_updated":"2025-08-04T15:17:08Z","snapshot_observed_at":"2026-08-06T05:05:21.355196Z","submitted_at":"2025-08-04T15:17:08Z","title":"On Distributional Dependent Performance of Classical and Neural Routing Solvers","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T05:05:23.694309Z"},"links":{"citing_paper":"/paper/2508.02510"},"observation_digest":"sha256:88d301115f9df5ae680fd103c57b61935626414428b3535317066cd48dd19040","observation_id":"54eafd59-e585-48ea-83ec-c29f061198f6","resolution":{"observed_at":"2026-08-06T05:05:30.653701Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:05:30.631387Z","title":"An extension of the lin-kernighan-helsgaun tsp solver for constrained traveling salesman and vehicle routing problems","venue":null,"work_id":"d922adea-0cad-47e0-a149-4f2dff7fb2d8","year":2017},"citing_paper":{"arxiv_id":"2508.02510","last_updated":"2025-08-04T15:17:08Z","snapshot_observed_at":"2026-08-06T05:05:21.355196Z","submitted_at":"2025-08-04T15:17:08Z","title":"On Distributional Dependent Performance of Classical and Neural Routing Solvers","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T05:05:23.759144Z"},"links":{"citing_paper":"/paper/2508.02510"},"observation_digest":"sha256:cc5a9394a49b4bc52eb747de85562822ba31c013d051a2f612b7b00d28e4e4de","observation_id":"76deb069-8a4b-4da1-92f1-2069f4101f7a","resolution":{"observed_at":"2026-08-06T05:05:30.637015Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.3233/faia200","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:05:26.919815Z","title":"Neural large neighborhood search for the capacitated vehicle routing problem","venue":null,"work_id":"316686a4-59e6-4c9b-9999-cf10436463f7","year":2020},"citing_paper":{"arxiv_id":"2508.02510","last_updated":"2025-08-04T15:17:08Z","snapshot_observed_at":"2026-08-06T05:05:21.355196Z","submitted_at":"2025-08-04T15:17:08Z","title":"On Distributional Dependent Performance of Classical and Neural Routing Solvers","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T05:05:23.835627Z"},"links":{"citing_paper":"/paper/2508.02510"},"observation_digest":"sha256:6b8d4e3c9b568c9031b88aec7c5bfc37fcb64bd722712bddbf920a876f3bad42","observation_id":"8055e491-1c68-40ea-841c-b6891736cada","resolution":{"observed_at":"2026-08-06T05:05:27.015435Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:05:23.913444Z","title":"Neural large neighborhood search for routing problems","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2508.02510","last_updated":"2025-08-04T15:17:08Z","snapshot_observed_at":"2026-08-06T05:05:21.355196Z","submitted_at":"2025-08-04T15:17:08Z","title":"On Distributional Dependent Performance of Classical and Neural Routing Solvers","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T05:05:23.913444Z"},"links":{"citing_paper":"/paper/2508.02510"},"observation_digest":"sha256:a8ba19bd57a58a74ef271f1d4601e9bfaba6c963d8e37c0a620ad7e0a07f542e","observation_id":"3c3ff284-51ac-47cb-90fb-06732731ebc4","resolution":{"observed_at":"2026-08-06T05:05:23.913444Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:05:30.609707Z","title":"Efficient Active Search for Combinatorial Optimization Problems","venue":null,"work_id":"60f10967-d817-46c7-8e76-1457576bc1ae","year":2022},"citing_paper":{"arxiv_id":"2508.02510","last_updated":"2025-08-04T15:17:08Z","snapshot_observed_at":"2026-08-06T05:05:21.355196Z","submitted_at":"2025-08-04T15:17:08Z","title":"On Distributional Dependent Performance of Classical and Neural Routing Solvers","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T05:05:23.988520Z"},"links":{"citing_paper":"/paper/2508.02510"},"observation_digest":"sha256:36ae634dde842e672b277c59d422cbd2795804801cfcea733805f826241d59eb","observation_id":"e8b8ac55-6d65-442c-ad07-35a9cbe3020f","resolution":{"observed_at":"2026-08-06T05:05:30.615761Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:05:30.592085Z","title":"Efficient active search for combinatorial optimization problems","venue":null,"work_id":"0d0f91c5-35a1-4e34-9b41-5c8e1b9df873","year":2022},"citing_paper":{"arxiv_id":"2508.02510","last_updated":"2025-08-04T15:17:08Z","snapshot_observed_at":"2026-08-06T05:05:21.355196Z","submitted_at":"2025-08-04T15:17:08Z","title":"On Distributional Dependent Performance of Classical and Neural Routing Solvers","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T05:05:24.063839Z"},"links":{"citing_paper":"/paper/2508.02510"},"observation_digest":"sha256:649525ad36932e7fe7b3b8ca23e230f4b15a0d590d29a111a92884583e6c2f68","observation_id":"c6a27980-09bb-41d2-b3c2-a9fd06fa89a1","resolution":{"observed_at":"2026-08-06T05:05:30.597318Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:05:30.574850Z","title":"PolyNet: Learning Diverse Solution Strategies for Neural Combinatorial Optimization, February 2024","venue":null,"work_id":"c9f2bab7-bce8-4d80-b3b7-614ca5d10a03","year":2024},"citing_paper":{"arxiv_id":"2508.02510","last_updated":"2025-08-04T15:17:08Z","snapshot_observed_at":"2026-08-06T05:05:21.355196Z","submitted_at":"2025-08-04T15:17:08Z","title":"On Distributional Dependent Performance of Classical and Neural Routing Solvers","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T05:05:24.182713Z"},"links":{"citing_paper":"/paper/2508.02510"},"observation_digest":"sha256:4fec0539de4282303e6ce8f07d91c4556f0ec67135730d29a7ed3d505dab58e2","observation_id":"ee7fcc2d-9145-4878-9b94-71eb35e9e7d1","resolution":{"observed_at":"2026-08-06T05:05:30.580040Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:05:24.281667Z","title":"Pointerformer: Deep reinforced multi-pointer transformer for the traveling salesman problem","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2508.02510","last_updated":"2025-08-04T15:17:08Z","snapshot_observed_at":"2026-08-06T05:05:21.355196Z","submitted_at":"2025-08-04T15:17:08Z","title":"On Distributional Dependent Performance of Classical and Neural Routing Solvers","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T05:05:24.281667Z"},"links":{"citing_paper":"/paper/2508.02510"},"observation_digest":"sha256:b8bc74e9109784af5b0089141b9f568f3d05b267da48d17fd4304623446f172c","observation_id":"eb74eebe-508e-49ba-9ec7-a31023630608","resolution":{"observed_at":"2026-08-06T05:05:24.281667Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:05:30.537647Z","title":"Sym-NCO: Leveraging Symmetricity for Neural Combinatorial Optimization","venue":null,"work_id":"2c9ffb8b-158a-4499-9b13-af316515122e","year":2022},"citing_paper":{"arxiv_id":"2508.02510","last_updated":"2025-08-04T15:17:08Z","snapshot_observed_at":"2026-08-06T05:05:21.355196Z","submitted_at":"2025-08-04T15:17:08Z","title":"On Distributional Dependent Performance of Classical and Neural Routing Solvers","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T05:05:24.394652Z"},"links":{"citing_paper":"/paper/2508.02510"},"observation_digest":"sha256:b7cf5fea3ed2499341ee0655f01f09c460403b586ca2cabac0a675d492716980","observation_id":"5e3870b1-1ed0-4d00-a647-6184e4fd30f1","resolution":{"observed_at":"2026-08-06T05:05:30.544001Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:05:30.518491Z","title":"Scale-conditioned adaptation for large scale combinatorial optimization","venue":null,"work_id":"9faa7339-ecee-4ad0-a852-2368002d851f","year":2022},"citing_paper":{"arxiv_id":"2508.02510","last_updated":"2025-08-04T15:17:08Z","snapshot_observed_at":"2026-08-06T05:05:21.355196Z","submitted_at":"2025-08-04T15:17:08Z","title":"On Distributional Dependent Performance of Classical and Neural Routing Solvers","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T05:05:24.470575Z"},"links":{"citing_paper":"/paper/2508.02510"},"observation_digest":"sha256:cf25a86877ff81dcbe0fb1c32756b4138684e1383601bbff87d9e8bc2952c410","observation_id":"3c82dcba-330e-40e3-bf34-416fb76c7e27","resolution":{"observed_at":"2026-08-06T05:05:30.524100Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:05:30.491643Z","title":"Attention, Learn to Solve Routing Problems! In 7th International Conference on Learning Representations, ICLR 2019, New Orleans, LA, USA, May 6-9, 2019","venue":null,"work_id":"a2b53af2-f9c9-40af-9ebc-4886026e5f0a","year":2019},"citing_paper":{"arxiv_id":"2508.02510","last_updated":"2025-08-04T15:17:08Z","snapshot_observed_at":"2026-08-06T05:05:21.355196Z","submitted_at":"2025-08-04T15:17:08Z","title":"On Distributional Dependent Performance of Classical and Neural Routing Solvers","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T05:05:24.522821Z"},"links":{"citing_paper":"/paper/2508.02510"},"observation_digest":"sha256:9508877e44b80a3450daaa7dc44c39b2a56f1abb27e704d4968d074dc3794033","observation_id":"e1aeaebd-32c4-4c83-b40e-c01f4fe6d23d","resolution":{"observed_at":"2026-08-06T05:05:30.501964Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:05:30.470349Z","title":"Deep policy dynamic programming for vehicle routing problems","venue":null,"work_id":"be2fefa2-4bb6-4a56-b872-be9cd5bbebd8","year":2022},"citing_paper":{"arxiv_id":"2508.02510","last_updated":"2025-08-04T15:17:08Z","snapshot_observed_at":"2026-08-06T05:05:21.355196Z","submitted_at":"2025-08-04T15:17:08Z","title":"On Distributional Dependent Performance of Classical and Neural Routing Solvers","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T05:05:24.611122Z"},"links":{"citing_paper":"/paper/2508.02510"},"observation_digest":"sha256:4c2b1d8b6aa5bf65a3a6574400f083dc9e4a4218e2dbddf955d1379aff372d90","observation_id":"425126df-7855-45c7-bc1f-93aea7c6f037","resolution":{"observed_at":"2026-08-06T05:05:30.475007Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:05:30.449705Z","title":null,"venue":null,"work_id":"af4e7a4d-bbcd-452b-9127-d92227a80abc","year":2022},"citing_paper":{"arxiv_id":"2508.02510","last_updated":"2025-08-04T15:17:08Z","snapshot_observed_at":"2026-08-06T05:05:21.355196Z","submitted_at":"2025-08-04T15:17:08Z","title":"On Distributional Dependent Performance of Classical and Neural Routing Solvers","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T05:05:24.666325Z"},"links":{"citing_paper":"/paper/2508.02510"},"observation_digest":"sha256:def7e9382acb4587755743fb1df5c1a379fcf89ac5ef749defe80b9a6f8c92ca","observation_id":"d6f83435-fe2e-4ecb-81d0-0ac80db21b9f","resolution":{"observed_at":"2026-08-06T05:05:30.455679Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:05:30.428838Z","title":"POMO: Policy optimization with multiple optima for reinforcement learning","venue":null,"work_id":"6ae53ae9-e426-4a81-9494-cb64add93f2d","year":2020},"citing_paper":{"arxiv_id":"2508.02510","last_updated":"2025-08-04T15:17:08Z","snapshot_observed_at":"2026-08-06T05:05:21.355196Z","submitted_at":"2025-08-04T15:17:08Z","title":"On Distributional Dependent Performance of Classical and Neural Routing Solvers","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T05:05:24.738409Z"},"links":{"citing_paper":"/paper/2508.02510"},"observation_digest":"sha256:62783e465a6e5cc8943befafc6f4e30cbe2d836573304f9117cb06a310895809","observation_id":"1c149ef4-6723-46f0-ac90-3d3c3f05edde","resolution":{"observed_at":"2026-08-06T05:05:30.434229Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:05:30.410188Z","title":"Matrix encoding networks for neural combinatorial optimization","venue":null,"work_id":"5380cf1c-a008-4e23-8145-ae0278c5786d","year":2021},"citing_paper":{"arxiv_id":"2508.02510","last_updated":"2025-08-04T15:17:08Z","snapshot_observed_at":"2026-08-06T05:05:21.355196Z","submitted_at":"2025-08-04T15:17:08Z","title":"On Distributional Dependent Performance of Classical and Neural Routing Solvers","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T05:05:24.790430Z"},"links":{"citing_paper":"/paper/2508.02510"},"observation_digest":"sha256:707408203fc1c740c79a45929122640b79446f423790e0317f82075c2bdf6d5f","observation_id":"807fd679-a235-4cb6-b2d9-5270bb0157a4","resolution":{"observed_at":"2026-08-06T05:05:30.415872Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:05:30.389731Z","title":"Learning to delegate for large-scale vehicle routing","venue":null,"work_id":"6cc7d0c4-a868-4f30-9865-40159b439db8","year":2021},"citing_paper":{"arxiv_id":"2508.02510","last_updated":"2025-08-04T15:17:08Z","snapshot_observed_at":"2026-08-06T05:05:21.355196Z","submitted_at":"2025-08-04T15:17:08Z","title":"On Distributional Dependent Performance of Classical and Neural Routing Solvers","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T05:05:24.870062Z"},"links":{"citing_paper":"/paper/2508.02510"},"observation_digest":"sha256:177eb48d6938ec85dcb33d6d8291c0ac55c4cfdad1967e384eb989d6f96b1997","observation_id":"abeec8db-d5a6-4a7d-8afb-fadf8f25a7eb","resolution":{"observed_at":"2026-08-06T05:05:30.396544Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:05:30.302784Z","title":"From Distribution Learning in Training to Gradient Search in Testing for Combinatorial Optimization","venue":null,"work_id":"6ae46e54-54c2-4904-b217-483f15ef1719","year":2023},"citing_paper":{"arxiv_id":"2508.02510","last_updated":"2025-08-04T15:17:08Z","snapshot_observed_at":"2026-08-06T05:05:21.355196Z","submitted_at":"2025-08-04T15:17:08Z","title":"On Distributional Dependent Performance of Classical and Neural Routing Solvers","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T05:05:24.951119Z"},"links":{"citing_paper":"/paper/2508.02510"},"observation_digest":"sha256:38816932db7cdc0d8551c80df4687a5797d4f1183db121bd7b7c1b2d5104cbd0","observation_id":"3844aef2-4480-42e7-be63-811d3861b8bc","resolution":{"observed_at":"2026-08-06T05:05:30.378056Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2011.06188","last_updated":"2020-11-12T04:21:04Z","snapshot_observed_at":"2026-08-05T23:50:07.459162Z","submitted_at":"2020-11-12T04:21:04Z","title":"Evaluating Curriculum Learning Strategies in Neural Combinatorial Optimization","version":1},"cited_work":{"arxiv_id":"2011.06188","doi":null,"metadata_source":"pith","pith_arxiv_id":"2011.06188","snapshot_observed_at":"2026-08-06T05:05:27.273998Z","title":"Evaluating Curriculum Learning Strategies in Neural Combinatorial Optimization","venue":"cs.LG","work_id":"b1533a29-65c2-4df2-af0b-cf53a63ccb7e","year":2020},"citing_paper":{"arxiv_id":"2508.02510","last_updated":"2025-08-04T15:17:08Z","snapshot_observed_at":"2026-08-06T05:05:21.355196Z","submitted_at":"2025-08-04T15:17:08Z","title":"On Distributional Dependent Performance of Classical and Neural Routing Solvers","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T05:05:25.066719Z"},"links":{"cited_paper":"/paper/2011.06188","citing_paper":"/paper/2508.02510"},"observation_digest":"sha256:9c9dd4d2db436d5788f5d24ca6872fb7d17ac8216315316f255f66d17d1595f9","observation_id":"e041b9c0-73a9-4efe-b96b-ff420479ff93","resolution":{"observed_at":"2026-08-06T05:05:27.333332Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:05:29.947279Z","title":"Neural Combinatorial Optimization with Heavy Decoder: Toward Large Scale Generalization","venue":null,"work_id":"6cb1d793-e548-4cb1-95f1-c6622a901fb3","year":2023},"citing_paper":{"arxiv_id":"2508.02510","last_updated":"2025-08-04T15:17:08Z","snapshot_observed_at":"2026-08-06T05:05:21.355196Z","submitted_at":"2025-08-04T15:17:08Z","title":"On Distributional Dependent Performance of Classical and Neural Routing Solvers","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T05:05:25.177216Z"},"links":{"citing_paper":"/paper/2508.02510"},"observation_digest":"sha256:f5e664635927b68cb2d823e566ece96773d37d2c0feded9edae3f26803b2d936","observation_id":"36d17696-0221-40ac-8f8e-c9ec6af2042d","resolution":{"observed_at":"2026-08-06T05:05:30.088140Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:05:29.807429Z","title":"Learning to Search Feasible and Infeasible Regions of Routing Problems with Flexible Neural k-Opt","venue":null,"work_id":"b896d5ff-2384-41b8-86c8-5e65d4b1da67","year":2023},"citing_paper":{"arxiv_id":"2508.02510","last_updated":"2025-08-04T15:17:08Z","snapshot_observed_at":"2026-08-06T05:05:21.355196Z","submitted_at":"2025-08-04T15:17:08Z","title":"On Distributional Dependent Performance of Classical and Neural Routing Solvers","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-06T05:05:25.226000Z"},"links":{"citing_paper":"/paper/2508.02510"},"observation_digest":"sha256:91b6e4dc10e0796d3840eaf7bab48e0b7dfe7e48f34f438dca86f05ccffffcbe","observation_id":"f21093ff-0628-48ac-95f1-1c41b290b88f","resolution":{"observed_at":"2026-08-06T05:05:29.861089Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:05:29.511439Z","title":null,"venue":null,"work_id":"5f54b84e-dcf2-47ce-bade-5791ae40ac59","year":2023},"citing_paper":{"arxiv_id":"2508.02510","last_updated":"2025-08-04T15:17:08Z","snapshot_observed_at":"2026-08-06T05:05:21.355196Z","submitted_at":"2025-08-04T15:17:08Z","title":"On Distributional Dependent Performance of Classical and Neural Routing Solvers","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-06T05:05:25.299355Z"},"links":{"citing_paper":"/paper/2508.02510"},"observation_digest":"sha256:2229fba2c36c074a86438d14e38c6aed7f3e183c9f7925e990f30c580b2b90c2","observation_id":"086e0755-2e91-4e92-9b87-cbe2bde3dccd","resolution":{"observed_at":"2026-08-06T05:05:29.728195Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:05:29.266742Z","title":"Reinforce- ment learning for solving the vehicle routing problem","venue":null,"work_id":"441d1dd1-0c6f-43bf-a32b-b0d0e825fa7b","year":2018},"citing_paper":{"arxiv_id":"2508.02510","last_updated":"2025-08-04T15:17:08Z","snapshot_observed_at":"2026-08-06T05:05:21.355196Z","submitted_at":"2025-08-04T15:17:08Z","title":"On Distributional Dependent Performance of Classical and Neural Routing Solvers","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-06T05:05:25.360074Z"},"links":{"citing_paper":"/paper/2508.02510"},"observation_digest":"sha256:11b3458d15193869a39394f052042ee3514022b0e4dac37782032f55aa10dee4","observation_id":"37a4b4ba-6c6d-4f36-90ba-b581bcb3df5d","resolution":{"observed_at":"2026-08-06T05:05:29.395940Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:05:29.163554Z","title":"DIFUSCO: Graph-based Diffusion Solvers for Combinato- rial Optimization","venue":null,"work_id":"cd74e1fc-15b2-4526-ba85-ee834208b9c6","year":2023},"citing_paper":{"arxiv_id":"2508.02510","last_updated":"2025-08-04T15:17:08Z","snapshot_observed_at":"2026-08-06T05:05:21.355196Z","submitted_at":"2025-08-04T15:17:08Z","title":"On Distributional Dependent Performance of Classical and Neural Routing Solvers","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-06T05:05:25.426545Z"},"links":{"citing_paper":"/paper/2508.02510"},"observation_digest":"sha256:650f66238609385b481bf49c12c718712554d56499d8b10b98b31ab2763f3042","observation_id":"39b53191-09da-4199-9885-a96d0817a453","resolution":{"observed_at":"2026-08-06T05:05:29.241161Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:05:29.011010Z","title":"New benchmark instances for the capacitated vehicle routing problem","venue":null,"work_id":"23c472b8-3a31-4def-8aef-21efaa797df7","year":2017},"citing_paper":{"arxiv_id":"2508.02510","last_updated":"2025-08-04T15:17:08Z","snapshot_observed_at":"2026-08-06T05:05:21.355196Z","submitted_at":"2025-08-04T15:17:08Z","title":"On Distributional Dependent Performance of Classical and Neural Routing Solvers","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-06T05:05:25.494889Z"},"links":{"citing_paper":"/paper/2508.02510"},"observation_digest":"sha256:877ce3656bcac02a4db24036488234e5e2b78da9f5efc8673a7c84271f9ad8fd","observation_id":"76a92070-64db-4205-8181-56dae63c9f7a","resolution":{"observed_at":"2026-08-06T05:05:29.063300Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:05:25.575769Z","title":"Hybrid genetic search for the cvrp: Open-source implementation and swap* neighborhood","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2508.02510","last_updated":"2025-08-04T15:17:08Z","snapshot_observed_at":"2026-08-06T05:05:21.355196Z","submitted_at":"2025-08-04T15:17:08Z","title":"On Distributional Dependent Performance of Classical and Neural Routing Solvers","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-06T05:05:25.575769Z"},"links":{"citing_paper":"/paper/2508.02510"},"observation_digest":"sha256:7d05257609a448df8c0117ce59ae912a16f4f450cf8dfd23c1cc2ba27fa97725","observation_id":"90bdd152-ccea-4c51-a220-ba4929b99635","resolution":{"observed_at":"2026-08-06T05:05:25.575769Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:05:28.862554Z","title":"A hybrid genetic algorithm for multidepot and periodic vehicle routing problems","venue":null,"work_id":"91381c73-eb67-4005-9e53-480e8b7fecd1","year":2012},"citing_paper":{"arxiv_id":"2508.02510","last_updated":"2025-08-04T15:17:08Z","snapshot_observed_at":"2026-08-06T05:05:21.355196Z","submitted_at":"2025-08-04T15:17:08Z","title":"On Distributional Dependent Performance of Classical and Neural Routing Solvers","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-06T05:05:25.655172Z"},"links":{"citing_paper":"/paper/2508.02510"},"observation_digest":"sha256:eee4065366d9458c391927ca0dcd687e120e584799fd4a673a45e50c14816808","observation_id":"770869e7-190e-4662-9d92-1e8eb957e13a","resolution":{"observed_at":"2026-08-06T05:05:28.921331Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:05:28.707611Z","title":"Pointer Networks","venue":null,"work_id":"b48d1200-057e-449e-be3a-8d285567e1a3","year":2015},"citing_paper":{"arxiv_id":"2508.02510","last_updated":"2025-08-04T15:17:08Z","snapshot_observed_at":"2026-08-06T05:05:21.355196Z","submitted_at":"2025-08-04T15:17:08Z","title":"On Distributional Dependent Performance of Classical and Neural Routing Solvers","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-06T05:05:25.743012Z"},"links":{"citing_paper":"/paper/2508.02510"},"observation_digest":"sha256:b07595d8fbe669c082effd64ae34c9451c021cbca876d96248ba2a49ed03abc9","observation_id":"23bba655-d082-4951-b947-3c3ba996f950","resolution":{"observed_at":"2026-08-06T05:05:28.771377Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:05:25.847199Z","title":"Multi-Decoder Attention Model with Em- bedding Glimpse for Solving Vehicle Routing Problems","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2508.02510","last_updated":"2025-08-04T15:17:08Z","snapshot_observed_at":"2026-08-06T05:05:21.355196Z","submitted_at":"2025-08-04T15:17:08Z","title":"On Distributional Dependent Performance of Classical and Neural Routing Solvers","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-06T05:05:25.847199Z"},"links":{"citing_paper":"/paper/2508.02510"},"observation_digest":"sha256:6537476faa0c745faab3b831c48ac1021a4f00e1105ec4e98e560b37d8a74503","observation_id":"d6be817e-265f-4419-9d8e-5c80851ad349","resolution":{"observed_at":"2026-08-06T05:05:25.847199Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:05:28.555474Z","title":"NeuroLKH: Combining Deep Learning Model with Lin-Kernighan-Helsgaun Heuristic for Solving the Traveling Salesman Problem","venue":null,"work_id":"e81a7425-7df7-4cbd-b3ca-b1446aa09c96","year":2021},"citing_paper":{"arxiv_id":"2508.02510","last_updated":"2025-08-04T15:17:08Z","snapshot_observed_at":"2026-08-06T05:05:21.355196Z","submitted_at":"2025-08-04T15:17:08Z","title":"On Distributional Dependent Performance of Classical and Neural Routing Solvers","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-06T05:05:25.941418Z"},"links":{"citing_paper":"/paper/2508.02510"},"observation_digest":"sha256:58643366b8453afc405c14625a93fb0b8f34dc4facb67f44ae45700d18bb32b7","observation_id":"aa15edb3-10b3-40be-b03f-45365babbab9","resolution":{"observed_at":"2026-08-06T05:05:28.626323Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:05:28.424981Z","title":"DeepACO: Neural-enhanced Ant Systems for Combinatorial Optimization","venue":null,"work_id":"8e647699-e674-4256-9743-a5204651bee7","year":2023},"citing_paper":{"arxiv_id":"2508.02510","last_updated":"2025-08-04T15:17:08Z","snapshot_observed_at":"2026-08-06T05:05:21.355196Z","submitted_at":"2025-08-04T15:17:08Z","title":"On Distributional Dependent Performance of Classical and Neural Routing Solvers","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-06T05:05:26.028496Z"},"links":{"citing_paper":"/paper/2508.02510"},"observation_digest":"sha256:c7e4c4c8c49f734b3f26589d78398e2841f784488eb2761ccabfc695ad02c4be","observation_id":"54dda5f8-eab1-46c6-9343-25d49b52f0d3","resolution":{"observed_at":"2026-08-06T05:05:28.461951Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:05:26.099817Z","title":"GLOP: Learning Global Partition and Local Construction for Solving Large-Scale Routing Problems in Real-Time","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2508.02510","last_updated":"2025-08-04T15:17:08Z","snapshot_observed_at":"2026-08-06T05:05:21.355196Z","submitted_at":"2025-08-04T15:17:08Z","title":"On Distributional Dependent Performance of Classical and Neural Routing Solvers","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-06T05:05:26.099817Z"},"links":{"citing_paper":"/paper/2508.02510"},"observation_digest":"sha256:7033770e8eee15575f9529a474e1b50b501a0ea8ab67d80b370d62c3f2a9259c","observation_id":"f391e17d-00b4-4d66-bfa3-b58f6e727f90","resolution":{"observed_at":"2026-08-06T05:05:26.099817Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:05:28.253895Z","title":"It’s Not What Machines Can Learn, It’s What We Cannot Teach","venue":null,"work_id":"39b14d4b-8026-4069-bb82-66452f80557d","year":2020},"citing_paper":{"arxiv_id":"2508.02510","last_updated":"2025-08-04T15:17:08Z","snapshot_observed_at":"2026-08-06T05:05:21.355196Z","submitted_at":"2025-08-04T15:17:08Z","title":"On Distributional Dependent Performance of Classical and Neural Routing Solvers","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-06T05:05:26.189290Z"},"links":{"citing_paper":"/paper/2508.02510"},"observation_digest":"sha256:84f5af58a604905ab8d711bdbf7f5b56dd8b0caca50eba92eb63b606ca2b4e10","observation_id":"6e116309-59c9-4bfc-8615-d49178b5de2b","resolution":{"observed_at":"2026-08-06T05:05:28.323563Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1609/aaai.v36i8.20899","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:05:26.695574Z","title":"Learning to solve travelling salesman problem with hardness-adaptive curriculum","venue":null,"work_id":"59c29d90-25b0-47fd-b87e-6f6795cc4eab","year":2022},"citing_paper":{"arxiv_id":"2508.02510","last_updated":"2025-08-04T15:17:08Z","snapshot_observed_at":"2026-08-06T05:05:21.355196Z","submitted_at":"2025-08-04T15:17:08Z","title":"On Distributional Dependent Performance of Classical and Neural Routing Solvers","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-06T05:05:26.282987Z"},"links":{"citing_paper":"/paper/2508.02510"},"observation_digest":"sha256:4fd3938e6ce5ae19e9fcc5433b2a7c41cabf6b1565d033ce0313226a63912137","observation_id":"a29e13ca-a3a9-4def-864e-d20b153b06a3","resolution":{"observed_at":"2026-08-06T05:05:26.801213Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:05:28.125730Z","title":"UDC: A Unified Neural Divide-and-Conquer Framework for Large-Scale Combinatorial Optimization Problems, June 2024","venue":null,"work_id":"5f474340-c7b1-4b5b-8dbd-f9b474f4eca6","year":2024},"citing_paper":{"arxiv_id":"2508.02510","last_updated":"2025-08-04T15:17:08Z","snapshot_observed_at":"2026-08-06T05:05:21.355196Z","submitted_at":"2025-08-04T15:17:08Z","title":"On Distributional Dependent Performance of Classical and Neural Routing Solvers","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-06T05:05:26.393475Z"},"links":{"citing_paper":"/paper/2508.02510"},"observation_digest":"sha256:717ec867240697894b82ea790053c3b7b66529d97cb090481a6834d331bb062e","observation_id":"2b2825f3-b489-45f7-9d94-bebf87c84b0b","resolution":{"observed_at":"2026-08-06T05:05:28.189162Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:05:27.924096Z","title":"Towards omni-generalizable neural methods for vehicle routing problems","venue":null,"work_id":"c570f65b-dc1a-48c7-8b6f-3258679f36b7","year":2023},"citing_paper":{"arxiv_id":"2508.02510","last_updated":"2025-08-04T15:17:08Z","snapshot_observed_at":"2026-08-06T05:05:21.355196Z","submitted_at":"2025-08-04T15:17:08Z","title":"On Distributional Dependent Performance of Classical and Neural Routing Solvers","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-06T05:05:26.480459Z"},"links":{"citing_paper":"/paper/2508.02510"},"observation_digest":"sha256:ad6144a3767b844d4021c96488582dd831023d4fd5d0d21b84430e9278dab20f","observation_id":"9004efdc-d485-4bcf-b6ee-17f0a016a36e","resolution":{"observed_at":"2026-08-06T05:05:28.014884Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:05:27.741890Z","title":null,"venue":null,"work_id":"e8c625eb-6d24-4b22-b1ed-f8cf9b09b2ac","year":2012},"citing_paper":{"arxiv_id":"2508.02510","last_updated":"2025-08-04T15:17:08Z","snapshot_observed_at":"2026-08-06T05:05:21.355196Z","submitted_at":"2025-08-04T15:17:08Z","title":"On Distributional Dependent Performance of Classical and Neural Routing Solvers","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-06T05:05:26.549203Z"},"links":{"citing_paper":"/paper/2508.02510"},"observation_digest":"sha256:46f0350eba8eb7d062e443bcb1469846850e20ec0ca85bb89ae5e03be6d6a726","observation_id":"431be518-ecbc-4e91-9410-c8c5d2ebe0d7","resolution":{"observed_at":"2026-08-06T05:05:27.803570Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2508.02510","last_updated":"2025-08-04T15:17:08Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-06T05:05:21.355196Z","submitted_at":"2025-08-04T15:17:08Z","title":"On Distributional Dependent Performance of Classical and Neural Routing Solvers"},"reference_resolution":{"displayed":50,"state_counts":{"malformed_identifier":2,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":10,"verified_exact":5,"verified_fuzzy":33},"total_outbound_references":50},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 0 inbound Pith citation observations for arXiv:2508.02510."}