{"as_of":"2026-08-07T12:39:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:5890f896a349b06cfec259feb10009914a0a3343afb1facc43ece3b23dd70618","coverage":[{"denominator":31,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":31,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T17:49:11.446253Z","state":"measured"},{"denominator":31,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":31,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+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/2507.09952/citation-record","integrity":"/paper/2507.09952/integrity","json":"/paper/2507.09952/citation-record.json","paper":"/paper/2507.09952"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:49:15.318594Z","title":"Fab: content-based, collaborative recommendation","venue":null,"work_id":"2f324fe6-196e-4bcb-99e4-0d38b29fa271","year":1997},"citing_paper":{"arxiv_id":"2507.09952","last_updated":"2025-07-14T06:01:58Z","snapshot_observed_at":"2026-08-06T17:40:51.020249Z","submitted_at":"2025-07-14T06:01:58Z","title":"Radial Neighborhood Smoothing Recommender System","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-06T17:49:09.560185Z"},"links":{"citing_paper":"/paper/2507.09952"},"observation_digest":"sha256:fac0341082a01558b8a7ebd984a2eb915db9db6126229a07f918b7bfc45bedb0","observation_id":"62510301-a3b6-4dff-afe3-11fcc22b6f94","resolution":{"observed_at":"2026-08-06T17:49:15.350625Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T17:49:15.207460Z","title":"Scalable collaborative filtering with jointly derived neighborhood interpolation weights","venue":null,"work_id":"5ba37693-8d3b-486f-bcd3-3b530bf0136e","year":2007},"citing_paper":{"arxiv_id":"2507.09952","last_updated":"2025-07-14T06:01:58Z","snapshot_observed_at":"2026-08-06T17:40:51.020249Z","submitted_at":"2025-07-14T06:01:58Z","title":"Radial Neighborhood Smoothing Recommender System","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-06T17:49:09.600901Z"},"links":{"citing_paper":"/paper/2507.09952"},"observation_digest":"sha256:1815dd9686368c07cd66a3f08d6a0c8b455ae65ef11473f7a6198bd0ba0cd0fe","observation_id":"7cda124d-c7b5-4ef3-b196-29f14833510b","resolution":{"observed_at":"2026-08-06T17:49:15.254125Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T17:49:09.662208Z","title":"Ellis, Brian Whitman, and Paul Lamere","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2507.09952","last_updated":"2025-07-14T06:01:58Z","snapshot_observed_at":"2026-08-06T17:40:51.020249Z","submitted_at":"2025-07-14T06:01:58Z","title":"Radial Neighborhood Smoothing Recommender System","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-06T17:49:09.662208Z"},"links":{"citing_paper":"/paper/2507.09952"},"observation_digest":"sha256:d2568dd5403e73a5faa4b86ce225e175913a7607104ead9f7651b264c012cca6","observation_id":"be22a36c-9be0-4396-85eb-77b492a67be1","resolution":{"observed_at":"2026-08-06T17:49:09.662208Z","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":"2026-08-06T17:49:15.082480Z","title":"User modeling for adaptive news access","venue":null,"work_id":"36543f97-f489-431e-88d9-5cb34fbb9953","year":2000},"citing_paper":{"arxiv_id":"2507.09952","last_updated":"2025-07-14T06:01:58Z","snapshot_observed_at":"2026-08-06T17:40:51.020249Z","submitted_at":"2025-07-14T06:01:58Z","title":"Radial Neighborhood Smoothing Recommender System","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-06T17:49:09.714187Z"},"links":{"citing_paper":"/paper/2507.09952"},"observation_digest":"sha256:13759e3bb752a6cff4b0750e126a7c42da3dd336baf72073b0e356b1e53eb58f","observation_id":"12a5e561-2702-46c7-b6b3-0ec2b770184a","resolution":{"observed_at":"2026-08-06T17:49:15.129963Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T17:49:14.989029Z","title":"Thy friend is my friend: Iterative collaborative filtering for sparse matrix estimation","venue":null,"work_id":"f7b77e07-ac15-42a5-95eb-34aa4de2d00f","year":2017},"citing_paper":{"arxiv_id":"2507.09952","last_updated":"2025-07-14T06:01:58Z","snapshot_observed_at":"2026-08-06T17:40:51.020249Z","submitted_at":"2025-07-14T06:01:58Z","title":"Radial Neighborhood Smoothing Recommender System","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-06T17:49:09.759434Z"},"links":{"citing_paper":"/paper/2507.09952"},"observation_digest":"sha256:145d1bf256992a2cf08aa4c7a74f22020b7ff3938095542c37cc5b622de04ed1","observation_id":"c6b3f510-55c8-456a-a716-12383cb9cce1","resolution":{"observed_at":"2026-08-06T17:49:15.027002Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T17:49:09.817795Z","title":"A singular value thresholding algorithm for matrix completion","venue":null,"work_id":null,"year":1956},"citing_paper":{"arxiv_id":"2507.09952","last_updated":"2025-07-14T06:01:58Z","snapshot_observed_at":"2026-08-06T17:40:51.020249Z","submitted_at":"2025-07-14T06:01:58Z","title":"Radial Neighborhood Smoothing Recommender System","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-06T17:49:09.817795Z"},"links":{"citing_paper":"/paper/2507.09952"},"observation_digest":"sha256:6b70d662074a2b90d78bf18738ddc22619236a5dd688d3ac7db6d3534c52e2ae","observation_id":"3c6769e9-4a80-4a79-a924-1cff0dbc5cc6","resolution":{"observed_at":"2026-08-06T17:49:09.817795Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:49:09.902319Z","title":"Exact matrix completion via convex optimization","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2507.09952","last_updated":"2025-07-14T06:01:58Z","snapshot_observed_at":"2026-08-06T17:40:51.020249Z","submitted_at":"2025-07-14T06:01:58Z","title":"Radial Neighborhood Smoothing Recommender System","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-06T17:49:09.902319Z"},"links":{"citing_paper":"/paper/2507.09952"},"observation_digest":"sha256:0e4f27331facbeea03f1e98331e408d39a628b21577d477fbc48a42d1208880a","observation_id":"18a56ce6-57cd-4557-8da5-28bf35265f8c","resolution":{"observed_at":"2026-08-06T17:49:09.902319Z","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":"2026-08-06T17:49:14.847475Z","title":"The power of convex relaxation: Near-optimal matrix completion","venue":null,"work_id":"cd1f3393-9957-4932-a6b8-a60b44980b9d","year":2010},"citing_paper":{"arxiv_id":"2507.09952","last_updated":"2025-07-14T06:01:58Z","snapshot_observed_at":"2026-08-06T17:40:51.020249Z","submitted_at":"2025-07-14T06:01:58Z","title":"Radial Neighborhood Smoothing Recommender System","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-06T17:49:09.944319Z"},"links":{"citing_paper":"/paper/2507.09952"},"observation_digest":"sha256:bb4d83aabe2db3b6c7cf4709ee0cade7605e3d58d05047273c11ca78c9cfc9b9","observation_id":"9beb9cfd-b25d-4fbd-b886-afb215851086","resolution":{"observed_at":"2026-08-06T17:49:14.897330Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2010.03240","last_updated":"2021-12-29T08:43:19Z","snapshot_observed_at":"2026-07-06T10:02:14.183940Z","submitted_at":"2020-10-07T07:44:30Z","title":"Bias and Debias in Recommender System: A Survey and Future Directions","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.03240","snapshot_observed_at":"2026-08-06T17:49:10.002617Z","title":"Bias and debias in recommender system: A survey and future directions","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2507.09952","last_updated":"2025-07-14T06:01:58Z","snapshot_observed_at":"2026-08-06T17:40:51.020249Z","submitted_at":"2025-07-14T06:01:58Z","title":"Radial Neighborhood Smoothing Recommender System","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-06T17:49:10.002617Z"},"links":{"cited_paper":"/paper/2010.03240","citing_paper":"/paper/2507.09952"},"observation_digest":"sha256:a831fd6e7b2c89a88ad648dfdf8d65200e131232d6d59cd5b17359fe6455c5e6","observation_id":"2a735139-18da-4575-947f-82af1037d8d0","resolution":{"observed_at":"2026-08-06T17:49:10.002617Z","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":"2026-08-06T17:49:14.730135Z","title":"Smooth neighborhood recommender systems","venue":null,"work_id":"76a53fad-cd06-460e-867d-18c9a83dcb16","year":2019},"citing_paper":{"arxiv_id":"2507.09952","last_updated":"2025-07-14T06:01:58Z","snapshot_observed_at":"2026-08-06T17:40:51.020249Z","submitted_at":"2025-07-14T06:01:58Z","title":"Radial Neighborhood Smoothing Recommender System","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-06T17:49:10.067684Z"},"links":{"citing_paper":"/paper/2507.09952"},"observation_digest":"sha256:8d5bf44a4075b859c99e77390ba26bf0b1a993358f34e992e9e0b0e745f35664","observation_id":"c99546ff-918a-4cd5-8c08-4a605f0821dd","resolution":{"observed_at":"2026-08-06T17:49:14.777161Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T17:49:14.563176Z","title":"A comprehensive survey of neighborhood-based recommendation methods","venue":null,"work_id":"54da2310-4846-4b43-9155-3b3c646da9a0","year":2011},"citing_paper":{"arxiv_id":"2507.09952","last_updated":"2025-07-14T06:01:58Z","snapshot_observed_at":"2026-08-06T17:40:51.020249Z","submitted_at":"2025-07-14T06:01:58Z","title":"Radial Neighborhood Smoothing Recommender System","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-06T17:49:10.104623Z"},"links":{"citing_paper":"/paper/2507.09952"},"observation_digest":"sha256:3019c30c81ca4a8ec8fa5bc11fcd21c568ef9547d499b12804c03425bd8f0b3a","observation_id":"8da44a11-5ccc-4890-90ec-66b16ffbdf7d","resolution":{"observed_at":"2026-08-06T17:49:14.620591Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T17:49:14.397489Z","title":"Trade-offs between machine learning and deep learning for mental illness detection on social media","venue":null,"work_id":"1be71c4c-eb7d-4d9d-8921-9a23a50e8b97","year":2025},"citing_paper":{"arxiv_id":"2507.09952","last_updated":"2025-07-14T06:01:58Z","snapshot_observed_at":"2026-08-06T17:40:51.020249Z","submitted_at":"2025-07-14T06:01:58Z","title":"Radial Neighborhood Smoothing Recommender System","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-06T17:49:10.160539Z"},"links":{"citing_paper":"/paper/2507.09952"},"observation_digest":"sha256:f93656b21e87b3dda9248ac5b141e87da364113bc847d64cbc9706ab203a879b","observation_id":"d472b2f9-41ea-4fed-9418-de3226f0789f","resolution":{"observed_at":"2026-08-06T17:49:14.469395Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T17:49:14.265210Z","title":"Using collaborative filtering to weave an information tapestry","venue":null,"work_id":"5042c28d-ab58-4ea9-8a11-16c550fad3c9","year":1992},"citing_paper":{"arxiv_id":"2507.09952","last_updated":"2025-07-14T06:01:58Z","snapshot_observed_at":"2026-08-06T17:40:51.020249Z","submitted_at":"2025-07-14T06:01:58Z","title":"Radial Neighborhood Smoothing Recommender System","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-06T17:49:10.210546Z"},"links":{"citing_paper":"/paper/2507.09952"},"observation_digest":"sha256:11c33a6ccc754737f864eff376fc5bf1860144adf1e1f6980190921e430e0d94","observation_id":"d88843c7-90a1-44b1-aa98-07fc33184fb3","resolution":{"observed_at":"2026-08-06T17:49:14.339814Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T17:49:14.128484Z","title":"Eigentaste: A constant time collaborative filtering algorithm","venue":null,"work_id":"536549c1-916f-4658-9538-41ded8d80195","year":2001},"citing_paper":{"arxiv_id":"2507.09952","last_updated":"2025-07-14T06:01:58Z","snapshot_observed_at":"2026-08-06T17:40:51.020249Z","submitted_at":"2025-07-14T06:01:58Z","title":"Radial Neighborhood Smoothing Recommender System","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-06T17:49:10.243550Z"},"links":{"citing_paper":"/paper/2507.09952"},"observation_digest":"sha256:2b9daad378cf13b1830e86f6b82c66b8ce63d6e453d6ed5e3ec2b0186de35b99","observation_id":"a5032063-3f26-485a-b135-2a7a3ef8c236","resolution":{"observed_at":"2026-08-06T17:49:14.176426Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T17:49:10.300162Z","title":"The movielens datasets: History and context","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2507.09952","last_updated":"2025-07-14T06:01:58Z","snapshot_observed_at":"2026-08-06T17:40:51.020249Z","submitted_at":"2025-07-14T06:01:58Z","title":"Radial Neighborhood Smoothing Recommender System","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-06T17:49:10.300162Z"},"links":{"citing_paper":"/paper/2507.09952"},"observation_digest":"sha256:9585c4e48283773e3f31281f99d2178364b516576b9a9af5c5d152eac63370ca","observation_id":"ebd6ab81-7d08-4bb5-9690-a937095aa5a9","resolution":{"observed_at":"2026-08-06T17:49:10.300162Z","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":"2026-08-06T17:49:13.944743Z","title":"Encoder: Entity mining and modification relation binding for composed image retrieval","venue":null,"work_id":"58bd881d-9661-46c7-a400-0e5564c8d208","year":2025},"citing_paper":{"arxiv_id":"2507.09952","last_updated":"2025-07-14T06:01:58Z","snapshot_observed_at":"2026-08-06T17:40:51.020249Z","submitted_at":"2025-07-14T06:01:58Z","title":"Radial Neighborhood Smoothing Recommender System","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-06T17:49:10.350924Z"},"links":{"citing_paper":"/paper/2507.09952"},"observation_digest":"sha256:96d37f77672b0b89020357f021217e983ce6f3bb48f49e69366b9a6e7b9ca596","observation_id":"ab84528c-6191-4f16-a87a-29862aa2c202","resolution":{"observed_at":"2026-08-06T17:49:14.015832Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.21309","last_updated":"2025-03-27T09:34:21Z","snapshot_observed_at":"2026-07-06T20:59:31.273397Z","submitted_at":"2025-03-27T09:34:21Z","title":"FineCIR: Explicit Parsing of Fine-Grained Modification Semantics for Composed Image Retrieval","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.21309","snapshot_observed_at":"2026-08-06T17:49:10.380802Z","title":"Finecir: Explicit parsing of fine-grained modification semantics for composed image retrieval","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.09952","last_updated":"2025-07-14T06:01:58Z","snapshot_observed_at":"2026-08-06T17:40:51.020249Z","submitted_at":"2025-07-14T06:01:58Z","title":"Radial Neighborhood Smoothing Recommender System","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-06T17:49:10.380802Z"},"links":{"cited_paper":"/paper/2503.21309","citing_paper":"/paper/2507.09952"},"observation_digest":"sha256:e143425f3ba0adb107606a1bb3d7169ef69da13b3272360e274e7406badbf7f1","observation_id":"313445bc-099a-4e2e-b638-844516952af9","resolution":{"observed_at":"2026-08-06T17:49:10.380802Z","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":"2026-08-06T17:49:13.797614Z","title":null,"venue":null,"work_id":"834f3cb5-5561-44f8-a3f3-fbc4676bf443","year":2003},"citing_paper":{"arxiv_id":"2507.09952","last_updated":"2025-07-14T06:01:58Z","snapshot_observed_at":"2026-08-06T17:40:51.020249Z","submitted_at":"2025-07-14T06:01:58Z","title":"Radial Neighborhood Smoothing Recommender System","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-06T17:49:10.430702Z"},"links":{"citing_paper":"/paper/2507.09952"},"observation_digest":"sha256:0c3da860c645d7f7631509ba71d568a9b4bc6a7e72c8163a6b775027b954daf7","observation_id":"343b8dc4-b379-4faf-815c-2b24471b19b9","resolution":{"observed_at":"2026-08-06T17:49:13.856796Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T17:49:13.627398Z","title":"Matrix completion with covariate information","venue":null,"work_id":"d0222e03-14f8-4175-827d-cf72e24ce2c5","year":2019},"citing_paper":{"arxiv_id":"2507.09952","last_updated":"2025-07-14T06:01:58Z","snapshot_observed_at":"2026-08-06T17:40:51.020249Z","submitted_at":"2025-07-14T06:01:58Z","title":"Radial Neighborhood Smoothing Recommender System","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-06T17:49:10.489592Z"},"links":{"citing_paper":"/paper/2507.09952"},"observation_digest":"sha256:ad463dd97390fdfd28e8d7193834687996a5fbcb66b799e3f72c9d424e2e260a","observation_id":"a8d0616d-c4a9-4771-818d-50243637e6f1","resolution":{"observed_at":"2026-08-06T17:49:13.713312Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T17:49:13.437989Z","title":"Collaborative prediction and ranking with non-random missing data","venue":null,"work_id":"5bebb5b2-9ecf-4233-b10f-2f419c8f0a86","year":2009},"citing_paper":{"arxiv_id":"2507.09952","last_updated":"2025-07-14T06:01:58Z","snapshot_observed_at":"2026-08-06T17:40:51.020249Z","submitted_at":"2025-07-14T06:01:58Z","title":"Radial Neighborhood Smoothing Recommender System","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-06T17:49:10.531484Z"},"links":{"citing_paper":"/paper/2507.09952"},"observation_digest":"sha256:58e1fcd36f4a57cd39b8bd1ff8f91d874d4624d46f97ac39fc321762deb46aae","observation_id":"870b2099-262d-430f-9cca-ded9151e885c","resolution":{"observed_at":"2026-08-06T17:49:13.500707Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T17:49:13.277232Z","title":"Spectral regularization algorithms for learning large incomplete matrices","venue":null,"work_id":"2e3719c0-eb00-418f-8202-835c767ab195","year":2010},"citing_paper":{"arxiv_id":"2507.09952","last_updated":"2025-07-14T06:01:58Z","snapshot_observed_at":"2026-08-06T17:40:51.020249Z","submitted_at":"2025-07-14T06:01:58Z","title":"Radial Neighborhood Smoothing Recommender System","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-06T17:49:10.576074Z"},"links":{"citing_paper":"/paper/2507.09952"},"observation_digest":"sha256:ff7865d2d89747790d99f9bf9fcddbd7bc927bd8e5c7e54f8e1eef0d9ba5c0d1","observation_id":"63a63684-372e-49db-8006-3d07b03c08f2","resolution":{"observed_at":"2026-08-06T17:49:13.335611Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.12199","last_updated":"2024-11-12T07:28:08Z","snapshot_observed_at":"2026-07-06T18:32:40.207270Z","submitted_at":"2024-06-18T01:55:37Z","title":"Time Series Modeling for Heart Rate Prediction: From ARIMA to Transformers","version":3},"cited_work":{"arxiv_id":"2406.12199","doi":null,"metadata_source":"pith","pith_arxiv_id":"2406.12199","snapshot_observed_at":"2026-08-06T17:49:12.156114Z","title":"Time Series Modeling for Heart Rate Prediction: From ARIMA to Transformers","venue":"cs.LG","work_id":"2218dc67-ada5-470d-a8f2-80634bd0ce9c","year":2024},"citing_paper":{"arxiv_id":"2507.09952","last_updated":"2025-07-14T06:01:58Z","snapshot_observed_at":"2026-08-06T17:40:51.020249Z","submitted_at":"2025-07-14T06:01:58Z","title":"Radial Neighborhood Smoothing Recommender System","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-06T17:49:10.629234Z"},"links":{"cited_paper":"/paper/2406.12199","citing_paper":"/paper/2507.09952"},"observation_digest":"sha256:12d331511e53519b0bcd33ad1a02b7a1c3b5d474e4560a033eb0089c514f3199","observation_id":"4d0ce80a-e28c-4e94-bf6b-dbdc9ba3628d","resolution":{"observed_at":"2026-08-06T17:49:12.253237Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T17:49:13.094834Z","title":"A comprehensive survey of neighborhood-based recommendation methods","venue":null,"work_id":"3ca08b41-c587-41da-b52f-843fd8e2856c","year":2015},"citing_paper":{"arxiv_id":"2507.09952","last_updated":"2025-07-14T06:01:58Z","snapshot_observed_at":"2026-08-06T17:40:51.020249Z","submitted_at":"2025-07-14T06:01:58Z","title":"Radial Neighborhood Smoothing Recommender System","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-06T17:49:10.682560Z"},"links":{"citing_paper":"/paper/2507.09952"},"observation_digest":"sha256:bc444ffa0efbe71e010a61b58a4104f4dcc5521d6f2987f793fcb3e8384bf0ce","observation_id":"e3af6378-a26f-4d28-812e-a63aed98a733","resolution":{"observed_at":"2026-08-06T17:49:13.171116Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T17:49:12.900443Z","title":"Fast maximum margin matrix factorization for collaborative prediction","venue":null,"work_id":"e47681eb-0091-4afc-b3a7-a71e344c8efd","year":2005},"citing_paper":{"arxiv_id":"2507.09952","last_updated":"2025-07-14T06:01:58Z","snapshot_observed_at":"2026-08-06T17:40:51.020249Z","submitted_at":"2025-07-14T06:01:58Z","title":"Radial Neighborhood Smoothing Recommender System","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-06T17:49:10.688339Z"},"links":{"citing_paper":"/paper/2507.09952"},"observation_digest":"sha256:b6633f2185c404b7ff22e41e4221ab01ac7add6a41b614809c3453f7b69524e3","observation_id":"40accda4-3d38-4e5f-882d-f22011ac1c0b","resolution":{"observed_at":"2026-08-06T17:49:12.993676Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T17:49:12.769623Z","title":"Blind regression: Nonparametric regression for latent variable models via collaborative filtering","venue":null,"work_id":"8c578aae-c858-4ad2-9a81-992242af0d2a","year":2016},"citing_paper":{"arxiv_id":"2507.09952","last_updated":"2025-07-14T06:01:58Z","snapshot_observed_at":"2026-08-06T17:40:51.020249Z","submitted_at":"2025-07-14T06:01:58Z","title":"Radial Neighborhood Smoothing Recommender System","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-06T17:49:10.759957Z"},"links":{"citing_paper":"/paper/2507.09952"},"observation_digest":"sha256:c62af29672b11061307caa6150814b3f261cd937438c95322b7b531d9731441c","observation_id":"5b24db38-8e0f-492e-96cf-d8b184c71aa2","resolution":{"observed_at":"2026-08-06T17:49:12.828363Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T17:49:12.633899Z","title":"Unifying user-based and item-based collaborative filtering approaches by similarity fusion","venue":null,"work_id":"9f05fdea-6249-4c80-b009-135089ed01ad","year":2006},"citing_paper":{"arxiv_id":"2507.09952","last_updated":"2025-07-14T06:01:58Z","snapshot_observed_at":"2026-08-06T17:40:51.020249Z","submitted_at":"2025-07-14T06:01:58Z","title":"Radial Neighborhood Smoothing Recommender System","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-06T17:49:10.894963Z"},"links":{"citing_paper":"/paper/2507.09952"},"observation_digest":"sha256:6cc84aeaad9290f5d37f321582423e0ab0bb33208c1670b1cb8bc0235fc205cf","observation_id":"5e43e318-8709-49fa-9df5-89306c7f1ce1","resolution":{"observed_at":"2026-08-06T17:49:12.704383Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2501.10871","last_updated":"2025-01-18T20:35:03Z","snapshot_observed_at":"2026-07-06T20:22:54.817573Z","submitted_at":"2025-01-18T20:35:03Z","title":"Enhancing User Intent for Recommendation Systems via Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.10871","snapshot_observed_at":"2026-08-06T17:49:10.949276Z","title":"Enhancing user intent for recommendation systems via large language models, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.09952","last_updated":"2025-07-14T06:01:58Z","snapshot_observed_at":"2026-08-06T17:40:51.020249Z","submitted_at":"2025-07-14T06:01:58Z","title":"Radial Neighborhood Smoothing Recommender System","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-06T17:49:10.949276Z"},"links":{"cited_paper":"/paper/2501.10871","citing_paper":"/paper/2507.09952"},"observation_digest":"sha256:21754199ce5590c7c1921e6e2120c9d3efcb223392f5aeae9b8ac1c0e1f95d90","observation_id":"cdfa4d69-1afd-4e23-8f84-c8d1a384441e","resolution":{"observed_at":"2026-08-06T17:49:10.949276Z","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":"2024.10238","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:49:11.981115Z","title":"Measuring digitalization capabilities using machine learning","venue":null,"work_id":"58e25ba7-1f50-40cb-98d7-6e2bbc714da9","year":2024},"citing_paper":{"arxiv_id":"2507.09952","last_updated":"2025-07-14T06:01:58Z","snapshot_observed_at":"2026-08-06T17:40:51.020249Z","submitted_at":"2025-07-14T06:01:58Z","title":"Radial Neighborhood Smoothing Recommender System","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-06T17:49:10.994259Z"},"links":{"citing_paper":"/paper/2507.09952"},"observation_digest":"sha256:475de2bccf783d702f19781d2bb6d40936e242f9ebd57cef76de769c5c3a56aa","observation_id":"f1530697-5a96-42e8-aac0-d0be4fe81a06","resolution":{"observed_at":"2026-08-06T17:49:12.041884Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T17:49:12.493811Z","title":"Leveraging missing ratings to improve online recommendation systems","venue":null,"work_id":"31d12f49-3132-4d6f-88c6-4a47555a0f64","year":2006},"citing_paper":{"arxiv_id":"2507.09952","last_updated":"2025-07-14T06:01:58Z","snapshot_observed_at":"2026-08-06T17:40:51.020249Z","submitted_at":"2025-07-14T06:01:58Z","title":"Radial Neighborhood Smoothing Recommender System","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-06T17:49:11.136547Z"},"links":{"citing_paper":"/paper/2507.09952"},"observation_digest":"sha256:3af0bf3c93ab2d702e634fd3397c68f8d0a2d624333301ed3464f9826946615c","observation_id":"142053bd-b45d-429f-902f-44f309fac630","resolution":{"observed_at":"2026-08-06T17:49:12.546013Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T17:49:12.403537Z","title":"Nonparametric matrix estimation with one-sided covariates","venue":null,"work_id":"0af6bd1a-5ccb-40c3-9c52-5c490b769129","year":2022},"citing_paper":{"arxiv_id":"2507.09952","last_updated":"2025-07-14T06:01:58Z","snapshot_observed_at":"2026-08-06T17:40:51.020249Z","submitted_at":"2025-07-14T06:01:58Z","title":"Radial Neighborhood Smoothing Recommender System","version":1},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-06T17:49:11.258464Z"},"links":{"citing_paper":"/paper/2507.09952"},"observation_digest":"sha256:0e55dae22e679755912637ca10bb485d0b253f8664808275dfdbc8299dbeb531","observation_id":"397fb0ee-d944-49e6-b8fb-6932b6f8f5f3","resolution":{"observed_at":"2026-08-06T17:49:12.476822Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.07236","last_updated":"2025-06-28T01:57:26Z","snapshot_observed_at":"2026-07-06T21:38:44.739873Z","submitted_at":"2025-06-08T17:42:24Z","title":"A Narrative Review on Large AI Models in Lung Cancer Screening, Diagnosis, and Treatment Planning","version":2},"cited_work":{"arxiv_id":"2506.07236","doi":null,"metadata_source":"pith","pith_arxiv_id":"2506.07236","snapshot_observed_at":"2026-08-06T17:49:11.635907Z","title":"A Narrative Review on Large AI Models in Lung Cancer Screening, Diagnosis, and Treatment Planning","venue":"eess.IV","work_id":"9fdf718a-2ab7-4b01-8dbb-8743053b63c4","year":2025},"citing_paper":{"arxiv_id":"2507.09952","last_updated":"2025-07-14T06:01:58Z","snapshot_observed_at":"2026-08-06T17:40:51.020249Z","submitted_at":"2025-07-14T06:01:58Z","title":"Radial Neighborhood Smoothing Recommender System","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-06T17:49:11.446253Z"},"links":{"cited_paper":"/paper/2506.07236","citing_paper":"/paper/2507.09952"},"observation_digest":"sha256:40d27018f7c674d675864baa8673251ad1da2fbd5a77baa4b23a62171429ba62","observation_id":"52a82d74-a3ad-4a7d-bbce-92736f248eb1","resolution":{"observed_at":"2026-08-06T17:49:11.751586Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2507.09952","last_updated":"2025-07-14T06:01:58Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-06T17:40:51.020249Z","submitted_at":"2025-07-14T06:01:58Z","title":"Radial Neighborhood Smoothing Recommender System"},"reference_resolution":{"displayed":31,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":8,"verified_exact":2,"verified_fuzzy":20},"total_outbound_references":31},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2507.09952."}