{"as_of":"2026-08-12T03:02:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:3a9969099a219eeac3dc5795d4c22225984258da392b3891b497dd203e51d5e1","coverage":[{"denominator":47,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":47,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-08T10:55:25.924794Z","state":"measured"},{"denominator":48,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":48,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-11T06:34:44.6726+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T18:37:42.131811Z","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":"2026-08-07T18:37:42.198411Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2502.08125","last_updated":"2025-02-12T05:06:23Z","snapshot_observed_at":"2026-08-08T10:18:15.644082Z","submitted_at":"2025-02-12T05:06:23Z","title":"Incremental Approximate Single-Source Shortest Paths with Predictions","version":1},"cited_work":{"arxiv_id":"2502.08125","doi":null,"metadata_source":"pith","pith_arxiv_id":"2502.08125","snapshot_observed_at":"2026-08-07T18:37:42.198411Z","title":"Incremental Approximate Single-Source Shortest Paths with Predictions","venue":"cs.DS","work_id":"bc11841b-591a-4086-a21b-a8ee404a7bbb","year":2025},"citing_paper":{"arxiv_id":"2502.10348","last_updated":"2025-02-14T18:20:45Z","snapshot_observed_at":"2026-08-07T18:21:09.152770Z","submitted_at":"2025-02-14T18:20:45Z","title":"On Incremental Approximate Shortest Paths in Directed Graphs","version":1},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-07T18:37:42.131811Z"},"links":{"cited_paper":"/paper/2502.08125","citing_paper":"/paper/2502.10348"},"observation_digest":"sha256:eb0c43dc0d2c506c7c0afbe3560046d969c7941b519621088e65ca221305adb6","observation_id":"4073fbfc-0a0a-4f76-9d71-cacfe8a7eac3","resolution":{"observed_at":"2026-08-07T18:37:42.206393Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2502.08125/citation-record","integrity":"/paper/2502.08125/integrity","json":"/paper/2502.08125/citation-record.json","paper":"/paper/2502.08125"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T10:55:26.440065Z","title":"Sorting with predic tions","venue":null,"work_id":"d92de1e1-fb99-4130-81c7-d2cba22838b3","year":2023},"citing_paper":{"arxiv_id":"2502.08125","last_updated":"2025-02-12T05:06:23Z","snapshot_observed_at":"2026-08-08T10:18:15.644082Z","submitted_at":"2025-02-12T05:06:23Z","title":"Incremental Approximate Single-Source Shortest Paths with Predictions","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-08T10:55:25.766254Z"},"links":{"citing_paper":"/paper/2502.08125"},"observation_digest":"sha256:700149cd4c6666dcd4538e64799a378ba0360aad5e6f79ed1d3b29329f3ba33e","observation_id":"598ecbfd-7a84-4fc6-96ea-b07cef3626cc","resolution":{"observed_at":"2026-08-08T10:55:26.443504Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T10:55:26.430384Z","title":"Learning-augment ed priority queues","venue":null,"work_id":"2e28803f-a665-4649-a825-db370bf0e4a7","year":2024},"citing_paper":{"arxiv_id":"2502.08125","last_updated":"2025-02-12T05:06:23Z","snapshot_observed_at":"2026-08-08T10:18:15.644082Z","submitted_at":"2025-02-12T05:06:23Z","title":"Incremental Approximate Single-Source Shortest Paths with Predictions","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-08T10:55:25.770396Z"},"links":{"citing_paper":"/paper/2502.08125"},"observation_digest":"sha256:ae256d490d9f5120c6e3ab680e8f2bede6cbf3333f2e21bf7c4b5f7ba66e6fbf","observation_id":"6d131348-a763-4aa9-8848-24408a808f4b","resolution":{"observed_at":"2026-08-08T10:55:26.434170Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T10:55:26.420652Z","title":"Bercea, Jakob Bæk Tejs Houen, and Rasmus Pagh","venue":null,"work_id":"2bbfeb4f-30db-4f0b-99b1-fed5a7489c18","year":2024},"citing_paper":{"arxiv_id":"2502.08125","last_updated":"2025-02-12T05:06:23Z","snapshot_observed_at":"2026-08-08T10:18:15.644082Z","submitted_at":"2025-02-12T05:06:23Z","title":"Incremental Approximate Single-Source Shortest Paths with Predictions","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-08T10:55:25.774697Z"},"links":{"citing_paper":"/paper/2502.08125"},"observation_digest":"sha256:e7e2b2cd7c40c6379d4210970ac207b4f3e69d6f4a4e677423947ca341e6d3c2","observation_id":"9865e98e-18ca-4b13-979d-cf64ae6938d4","resolution":{"observed_at":"2026-08-08T10:55:26.424028Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T10:55:26.409359Z","title":"Fully dynamic (2+ ε) approximate all-pairs shortest paths with fast query and close to linear update time","venue":null,"work_id":"490851fe-c107-41e8-a509-0da5ae47d8c8","year":2009},"citing_paper":{"arxiv_id":"2502.08125","last_updated":"2025-02-12T05:06:23Z","snapshot_observed_at":"2026-08-08T10:18:15.644082Z","submitted_at":"2025-02-12T05:06:23Z","title":"Incremental Approximate Single-Source Shortest Paths with Predictions","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-08T10:55:25.778689Z"},"links":{"citing_paper":"/paper/2502.08125"},"observation_digest":"sha256:6167e3729e1554e8336f40832f289309daf9c36f342c23e7ef35b17638657876","observation_id":"a71b5df4-57ff-4385-ad3e-f842844b74b4","resolution":{"observed_at":"2026-08-08T10:55:26.413705Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T10:55:26.398287Z","title":"Maintaining shortest paths under dele tions in weighted directed graphs","venue":null,"work_id":"84085983-2875-4a27-9909-437e7a7f654a","year":2016},"citing_paper":{"arxiv_id":"2502.08125","last_updated":"2025-02-12T05:06:23Z","snapshot_observed_at":"2026-08-08T10:18:15.644082Z","submitted_at":"2025-02-12T05:06:23Z","title":"Incremental Approximate Single-Source Shortest Paths with Predictions","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-08T10:55:25.782425Z"},"links":{"citing_paper":"/paper/2502.08125"},"observation_digest":"sha256:7eeb3a6371ef89517e8c6c19c7debe689c6ed416ea433466b96bf8c97bb0f75a","observation_id":"8acb7b1b-5250-4c09-b2a9-b6b0d446bf95","resolution":{"observed_at":"2026-08-08T10:55:26.401762Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T10:55:26.387395Z","title":"Deterministic decremental SSSP and approximate min-cost flow in almost-li near time","venue":null,"work_id":"ec4e1cf8-4601-4587-b3b2-60c9f46b631f","year":2021},"citing_paper":{"arxiv_id":"2502.08125","last_updated":"2025-02-12T05:06:23Z","snapshot_observed_at":"2026-08-08T10:18:15.644082Z","submitted_at":"2025-02-12T05:06:23Z","title":"Incremental Approximate Single-Source Shortest Paths with Predictions","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-08T10:55:25.786058Z"},"links":{"citing_paper":"/paper/2502.08125"},"observation_digest":"sha256:d2c11652d6ec480d903959cdcae96bac92199b3e404bce268d7c58ed7bedeab3","observation_id":"c6fe0b8b-1490-4dd6-ad0b-008aa158d90c","resolution":{"observed_at":"2026-08-08T10:55:26.391349Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T10:55:26.376722Z","title":"Near-optimal decre- mental SSSP in dense weighted digraphs","venue":null,"work_id":"8d0170c6-8d7a-4eb2-a898-82c9d51101d8","year":2020},"citing_paper":{"arxiv_id":"2502.08125","last_updated":"2025-02-12T05:06:23Z","snapshot_observed_at":"2026-08-08T10:18:15.644082Z","submitted_at":"2025-02-12T05:06:23Z","title":"Incremental Approximate Single-Source Shortest Paths with Predictions","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-08T10:55:25.789586Z"},"links":{"citing_paper":"/paper/2502.08125"},"observation_digest":"sha256:ea8e2a926f29716acb50709920ebd2fad8068dad9f52dff6396c941ecda4a678","observation_id":"1a32d30e-406f-44a7-8002-09c8e7ce0782","resolution":{"observed_at":"2026-08-08T10:55:26.380469Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T10:55:26.365481Z","title":"Adaptive probing policies for shortest path routing","venue":null,"work_id":"bbf951f2-ff9e-4860-ab77-55fbf02038b1","year":2020},"citing_paper":{"arxiv_id":"2502.08125","last_updated":"2025-02-12T05:06:23Z","snapshot_observed_at":"2026-08-08T10:18:15.644082Z","submitted_at":"2025-02-12T05:06:23Z","title":"Incremental Approximate Single-Source Shortest Paths with Predictions","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-08T10:55:25.792620Z"},"links":{"citing_paper":"/paper/2502.08125"},"observation_digest":"sha256:9f15074091c8e92b963018fe482fd314df4248515cca29aaeec585a4c1bbda03","observation_id":"7e3bd53f-8359-439b-bcfd-b2e193875917","resolution":{"observed_at":"2026-08-08T10:55:26.369029Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T10:55:26.354190Z","title":"Incremental single sour ce shortest paths in sparse digraphs","venue":null,"work_id":"7703770b-a6cc-422e-a336-6e4a9f4dad9a","year":2021},"citing_paper":{"arxiv_id":"2502.08125","last_updated":"2025-02-12T05:06:23Z","snapshot_observed_at":"2026-08-08T10:18:15.644082Z","submitted_at":"2025-02-12T05:06:23Z","title":"Incremental Approximate Single-Source Shortest Paths with Predictions","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-08T10:55:25.795881Z"},"links":{"citing_paper":"/paper/2502.08125"},"observation_digest":"sha256:97d26a5ad188a9c6136a14dcd658531ac7967586907cfd3bcc04e96890177c06","observation_id":"48430694-0415-40e1-ae93-abd88fd44c71","resolution":{"observed_at":"2026-08-08T10:55:26.358238Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2211.09251","last_updated":"2025-05-15T04:46:39Z","snapshot_observed_at":"2026-07-06T14:19:35.373606Z","submitted_at":"2022-11-16T22:50:40Z","title":"On the Power of Learning-Augmented Search Trees","version":3},"cited_work":{"arxiv_id":"2211.09251","doi":null,"metadata_source":"pith","pith_arxiv_id":"2211.09251","snapshot_observed_at":"2026-08-08T10:55:25.953280Z","title":"On the Power of Learning-Augmented Search Trees","venue":"cs.DS","work_id":"63558d1b-2f73-41a9-a86f-8c6ba5141a18","year":2022},"citing_paper":{"arxiv_id":"2502.08125","last_updated":"2025-02-12T05:06:23Z","snapshot_observed_at":"2026-08-08T10:18:15.644082Z","submitted_at":"2025-02-12T05:06:23Z","title":"Incremental Approximate Single-Source Shortest Paths with Predictions","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-08T10:55:25.799162Z"},"links":{"cited_paper":"/paper/2211.09251","citing_paper":"/paper/2502.08125"},"observation_digest":"sha256:b7f6def137139c2a885ab0f2de81022a06ec59cae1a8c14a233096a48b45bfc7","observation_id":"f5d1bffe-3717-485e-86af-e7bcb66dbd79","resolution":{"observed_at":"2026-08-08T10:55:25.958941Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T10:55:26.342590Z","title":"From WiscKey to Bourbon: A learned index for log-structured merge trees","venue":null,"work_id":"d24a8273-b02c-49c0-b405-7fcab79147e3","year":2020},"citing_paper":{"arxiv_id":"2502.08125","last_updated":"2025-02-12T05:06:23Z","snapshot_observed_at":"2026-08-08T10:18:15.644082Z","submitted_at":"2025-02-12T05:06:23Z","title":"Incremental Approximate Single-Source Shortest Paths with Predictions","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-08T10:55:25.802840Z"},"links":{"citing_paper":"/paper/2502.08125"},"observation_digest":"sha256:4d8f9265e82aee7d0fb022f390b566a6587d03a60f1d6d75173146d3c2c0fffa","observation_id":"3c7db9a7-cf25-44c8-a225-2137647ad7f7","resolution":{"observed_at":"2026-08-08T10:55:26.346966Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T10:55:26.331875Z","title":"Predictive flows for faster ford-fulkerson","venue":null,"work_id":"9e07b089-485c-429a-af0c-cfd348ba75cb","year":2023},"citing_paper":{"arxiv_id":"2502.08125","last_updated":"2025-02-12T05:06:23Z","snapshot_observed_at":"2026-08-08T10:18:15.644082Z","submitted_at":"2025-02-12T05:06:23Z","title":"Incremental Approximate Single-Source Shortest Paths with Predictions","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-08T10:55:25.806127Z"},"links":{"citing_paper":"/paper/2502.08125"},"observation_digest":"sha256:5c54e3ef1d5c7cef8d03f2ce5a3312ed3fd0ae97eadd7bd6828bc856247784bd","observation_id":"500d7769-1f59-4884-a7ac-76b113cfa949","resolution":{"observed_at":"2026-08-08T10:55:26.335828Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T10:55:26.319240Z","title":"ALEX: an updatable adaptive learned index","venue":null,"work_id":"67260b8d-80c7-4c27-b7b2-94b45add9252","year":2020},"citing_paper":{"arxiv_id":"2502.08125","last_updated":"2025-02-12T05:06:23Z","snapshot_observed_at":"2026-08-08T10:18:15.644082Z","submitted_at":"2025-02-12T05:06:23Z","title":"Incremental Approximate Single-Source Shortest Paths with Predictions","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-08T10:55:25.809590Z"},"links":{"citing_paper":"/paper/2502.08125"},"observation_digest":"sha256:b17853b0544f42175ce0fd7a848921d72c13b8838c9d3f5cbfb6f373db0b7f37","observation_id":"2096b127-befc-4f7d-9774-25402e891cba","resolution":{"observed_at":"2026-08-08T10:55:26.324030Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T10:55:26.308058Z","title":"Binary search with distributional p redictions","venue":null,"work_id":"9bc98ca7-041c-4e8b-a4d6-65772bc6f4a0","year":2024},"citing_paper":{"arxiv_id":"2502.08125","last_updated":"2025-02-12T05:06:23Z","snapshot_observed_at":"2026-08-08T10:18:15.644082Z","submitted_at":"2025-02-12T05:06:23Z","title":"Incremental Approximate Single-Source Shortest Paths with Predictions","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-08T10:55:25.812742Z"},"links":{"citing_paper":"/paper/2502.08125"},"observation_digest":"sha256:9f7473a7d6f84e365da59bc9798ecf4d0d79715edc49062c66b3c51d56f7bb61","observation_id":"c1c2fe9c-b6e3-4898-bee8-be3c4e29fb6e","resolution":{"observed_at":"2026-08-08T10:55:26.312127Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T10:55:26.297367Z","title":"Faster matchings via learned duals","venue":null,"work_id":"97635e69-7902-47d9-8103-d49a7b75c2d2","year":2021},"citing_paper":{"arxiv_id":"2502.08125","last_updated":"2025-02-12T05:06:23Z","snapshot_observed_at":"2026-08-08T10:18:15.644082Z","submitted_at":"2025-02-12T05:06:23Z","title":"Incremental Approximate Single-Source Shortest Paths with Predictions","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-08T10:55:25.815982Z"},"links":{"citing_paper":"/paper/2502.08125"},"observation_digest":"sha256:f74aa16bcbf91178d70d8d69d987880e08196159ffbb9557b5d2e033033e5214","observation_id":"0e9e5f3c-2986-48f9-b81c-3de33a0e98db","resolution":{"observed_at":"2026-08-08T10:55:26.301183Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T10:55:26.287726Z","title":"learning","venue":null,"work_id":"9058fb42-fa27-4caf-b0e1-82656119fc17","year":2021},"citing_paper":{"arxiv_id":"2502.08125","last_updated":"2025-02-12T05:06:23Z","snapshot_observed_at":"2026-08-08T10:18:15.644082Z","submitted_at":"2025-02-12T05:06:23Z","title":"Incremental Approximate Single-Source Shortest Paths with Predictions","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-08T10:55:25.819259Z"},"links":{"citing_paper":"/paper/2502.08125"},"observation_digest":"sha256:af1e6d62d22d5293b7a2d44007d56728eecfc1f9761f4d29ca0c35621be2e62a","observation_id":"cf16921f-05d7-480c-9d1a-1f37b5b3d491","resolution":{"observed_at":"2026-08-08T10:55:26.291221Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T10:55:26.278056Z","title":"Deterministic algorithms for decre- mental approximate shortest paths: Faster and simpler","venue":null,"work_id":"a7f22daf-9900-45c9-b48a-366b9f613178","year":2020},"citing_paper":{"arxiv_id":"2502.08125","last_updated":"2025-02-12T05:06:23Z","snapshot_observed_at":"2026-08-08T10:18:15.644082Z","submitted_at":"2025-02-12T05:06:23Z","title":"Incremental Approximate Single-Source Shortest Paths with Predictions","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-08T10:55:25.823371Z"},"links":{"citing_paper":"/paper/2502.08125"},"observation_digest":"sha256:b217936fa1439152a7bb2816742ec57ab20fb9c1b9c3f23cd344820e6453a20d","observation_id":"3a50e329-999b-4c43-9362-19af217c520a","resolution":{"observed_at":"2026-08-08T10:55:26.281264Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T10:55:26.265735Z","title":"Sublinear-time decremental algorithms for single-source reachability and shortest pa ths on directed graphs","venue":null,"work_id":"ce1e51c6-00e3-4e11-8f4c-e9d9ac880972","year":2014},"citing_paper":{"arxiv_id":"2502.08125","last_updated":"2025-02-12T05:06:23Z","snapshot_observed_at":"2026-08-08T10:18:15.644082Z","submitted_at":"2025-02-12T05:06:23Z","title":"Incremental Approximate Single-Source Shortest Paths with Predictions","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-08T10:55:25.826849Z"},"links":{"citing_paper":"/paper/2502.08125"},"observation_digest":"sha256:9a8986599ebab99a5297a0d58727ae6a8ab1666985519dad3c37023b20a9c32d","observation_id":"2fff3f0d-c84e-4fff-bec3-e5fa8e652712","resolution":{"observed_at":"2026-08-08T10:55:26.271430Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T10:55:26.254349Z","title":"Improved algorithms for decremental single-source reachability on directed gr aphs","venue":null,"work_id":"14879d81-f018-4c3b-8473-2a72ba731fe2","year":2015},"citing_paper":{"arxiv_id":"2502.08125","last_updated":"2025-02-12T05:06:23Z","snapshot_observed_at":"2026-08-08T10:18:15.644082Z","submitted_at":"2025-02-12T05:06:23Z","title":"Incremental Approximate Single-Source Shortest Paths with Predictions","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-08T10:55:25.830229Z"},"links":{"citing_paper":"/paper/2502.08125"},"observation_digest":"sha256:a3fd6ef9b6e34b3f779ae1ab336b514bd846ad6acd23b6a5be42e17ad496d3f6","observation_id":"068d3034-7ecc-40f5-ba61-718603201a76","resolution":{"observed_at":"2026-08-08T10:55:26.259019Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T10:55:26.244287Z","title":"Dynamic approximate all-pairs shortest paths: Breaking the o(mn) barrier and de randomization","venue":null,"work_id":"809021da-e27a-49b0-911b-2aed017ec0f3","year":2016},"citing_paper":{"arxiv_id":"2502.08125","last_updated":"2025-02-12T05:06:23Z","snapshot_observed_at":"2026-08-08T10:18:15.644082Z","submitted_at":"2025-02-12T05:06:23Z","title":"Incremental Approximate Single-Source Shortest Paths with Predictions","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-08T10:55:25.833893Z"},"links":{"citing_paper":"/paper/2502.08125"},"observation_digest":"sha256:8490a0bef7128979b5860dd2061ae229685e6715bc75b872cb9211394faa3f1f","observation_id":"55bd8bc1-dba7-4034-9635-47596661f7c9","resolution":{"observed_at":"2026-08-08T10:55:26.247931Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T10:55:26.233882Z","title":"Seybold, and Ch ristopher Y e","venue":null,"work_id":"6376f638-ef82-48ec-8c2b-58de306fab5e","year":2024},"citing_paper":{"arxiv_id":"2502.08125","last_updated":"2025-02-12T05:06:23Z","snapshot_observed_at":"2026-08-08T10:18:15.644082Z","submitted_at":"2025-02-12T05:06:23Z","title":"Incremental Approximate Single-Source Shortest Paths with Predictions","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-08T10:55:25.837387Z"},"links":{"citing_paper":"/paper/2502.08125"},"observation_digest":"sha256:556adc4c3d2fcddf83cc4928c6dfb87e3753e0134463aa0c272bc53c954c4f0e","observation_id":"3738772d-0c7f-4f93-8b0a-1c8e24a56cff","resolution":{"observed_at":"2026-08-08T10:55:26.237637Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T10:55:26.223149Z","title":"Fully dynamic biconnectivity and transitive closure","venue":null,"work_id":"d683a18b-969c-4499-a554-cd2855bf0e11","year":1995},"citing_paper":{"arxiv_id":"2502.08125","last_updated":"2025-02-12T05:06:23Z","snapshot_observed_at":"2026-08-08T10:18:15.644082Z","submitted_at":"2025-02-12T05:06:23Z","title":"Incremental Approximate Single-Source Shortest Paths with Predictions","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-08T10:55:25.840735Z"},"links":{"citing_paper":"/paper/2502.08125"},"observation_digest":"sha256:c1afe4d5b214a59f831cf0356b150547c6dcf60c18ba8f98bd29a7fd8cdb85b1","observation_id":"fc88f56d-586e-4729-befb-c7f203253428","resolution":{"observed_at":"2026-08-08T10:55:26.227293Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T10:55:26.213640Z","title":"Learning-based frequency estimation algorithms","venue":null,"work_id":"ceb7c059-bb4c-472b-8c75-1477fd45ee17","year":2019},"citing_paper":{"arxiv_id":"2502.08125","last_updated":"2025-02-12T05:06:23Z","snapshot_observed_at":"2026-08-08T10:18:15.644082Z","submitted_at":"2025-02-12T05:06:23Z","title":"Incremental Approximate Single-Source Shortest Paths with Predictions","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-08T10:55:25.844054Z"},"links":{"citing_paper":"/paper/2502.08125"},"observation_digest":"sha256:7898e5e4c3c721a969682225506e6c161857479ed08f98ffdf0ee29cb045b480","observation_id":"cd88e2ac-6852-4279-8338-5857da92cbab","resolution":{"observed_at":"2026-08-08T10:55:26.217396Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T10:55:26.204456Z","title":"Online page migration with ML advice","venue":null,"work_id":"fd43ea0c-fad1-42d6-982c-2eded26a0930","year":2022},"citing_paper":{"arxiv_id":"2502.08125","last_updated":"2025-02-12T05:06:23Z","snapshot_observed_at":"2026-08-08T10:18:15.644082Z","submitted_at":"2025-02-12T05:06:23Z","title":"Incremental Approximate Single-Source Shortest Paths with Predictions","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-08T10:55:25.848024Z"},"links":{"citing_paper":"/paper/2502.08125"},"observation_digest":"sha256:375155514cee3143a3070f2405966d8f18cf3aabff0ade963daf9eab2822d3f4","observation_id":"f3154460-665b-4482-a52b-c4b5565f6f8f","resolution":{"observed_at":"2026-08-08T10:55:26.208031Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T10:55:26.194226Z","title":"Onlin e algorithms for weighted paging with predictions","venue":null,"work_id":"5bbf0b79-c08e-4044-b8be-7db7867f5a3d","year":2020},"citing_paper":{"arxiv_id":"2502.08125","last_updated":"2025-02-12T05:06:23Z","snapshot_observed_at":"2026-08-08T10:18:15.644082Z","submitted_at":"2025-02-12T05:06:23Z","title":"Incremental Approximate Single-Source Shortest Paths with Predictions","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-08T10:55:25.851354Z"},"links":{"citing_paper":"/paper/2502.08125"},"observation_digest":"sha256:d8b87ca58131f971a77a85f6bc8e4ef7fef1cf34de442040118eb3221e72e8ec","observation_id":"2f7a9cb2-1578-4f93-a9ac-8a9eb6be599b","resolution":{"observed_at":"2026-08-08T10:55:26.197662Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T10:55:26.183877Z","title":"Chi, Jeffrey Dean, and Neo klis Polyzotis","venue":null,"work_id":"7a4d47cc-d711-453c-a2df-e0f0d50d0b8a","year":2018},"citing_paper":{"arxiv_id":"2502.08125","last_updated":"2025-02-12T05:06:23Z","snapshot_observed_at":"2026-08-08T10:18:15.644082Z","submitted_at":"2025-02-12T05:06:23Z","title":"Incremental Approximate Single-Source Shortest Paths with Predictions","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-08T10:55:25.854634Z"},"links":{"citing_paper":"/paper/2502.08125"},"observation_digest":"sha256:e2ef6a3c2bc2ac294334e7babb6ac417084a346532effa933fc8b0b452682030","observation_id":"20589312-253f-4cda-9b54-5ee922985cfd","resolution":{"observed_at":"2026-08-08T10:55:26.188048Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T10:55:26.173351Z","title":"Incremental sssp for sparse digraphs beyond the hopset barrier","venue":null,"work_id":"8ee2a2c9-4ea8-4c0d-8e4b-b27ff56e13bb","year":2022},"citing_paper":{"arxiv_id":"2502.08125","last_updated":"2025-02-12T05:06:23Z","snapshot_observed_at":"2026-08-08T10:18:15.644082Z","submitted_at":"2025-02-12T05:06:23Z","title":"Incremental Approximate Single-Source Shortest Paths with Predictions","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-08T10:55:25.857925Z"},"links":{"citing_paper":"/paper/2502.08125"},"observation_digest":"sha256:5f7a398fa59e3482a75687b3ea53a9779eba9e49c5c90d08077678f07fb6f126","observation_id":"fe0acc77-4c29-4b24-a893-4cddacd33bd4","resolution":{"observed_at":"2026-08-08T10:55:26.177316Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T10:55:26.163109Z","title":"Speeding up bellman ford via minimum vi- olation permutations","venue":null,"work_id":"bc139bf7-6961-485c-a9da-835ca2fde577","year":2023},"citing_paper":{"arxiv_id":"2502.08125","last_updated":"2025-02-12T05:06:23Z","snapshot_observed_at":"2026-08-08T10:18:15.644082Z","submitted_at":"2025-02-12T05:06:23Z","title":"Incremental Approximate Single-Source Shortest Paths with Predictions","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-08T10:55:25.861068Z"},"links":{"citing_paper":"/paper/2502.08125"},"observation_digest":"sha256:7ee9e3f3c43aa2d52a7434077c3046b2a42c5b60627cf1a868467d1720dfd249","observation_id":"dcc5d991-8d14-4eec-8637-748f38fa98c3","resolution":{"observed_at":"2026-08-08T10:55:26.166950Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T10:55:26.152059Z","title":"Learning aug mented binary search trees","venue":null,"work_id":"f3ffd048-03ba-4c5d-99c6-abbae832e279","year":2022},"citing_paper":{"arxiv_id":"2502.08125","last_updated":"2025-02-12T05:06:23Z","snapshot_observed_at":"2026-08-08T10:18:15.644082Z","submitted_at":"2025-02-12T05:06:23Z","title":"Incremental Approximate Single-Source Shortest Paths with Predictions","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-08T10:55:25.864359Z"},"links":{"citing_paper":"/paper/2502.08125"},"observation_digest":"sha256:26ac91601d938c7a13b88630a5ecad123f768b1bf7458e95be65383e65cdc958","observation_id":"1747e776-5892-4d4d-bebd-6ae16b7ee1f1","resolution":{"observed_at":"2026-08-08T10:55:26.156021Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T10:55:26.140971Z","title":"Woodruff","venue":null,"work_id":"544b2a40-df15-4f42-b5cc-b7e3b4f7b905","year":2022},"citing_paper":{"arxiv_id":"2502.08125","last_updated":"2025-02-12T05:06:23Z","snapshot_observed_at":"2026-08-08T10:18:15.644082Z","submitted_at":"2025-02-12T05:06:23Z","title":"Incremental Approximate Single-Source Shortest Paths with Predictions","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-08T10:55:25.867583Z"},"links":{"citing_paper":"/paper/2502.08125"},"observation_digest":"sha256:0a28e79767ef431373069e6953f3cc74fa9c2a9bdf1c484abedd1864117cbf8b","observation_id":"e9447ebf-7246-496c-8635-462f76e73616","resolution":{"observed_at":"2026-08-08T10:55:26.144383Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T10:55:26.129813Z","title":"Liu and V aidehi Srinivas","venue":null,"work_id":"94716f6d-4d5d-40b4-8ee1-ec44d550ffc9","year":2024},"citing_paper":{"arxiv_id":"2502.08125","last_updated":"2025-02-12T05:06:23Z","snapshot_observed_at":"2026-08-08T10:18:15.644082Z","submitted_at":"2025-02-12T05:06:23Z","title":"Incremental Approximate Single-Source Shortest Paths with Predictions","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-08T10:55:25.871127Z"},"links":{"citing_paper":"/paper/2502.08125"},"observation_digest":"sha256:ce94d5dca73c98c3b73d89ff6ef13747efb11c0f3b01efa3e521a6786cfec639","observation_id":"4f3f2f2d-dde3-4ded-aaf1-fac221fcf170","resolution":{"observed_at":"2026-08-08T10:55:26.134542Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T10:55:26.119029Z","title":"Competit ive caching with machine learned advice","venue":null,"work_id":"505b28b5-34f7-4e00-b880-19ef076270b5","year":2021},"citing_paper":{"arxiv_id":"2502.08125","last_updated":"2025-02-12T05:06:23Z","snapshot_observed_at":"2026-08-08T10:18:15.644082Z","submitted_at":"2025-02-12T05:06:23Z","title":"Incremental Approximate Single-Source Shortest Paths with Predictions","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-08T10:55:25.874982Z"},"links":{"citing_paper":"/paper/2502.08125"},"observation_digest":"sha256:3715d341141879da9a43b11fcd0bb41e6e9b36929180afca3b9503c7bf6099fc","observation_id":"c624940f-924c-47f9-8726-f3ecf7a7164b","resolution":{"observed_at":"2026-08-08T10:55:26.122825Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T10:55:26.107911Z","title":"Faster approximation schemes for fr actional multicommodity flow problems via dynamic graph algorithms","venue":null,"work_id":"d58d3c61-a56e-4a06-8bb9-4d7ee7f300b1","year":2010},"citing_paper":{"arxiv_id":"2502.08125","last_updated":"2025-02-12T05:06:23Z","snapshot_observed_at":"2026-08-08T10:18:15.644082Z","submitted_at":"2025-02-12T05:06:23Z","title":"Incremental Approximate Single-Source Shortest Paths with Predictions","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-08T10:55:25.878126Z"},"links":{"citing_paper":"/paper/2502.08125"},"observation_digest":"sha256:521057341936eddc69ff52d386073e4d81b6a09ac493c37e4187b677109d7a14","observation_id":"01f3b65b-f8a2-4b6c-838b-82864f6922ea","resolution":{"observed_at":"2026-08-08T10:55:26.112217Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T10:55:26.097794Z","title":"Online list labeling with predictions","venue":null,"work_id":"0e7075f3-8f14-4d9e-9b56-02bb3b60f927","year":2023},"citing_paper":{"arxiv_id":"2502.08125","last_updated":"2025-02-12T05:06:23Z","snapshot_observed_at":"2026-08-08T10:18:15.644082Z","submitted_at":"2025-02-12T05:06:23Z","title":"Incremental Approximate Single-Source Shortest Paths with Predictions","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-08T10:55:25.881344Z"},"links":{"citing_paper":"/paper/2502.08125"},"observation_digest":"sha256:01bd3b2ed2021cf4031a503b51b543d955f60ad170df8bc1f82b1b89cc18fc4a","observation_id":"4224e90c-405d-45ec-bba9-5160475b68f6","resolution":{"observed_at":"2026-08-08T10:55:26.101305Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T10:55:26.088236Z","title":"Incremental topological ordering and cycle detection with predictions","venue":null,"work_id":"c7c95d1d-b9e9-4be5-b505-60b6c1183d33","year":2024},"citing_paper":{"arxiv_id":"2502.08125","last_updated":"2025-02-12T05:06:23Z","snapshot_observed_at":"2026-08-08T10:18:15.644082Z","submitted_at":"2025-02-12T05:06:23Z","title":"Incremental Approximate Single-Source Shortest Paths with Predictions","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-08T10:55:25.884621Z"},"links":{"citing_paper":"/paper/2502.08125"},"observation_digest":"sha256:2891443177feb90b4d47a4e898495e343ca4ed4ca49cdce9d18a39a133f7f3c8","observation_id":"14405ccd-daa7-40d0-a36f-c2e8f0bb3fbd","resolution":{"observed_at":"2026-08-08T10:55:26.091906Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T10:55:26.077475Z","title":"A model for learned bloom filters and optimizing by sandwiching","venue":null,"work_id":"4049a249-2742-43ad-b93c-17ae85d55746","year":2018},"citing_paper":{"arxiv_id":"2502.08125","last_updated":"2025-02-12T05:06:23Z","snapshot_observed_at":"2026-08-08T10:18:15.644082Z","submitted_at":"2025-02-12T05:06:23Z","title":"Incremental Approximate Single-Source Shortest Paths with Predictions","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-08T10:55:25.888253Z"},"links":{"citing_paper":"/paper/2502.08125"},"observation_digest":"sha256:710379db468d22817e59764efbae3740309be496a1d558c7345b31a0b24efb06","observation_id":"216f84a6-40d4-47ad-af4d-ccef42e750f2","resolution":{"observed_at":"2026-08-08T10:55:26.081635Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T10:55:26.067027Z","title":"Fully-dynamic-to- incremental reductions with known deletion order (e.g","venue":null,"work_id":"046b1998-8b21-4f1e-9261-157736596d65","year":2023},"citing_paper":{"arxiv_id":"2502.08125","last_updated":"2025-02-12T05:06:23Z","snapshot_observed_at":"2026-08-08T10:18:15.644082Z","submitted_at":"2025-02-12T05:06:23Z","title":"Incremental Approximate Single-Source Shortest Paths with Predictions","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-08T10:55:25.891672Z"},"links":{"citing_paper":"/paper/2502.08125"},"observation_digest":"sha256:9432cd58baac57596f8db360c691eaf210d9771b4ad202382777a3570bf9c4ae","observation_id":"deb7098a-4355-4c7f-b0ef-def194307e55","resolution":{"observed_at":"2026-08-08T10:55:26.070837Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T10:55:26.056974Z","title":"Learning-augmented maximum flow","venue":null,"work_id":"bbba6f7a-914a-47bd-b27a-71e742c250f6","year":2024},"citing_paper":{"arxiv_id":"2502.08125","last_updated":"2025-02-12T05:06:23Z","snapshot_observed_at":"2026-08-08T10:18:15.644082Z","submitted_at":"2025-02-12T05:06:23Z","title":"Incremental Approximate Single-Source Shortest Paths with Predictions","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-08T10:55:25.894660Z"},"links":{"citing_paper":"/paper/2502.08125"},"observation_digest":"sha256:6300b61195798bd0abc27c2167de45534fb97c6f7d478a83f263c09ac5b62e27","observation_id":"1e61f0a4-e683-4df6-aa42-25251671c9fb","resolution":{"observed_at":"2026-08-08T10:55:26.060375Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T10:55:26.047221Z","title":"New algorithms and hardness for incremental single-source shortest paths in directed graphs","venue":null,"work_id":"7ff7b465-1eb8-4f42-b372-16e15d88ccc2","year":2020},"citing_paper":{"arxiv_id":"2502.08125","last_updated":"2025-02-12T05:06:23Z","snapshot_observed_at":"2026-08-08T10:18:15.644082Z","submitted_at":"2025-02-12T05:06:23Z","title":"Incremental Approximate Single-Source Shortest Paths with Predictions","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-08T10:55:25.897729Z"},"links":{"citing_paper":"/paper/2502.08125"},"observation_digest":"sha256:0f7f90ac455fd6f67facfd41a57d6287d35761279d5a884d92c9d66279e45b1d","observation_id":"d3a15a3b-0ebf-4ae5-ac6b-7a80aae7b696","resolution":{"observed_at":"2026-08-08T10:55:26.050702Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T10:55:26.037669Z","title":"On dynamic shortest paths pr oblems","venue":null,"work_id":"4375fa1e-93e5-485b-828c-9d19654d1614","year":2011},"citing_paper":{"arxiv_id":"2502.08125","last_updated":"2025-02-12T05:06:23Z","snapshot_observed_at":"2026-08-08T10:18:15.644082Z","submitted_at":"2025-02-12T05:06:23Z","title":"Incremental Approximate Single-Source Shortest Paths with Predictions","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-08T10:55:25.901369Z"},"links":{"citing_paper":"/paper/2502.08125"},"observation_digest":"sha256:6f6d2933254aad3a3a34878925180960a93c5530461ec342320a1a31cc425be4","observation_id":"aeb706c4-774b-4ad5-8436-977dc6b7b1e2","resolution":{"observed_at":"2026-08-08T10:55:26.041113Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T10:55:26.028083Z","title":"Discrete-convex-anal ysis-based framework for warm-starting algorithms with predictions","venue":null,"work_id":"ad7dd929-2753-457a-ae36-8dd8348fd9a4","year":2022},"citing_paper":{"arxiv_id":"2502.08125","last_updated":"2025-02-12T05:06:23Z","snapshot_observed_at":"2026-08-08T10:18:15.644082Z","submitted_at":"2025-02-12T05:06:23Z","title":"Incremental Approximate Single-Source Shortest Paths with Predictions","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-08T10:55:25.904459Z"},"links":{"citing_paper":"/paper/2502.08125"},"observation_digest":"sha256:a629ae206753d260a02935f09017414128cb53a6de1e114c427d768d4ee41e6b","observation_id":"a78040eb-1804-42ca-8a0a-91b12ab55392","resolution":{"observed_at":"2026-08-08T10:55:26.031387Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T10:55:26.018127Z","title":"An on-line edge-deleti on problem","venue":null,"work_id":"51ee4242-2e39-4597-bc69-3c9abbf7fe03","year":1981},"citing_paper":{"arxiv_id":"2502.08125","last_updated":"2025-02-12T05:06:23Z","snapshot_observed_at":"2026-08-08T10:18:15.644082Z","submitted_at":"2025-02-12T05:06:23Z","title":"Incremental Approximate Single-Source Shortest Paths with Predictions","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-08T10:55:25.907556Z"},"links":{"citing_paper":"/paper/2502.08125"},"observation_digest":"sha256:587eaf30cd2c9e033bc1f7df16985f84f566f6ac767daeae0859f8a5040edeac","observation_id":"6c9b7bf1-aad0-4820-97f5-42701ddc01de","resolution":{"observed_at":"2026-08-08T10:55:26.022122Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T10:55:26.007121Z","title":"warm start","venue":null,"work_id":"66b03bdc-121d-405f-8b63-70c4507ace4b","year":2025},"citing_paper":{"arxiv_id":"2502.08125","last_updated":"2025-02-12T05:06:23Z","snapshot_observed_at":"2026-08-08T10:18:15.644082Z","submitted_at":"2025-02-12T05:06:23Z","title":"Incremental Approximate Single-Source Shortest Paths with Predictions","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-08T10:55:25.910803Z"},"links":{"citing_paper":"/paper/2502.08125"},"observation_digest":"sha256:c5b7145f0ebefb7db098d76ca0b5a86099c72205201676a0a3a96e1362b8f073","observation_id":"7548846b-3e5c-46df-94f1-1e380353d9de","resolution":{"observed_at":"2026-08-08T10:55:26.011581Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T10:55:25.997298Z","title":"Partitioned learned bloom filters","venue":null,"work_id":"9eaa94d2-bc69-4d71-9d5f-2bd40080c6c0","year":2021},"citing_paper":{"arxiv_id":"2502.08125","last_updated":"2025-02-12T05:06:23Z","snapshot_observed_at":"2026-08-08T10:18:15.644082Z","submitted_at":"2025-02-12T05:06:23Z","title":"Incremental Approximate Single-Source Shortest Paths with Predictions","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-08T10:55:25.914656Z"},"links":{"citing_paper":"/paper/2502.08125"},"observation_digest":"sha256:67899274335ec7bbf56f9954da2c640be8746b0948056bbc23296364b86f5330","observation_id":"e19052ba-25f5-463c-a9a7-539a33821124","resolution":{"observed_at":"2026-08-08T10:55:26.000638Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T10:55:25.987410Z","title":"On dynamic graph algorithms with predictions","venue":null,"work_id":"2a6c5267-a490-4f04-9bbe-e02501f4854b","year":2024},"citing_paper":{"arxiv_id":"2502.08125","last_updated":"2025-02-12T05:06:23Z","snapshot_observed_at":"2026-08-08T10:18:15.644082Z","submitted_at":"2025-02-12T05:06:23Z","title":"Incremental Approximate Single-Source Shortest Paths with Predictions","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-08T10:55:25.918046Z"},"links":{"citing_paper":"/paper/2502.08125"},"observation_digest":"sha256:eb1509b6242284bd1683758070be6786552baa5c864cae16816b3a1c86778893","observation_id":"fdbf5334-f3c9-4ee6-895a-bd2f13ffaea4","resolution":{"observed_at":"2026-08-08T10:55:25.990926Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T10:55:25.976625Z","title":"Robust learning-augmented dictionaries","venue":null,"work_id":"5ef0b61e-8754-4b9f-ba06-070d8b607420","year":2024},"citing_paper":{"arxiv_id":"2502.08125","last_updated":"2025-02-12T05:06:23Z","snapshot_observed_at":"2026-08-08T10:18:15.644082Z","submitted_at":"2025-02-12T05:06:23Z","title":"Incremental Approximate Single-Source Shortest Paths with Predictions","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-08T10:55:25.921173Z"},"links":{"citing_paper":"/paper/2502.08125"},"observation_digest":"sha256:6de8163a96cc245b7b3b8face910c74dd2cdeab3920027b54ec7b25663aedeaf","observation_id":"735800ed-7cc6-48fa-8c22-221966108f7a","resolution":{"observed_at":"2026-08-08T10:55:25.979959Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-08T10:55:25.966055Z","title":"Robust learning-augmented dictionaries","venue":null,"work_id":"c66233bb-b2c0-4c48-a4d4-2d4a1cf176e9","year":2024},"citing_paper":{"arxiv_id":"2502.08125","last_updated":"2025-02-12T05:06:23Z","snapshot_observed_at":"2026-08-08T10:18:15.644082Z","submitted_at":"2025-02-12T05:06:23Z","title":"Incremental Approximate Single-Source Shortest Paths with Predictions","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-08T10:55:25.924794Z"},"links":{"citing_paper":"/paper/2502.08125"},"observation_digest":"sha256:321287efa54efc38e8ad6840705ce5f2b91830914f385223b0cb19b59bae02a2","observation_id":"30d6551c-1cc5-49ac-8f67-137089cdeee4","resolution":{"observed_at":"2026-08-08T10:55:25.970270Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2502.08125","last_updated":"2025-02-12T05:06:23Z","latest_version":1,"primary_category":"cs.DS","snapshot_observed_at":"2026-08-08T10:18:15.644082Z","submitted_at":"2025-02-12T05:06:23Z","title":"Incremental Approximate Single-Source Shortest Paths with Predictions"},"reference_resolution":{"displayed":47,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":1,"verified_fuzzy":46},"total_outbound_references":47},"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":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"thesis":"As of 12 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 1 inbound Pith citation observation for arXiv:2502.08125."}