{"as_of":"2026-08-07T13:17:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:54e04931a9afc7b3b50b5e3abacdee9a1516c57312f09a0e77dd857ccb080ebc","coverage":[{"denominator":24,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":24,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-11T02:50:06.746659Z","state":"measured"},{"denominator":24,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":24,"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/2607.05735/citation-record","integrity":"/paper/2607.05735/integrity","json":"/paper/2607.05735/citation-record.json","paper":"/paper/2607.05735"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T02:57:56.771614Z","title":"Edelman, Surbhi Goel, Sham Kakade, Eran Malach, and Cyril Zhang","venue":null,"work_id":"0484c0b9-fb21-4745-989a-141f661d0104","year":2022},"citing_paper":{"arxiv_id":"2607.05735","last_updated":"2026-07-07T01:41:42Z","snapshot_observed_at":"2026-08-07T03:43:40.481601Z","submitted_at":"2026-07-07T01:41:42Z","title":"Width-Robust Learnability in Mean-Field Bayesian Neural Networks","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-07-11T02:50:06.746659Z"},"links":{"citing_paper":"/paper/2607.05735"},"observation_digest":"sha256:c4f63fdfce989836922d7f2c04778cd5e94b563af91ba872c987b953778da901","observation_id":"f441e539-48f4-4105-b77d-c61cb0533f99","resolution":{"observed_at":"2026-07-11T02:57:56.799529Z","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":"2026-07-11T02:57:56.835562Z","title":"Self-consistent dynamical field theory of kernel evo- lution in wide neural networks","venue":null,"work_id":"3db5f882-36dc-4d82-8d63-5678e8e8c9c4","year":2023},"citing_paper":{"arxiv_id":"2607.05735","last_updated":"2026-07-07T01:41:42Z","snapshot_observed_at":"2026-08-07T03:43:40.481601Z","submitted_at":"2026-07-07T01:41:42Z","title":"Width-Robust Learnability in Mean-Field Bayesian Neural Networks","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-07-11T02:50:06.746659Z"},"links":{"citing_paper":"/paper/2607.05735"},"observation_digest":"sha256:3cd76fe61d2369fcb6ec18e0f36a9f5acc68b6b1849278e0a03d870e14f62607","observation_id":"ca1051ac-b4f0-4a95-a2e5-c8519acb4232","resolution":{"observed_at":"2026-07-11T02:57:56.866066Z","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":"2026-07-11T02:57:56.548357Z","title":"How uniform random weights induce non-uniform bias: Typical interpolating neural networks generalize with narrow teachers","venue":null,"work_id":"e9b49450-f322-46f7-9c45-1cb2ee1622d3","year":2024},"citing_paper":{"arxiv_id":"2607.05735","last_updated":"2026-07-07T01:41:42Z","snapshot_observed_at":"2026-08-07T03:43:40.481601Z","submitted_at":"2026-07-07T01:41:42Z","title":"Width-Robust Learnability in Mean-Field Bayesian Neural Networks","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-07-11T02:50:06.746659Z"},"links":{"citing_paper":"/paper/2607.05735"},"observation_digest":"sha256:1353456f0f62a3f2f6e73ff9bab7b16e0bea1d3a8968947e26c1f52bee8660bb","observation_id":"6b153374-63aa-4ea5-9032-63e169a31f8c","resolution":{"observed_at":"2026-07-11T02:57:56.575860Z","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":"2026-07-11T02:57:56.581107Z","title":null,"venue":null,"work_id":"dc7d5aa1-0e5b-478b-b996-10872c700436","year":2018},"citing_paper":{"arxiv_id":"2607.05735","last_updated":"2026-07-07T01:41:42Z","snapshot_observed_at":"2026-08-07T03:43:40.481601Z","submitted_at":"2026-07-07T01:41:42Z","title":"Width-Robust Learnability in Mean-Field Bayesian Neural Networks","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-07-11T02:50:06.746659Z"},"links":{"citing_paper":"/paper/2607.05735"},"observation_digest":"sha256:b349930f8816cae739b478d7b4ccf0af73dda279f6dadd65b2cec8f54feebfba","observation_id":"3b3983f4-9f2d-453c-b0d7-cecf043201ac","resolution":{"observed_at":"2026-07-11T02:57:56.609984Z","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":"2026-07-11T02:57:56.674577Z","title":"Generalization bounds for neural networks via approximate description length","venue":null,"work_id":"0bf00f86-a025-4bb9-a52a-4a8479f3d7fe","year":2019},"citing_paper":{"arxiv_id":"2607.05735","last_updated":"2026-07-07T01:41:42Z","snapshot_observed_at":"2026-08-07T03:43:40.481601Z","submitted_at":"2026-07-07T01:41:42Z","title":"Width-Robust Learnability in Mean-Field Bayesian Neural Networks","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-07-11T02:50:06.746659Z"},"links":{"citing_paper":"/paper/2607.05735"},"observation_digest":"sha256:282c1672becea02ddd33d2135fdda14d904880fa34a25cc0e025beb8568eea0d","observation_id":"f0a04536-1a7d-4ed7-8d32-64e7464c5fbe","resolution":{"observed_at":"2026-07-11T02:57:56.704442Z","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":"2026-07-11T02:57:56.804465Z","title":"On the sample complexity of two-layer networks: Lipschitz vs","venue":null,"work_id":"775fd23f-01ac-4e33-bdd9-5df4c938f19b","year":2024},"citing_paper":{"arxiv_id":"2607.05735","last_updated":"2026-07-07T01:41:42Z","snapshot_observed_at":"2026-08-07T03:43:40.481601Z","submitted_at":"2026-07-07T01:41:42Z","title":"Width-Robust Learnability in Mean-Field Bayesian Neural Networks","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-07-11T02:50:06.746659Z"},"links":{"citing_paper":"/paper/2607.05735"},"observation_digest":"sha256:276fb594141bd8413ca2a2aa0c8944a16918abb13843a006d29123d195b05a39","observation_id":"e24aba7a-6c60-455d-82c0-4fc1a7065c4a","resolution":{"observed_at":"2026-07-11T02:57:56.831828Z","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":"2026-07-11T02:57:56.517992Z","title":"Learning parities with neural networks","venue":null,"work_id":"c5b2417c-7a09-4614-9c70-58af85fa5d9c","year":2020},"citing_paper":{"arxiv_id":"2607.05735","last_updated":"2026-07-07T01:41:42Z","snapshot_observed_at":"2026-08-07T03:43:40.481601Z","submitted_at":"2026-07-07T01:41:42Z","title":"Width-Robust Learnability in Mean-Field Bayesian Neural Networks","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-07-11T02:50:06.746659Z"},"links":{"citing_paper":"/paper/2607.05735"},"observation_digest":"sha256:bbfb9cb302d18be6585bb4441f3c402a5f7d88cc2070a7107b4696eee382b377","observation_id":"1e81abbe-8e26-407c-ac3d-08587aa9a706","resolution":{"observed_at":"2026-07-11T02:57:56.542913Z","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":"2603.11161","last_updated":"2026-05-07T13:22:24Z","snapshot_observed_at":"2026-07-06T22:48:44.253503Z","submitted_at":"2026-03-11T18:00:00Z","title":"Algorithmic Task Capture, Computational Complexity, and Inductive Bias of Infinite Transformers","version":2},"cited_work":{"arxiv_id":"2603.11161","doi":null,"metadata_source":"pith","pith_arxiv_id":"2603.11161","snapshot_observed_at":"2026-07-11T02:57:47.058973Z","title":"Algorithmic Task Capture, Computational Complexity, and Inductive Bias of Infinite Transformers","venue":"cs.LG","work_id":"4736bbb5-f471-4c16-bb75-f78239f2777c","year":2026},"citing_paper":{"arxiv_id":"2607.05735","last_updated":"2026-07-07T01:41:42Z","snapshot_observed_at":"2026-08-07T03:43:40.481601Z","submitted_at":"2026-07-07T01:41:42Z","title":"Width-Robust Learnability in Mean-Field Bayesian Neural Networks","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-07-11T02:50:06.746659Z"},"links":{"cited_paper":"/paper/2603.11161","citing_paper":"/paper/2607.05735"},"observation_digest":"sha256:236e42992b5b114a803589671bfa1c987fefc066c34c66564d1edeca647deb3d","observation_id":"1dda7ac2-3187-48fc-9b6f-e38505af4efd","resolution":{"observed_at":"2026-07-11T02:57:47.089470Z","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":"2602.12855","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T02:57:47.025100Z","title":"Lecture notes: From gaussian processes to feature learning.arXiv preprint arXiv:2602.12855, 2026","venue":null,"work_id":"8631f1c1-7ea1-43ed-ba7f-f021c2dfb340","year":2026},"citing_paper":{"arxiv_id":"2607.05735","last_updated":"2026-07-07T01:41:42Z","snapshot_observed_at":"2026-08-07T03:43:40.481601Z","submitted_at":"2026-07-07T01:41:42Z","title":"Width-Robust Learnability in Mean-Field Bayesian Neural Networks","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-07-11T02:50:06.746659Z"},"links":{"citing_paper":"/paper/2607.05735"},"observation_digest":"sha256:4178a1516c5b9db7f55df62e0212a16e0663b3a6f9533489328adef75b97f55c","observation_id":"fd3f3efd-55df-498b-880b-341a1463cc19","resolution":{"observed_at":"2026-07-11T02:57:47.052198Z","resolver_source":"arxiv_id","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":"2026-07-11T02:57:56.614552Z","title":"Neuraltangentkernel: convergenceand generalization in neural networks","venue":null,"work_id":"b8c21a08-50c9-47e8-aa7d-69972257a628","year":2018},"citing_paper":{"arxiv_id":"2607.05735","last_updated":"2026-07-07T01:41:42Z","snapshot_observed_at":"2026-08-07T03:43:40.481601Z","submitted_at":"2026-07-07T01:41:42Z","title":"Width-Robust Learnability in Mean-Field Bayesian Neural Networks","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-07-11T02:50:06.746659Z"},"links":{"citing_paper":"/paper/2607.05735"},"observation_digest":"sha256:7a8e647f2616d91148ed3508354042bf4442b9a0ddadc7f2a3c74fb01933f2d4","observation_id":"0617aac7-55fe-4d2d-a6bd-204e2959f514","resolution":{"observed_at":"2026-07-11T02:57:56.641731Z","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":"2502.07998","last_updated":"2025-09-10T18:21:17Z","snapshot_observed_at":"2026-07-06T20:35:02.935416Z","submitted_at":"2025-02-11T22:34:49Z","title":"Adaptive kernel predictors from feature-learning infinite limits of neural networks","version":2},"cited_work":{"arxiv_id":"2502.07998","doi":"10.48550/arxiv.2502.07998","metadata_source":"pith","pith_arxiv_id":"2502.07998","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Adaptive kernel predictors from feature-learning infinite limits of neural networks","venue":"cs.LG","work_id":"38e737c0-85b2-438e-bc55-6cbfff28f59a","year":2025},"citing_paper":{"arxiv_id":"2607.05735","last_updated":"2026-07-07T01:41:42Z","snapshot_observed_at":"2026-08-07T03:43:40.481601Z","submitted_at":"2026-07-07T01:41:42Z","title":"Width-Robust Learnability in Mean-Field Bayesian Neural Networks","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-07-11T02:50:06.746659Z"},"links":{"cited_paper":"/paper/2502.07998","citing_paper":"/paper/2607.05735"},"observation_digest":"sha256:06e6f1ce4b51df1aba2c569e48b4485a23e3d7fe8417cc6be9afc8e9ec65c569","observation_id":"5a8e3961-d350-466d-b79a-a55f4d0c37ce","resolution":{"observed_at":"2026-07-11T02:57:47.204069Z","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":"2026-07-11T02:57:56.459063Z","title":"Schoenholz, Jeffrey Pennington, and Jascha Sohl-Dickstein","venue":null,"work_id":"663e8174-7c30-41eb-afdd-7e12ff6d731b","year":2018},"citing_paper":{"arxiv_id":"2607.05735","last_updated":"2026-07-07T01:41:42Z","snapshot_observed_at":"2026-08-07T03:43:40.481601Z","submitted_at":"2026-07-07T01:41:42Z","title":"Width-Robust Learnability in Mean-Field Bayesian Neural Networks","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-07-11T02:50:06.746659Z"},"links":{"citing_paper":"/paper/2607.05735"},"observation_digest":"sha256:f5ea1e47dda7c3fa7dc986a7b71b687e10234d3e4c84291ea940985915bb625f","observation_id":"f1486a1a-10e9-4285-8029-1ab76da74272","resolution":{"observed_at":"2026-07-11T02:57:56.486555Z","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":"2026-07-11T02:57:56.489890Z","title":"Lin, Allan Pinkus, and Shimon Schocken","venue":null,"work_id":"b8bf1615-3dff-4aa9-9650-4163080513b0","year":1993},"citing_paper":{"arxiv_id":"2607.05735","last_updated":"2026-07-07T01:41:42Z","snapshot_observed_at":"2026-08-07T03:43:40.481601Z","submitted_at":"2026-07-07T01:41:42Z","title":"Width-Robust Learnability in Mean-Field Bayesian Neural Networks","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-07-11T02:50:06.746659Z"},"links":{"citing_paper":"/paper/2607.05735"},"observation_digest":"sha256:c1d5026047e8f8926d8549c961127337dccfb8caf7a1fdf56fb7aeb4ae3bbbe5","observation_id":"95f82985-87fb-4d4e-a0c6-eb09d19f4adb","resolution":{"observed_at":"2026-07-11T02:57:56.514285Z","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":"2026-07-11T02:57:56.400884Z","title":"A mean field view of the landscape of two-layer neural networks.Proceedings of the National Academy of Sciences of the United States of America, 115:E7665 – E7671, 2018","venue":null,"work_id":"f20d1745-8569-48f3-8153-953066f49ba4","year":2018},"citing_paper":{"arxiv_id":"2607.05735","last_updated":"2026-07-07T01:41:42Z","snapshot_observed_at":"2026-08-07T03:43:40.481601Z","submitted_at":"2026-07-07T01:41:42Z","title":"Width-Robust Learnability in Mean-Field Bayesian Neural Networks","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-07-11T02:50:06.746659Z"},"links":{"citing_paper":"/paper/2607.05735"},"observation_digest":"sha256:a27e5dfb48c0af91742c4f2c77be3c6f955de0db637bb5daf3760f4b28319083","observation_id":"9ff6274a-921b-446f-95c8-483d2c00bc49","resolution":{"observed_at":"2026-07-11T02:57:56.425089Z","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":"2106.04110","last_updated":"2021-06-08T05:20:00Z","snapshot_observed_at":"2026-07-06T11:16:59.462429Z","submitted_at":"2021-06-08T05:20:00Z","title":"A self consistent theory of Gaussian Processes captures feature learning effects in finite CNNs","version":1},"cited_work":{"arxiv_id":"2106.04110","doi":null,"metadata_source":"pith","pith_arxiv_id":"2106.04110","snapshot_observed_at":"2026-07-11T02:57:47.133708Z","title":"A self consistent theory of Gaussian Processes captures feature learning effects in finite CNNs","venue":"cs.LG","work_id":"1e50dee6-89a4-4954-8c05-eda57453d357","year":2021},"citing_paper":{"arxiv_id":"2607.05735","last_updated":"2026-07-07T01:41:42Z","snapshot_observed_at":"2026-08-07T03:43:40.481601Z","submitted_at":"2026-07-07T01:41:42Z","title":"Width-Robust Learnability in Mean-Field Bayesian Neural Networks","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-07-11T02:50:06.746659Z"},"links":{"cited_paper":"/paper/2106.04110","citing_paper":"/paper/2607.05735"},"observation_digest":"sha256:dd3034aff40746a40dfbb974bd4d25450e2bf4e89bccbd97a065207e45ef1770","observation_id":"ef932345-35cc-4385-8ba5-302153135159","resolution":{"observed_at":"2026-07-11T02:57:47.166961Z","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":"2026-07-11T02:57:56.645711Z","title":"A rigorous framework for the mean field limit of multilayer neural networks.Mathematical Statistics and Learning, 6(3):201–357, 2023","venue":null,"work_id":"5aaa4814-c8c7-4a04-a7cc-e43ac978167d","year":2023},"citing_paper":{"arxiv_id":"2607.05735","last_updated":"2026-07-07T01:41:42Z","snapshot_observed_at":"2026-08-07T03:43:40.481601Z","submitted_at":"2026-07-07T01:41:42Z","title":"Width-Robust Learnability in Mean-Field Bayesian Neural Networks","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-07-11T02:50:06.746659Z"},"links":{"citing_paper":"/paper/2607.05735"},"observation_digest":"sha256:5e0bc577c91150eaa7cb444d57ab6afefe9d560a557081498858ffea3fea58bc","observation_id":"1856196e-329d-4d1b-b1c2-5a414cf705cc","resolution":{"observed_at":"2026-07-11T02:57:56.670256Z","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":"2026-07-11T02:57:56.429564Z","title":"Rotskoff and Eric Vanden-Eijnden","venue":null,"work_id":"374907c3-1434-4c9b-88d1-a6a8b2651e45","year":2018},"citing_paper":{"arxiv_id":"2607.05735","last_updated":"2026-07-07T01:41:42Z","snapshot_observed_at":"2026-08-07T03:43:40.481601Z","submitted_at":"2026-07-07T01:41:42Z","title":"Width-Robust Learnability in Mean-Field Bayesian Neural Networks","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-07-11T02:50:06.746659Z"},"links":{"citing_paper":"/paper/2607.05735"},"observation_digest":"sha256:818067fdf494edab41e178f8c39e0e7f73ceecbdc4e1a0f50f73592f6f62f959","observation_id":"8da0fc37-deab-47fc-8fe3-74611ebe613f","resolution":{"observed_at":"2026-07-11T02:57:56.455604Z","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":"2512.04165","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T02:57:47.095471Z","title":"Mitigating the curse of detail: Scaling arguments for feature learning and sample complexity.arXiv preprint arXiv:2512.04165, 2025","venue":null,"work_id":"5ebed8e3-9714-4f37-b117-05806144d8a9","year":2025},"citing_paper":{"arxiv_id":"2607.05735","last_updated":"2026-07-07T01:41:42Z","snapshot_observed_at":"2026-08-07T03:43:40.481601Z","submitted_at":"2026-07-07T01:41:42Z","title":"Width-Robust Learnability in Mean-Field Bayesian Neural Networks","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-07-11T02:50:06.746659Z"},"links":{"citing_paper":"/paper/2607.05735"},"observation_digest":"sha256:18af0ebaa379393d0a7d584b552676231f22d81e6ff4eb11995c639ad7578a3f","observation_id":"3a6c8c29-14f9-41ec-9f34-7bd223e50be3","resolution":{"observed_at":"2026-07-11T02:57:47.125716Z","resolver_source":"arxiv_id","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":"2026-07-11T02:57:56.335979Z","title":"From kernels to features: A multi-scale adaptive theory of feature learning","venue":null,"work_id":"7cf3d3b3-074e-40dc-869c-435a3f9bfd27","year":2025},"citing_paper":{"arxiv_id":"2607.05735","last_updated":"2026-07-07T01:41:42Z","snapshot_observed_at":"2026-08-07T03:43:40.481601Z","submitted_at":"2026-07-07T01:41:42Z","title":"Width-Robust Learnability in Mean-Field Bayesian Neural Networks","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-07-11T02:50:06.746659Z"},"links":{"citing_paper":"/paper/2607.05735"},"observation_digest":"sha256:626a121ecc2782a8843e21ca4bb8b50a7de6fad428d48afa5072b245ce6e292b","observation_id":"eed3d484-6cde-431a-95ee-da4fb7f9ee03","resolution":{"observed_at":"2026-07-11T02:57:56.366195Z","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":"2026-07-11T02:57:56.735406Z","title":"A unified approach to fea- ture learning in bayesian neural networks","venue":null,"work_id":"ecee03ec-dad2-4af4-8e9b-c4e6b3558f3b","year":2024},"citing_paper":{"arxiv_id":"2607.05735","last_updated":"2026-07-07T01:41:42Z","snapshot_observed_at":"2026-08-07T03:43:40.481601Z","submitted_at":"2026-07-07T01:41:42Z","title":"Width-Robust Learnability in Mean-Field Bayesian Neural Networks","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-07-11T02:50:06.746659Z"},"links":{"citing_paper":"/paper/2607.05735"},"observation_digest":"sha256:179c97cbf286136d613c37f4c707195a10355da4c21279fc39c665a6a4a63f10","observation_id":"8daded67-2b82-4fdf-bece-efa56dcfed85","resolution":{"observed_at":"2026-07-11T02:57:56.766846Z","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":"2026-07-11T02:57:56.299845Z","title":"Separation of scales and a thermodynamic description of feature learning in some cnns.Nature Communications, 14, 2021","venue":null,"work_id":"f6635c91-2c51-4e80-9407-8c0ba338dd94","year":2021},"citing_paper":{"arxiv_id":"2607.05735","last_updated":"2026-07-07T01:41:42Z","snapshot_observed_at":"2026-08-07T03:43:40.481601Z","submitted_at":"2026-07-07T01:41:42Z","title":"Width-Robust Learnability in Mean-Field Bayesian Neural Networks","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-07-11T02:50:06.746659Z"},"links":{"citing_paper":"/paper/2607.05735"},"observation_digest":"sha256:64a914b924435a05e29c490f86e9ca4960f71aa92775bda93743a535c0bc1ccd","observation_id":"d1c6ced4-3de4-4bd0-8c15-6b2318d47611","resolution":{"observed_at":"2026-07-11T02:57:56.330167Z","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":"2026-07-11T02:57:56.708321Z","title":"Sirignano and Konstantinos V","venue":null,"work_id":"c32d40c8-a79a-483a-bad1-894ab0596748","year":2018},"citing_paper":{"arxiv_id":"2607.05735","last_updated":"2026-07-07T01:41:42Z","snapshot_observed_at":"2026-08-07T03:43:40.481601Z","submitted_at":"2026-07-07T01:41:42Z","title":"Width-Robust Learnability in Mean-Field Bayesian Neural Networks","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-07-11T02:50:06.746659Z"},"links":{"citing_paper":"/paper/2607.05735"},"observation_digest":"sha256:1c76d7283a1a826af253c327de5b98f4366b648c2b8eee2ceee686dfd6153f2b","observation_id":"2ec23183-bbd0-45cc-82ea-11d5b1fc38fa","resolution":{"observed_at":"2026-07-11T02:57:56.731102Z","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":"2026-07-11T02:57:56.370121Z","title":"Edward Hu","venue":null,"work_id":"3ef291bd-58d9-409a-8912-59088fb3db64","year":2021},"citing_paper":{"arxiv_id":"2607.05735","last_updated":"2026-07-07T01:41:42Z","snapshot_observed_at":"2026-08-07T03:43:40.481601Z","submitted_at":"2026-07-07T01:41:42Z","title":"Width-Robust Learnability in Mean-Field Bayesian Neural Networks","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-07-11T02:50:06.746659Z"},"links":{"citing_paper":"/paper/2607.05735"},"observation_digest":"sha256:ee32d15d53d8d15d2275ca655f02dbfb31a26d32501285e0ea8b77bdf6823988","observation_id":"e6a115e9-b312-4aa9-9ed5-6d6bf54af367","resolution":{"observed_at":"2026-07-11T02:57:56.396406Z","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":"2504.16920","last_updated":"2025-08-11T13:29:28Z","snapshot_observed_at":"2026-07-06T21:13:45.700548Z","submitted_at":"2025-04-23T17:45:42Z","title":"Summary statistics of learning link changing neural representations to behavior","version":3},"cited_work":{"arxiv_id":"2504.16920","doi":null,"metadata_source":"pith","pith_arxiv_id":"2504.16920","snapshot_observed_at":"2026-07-11T02:57:47.210526Z","title":"Summary statistics of learning link changing neural representations to behavior","venue":"q-bio.NC","work_id":"64426347-17fa-4530-b60c-ad34a0be3809","year":2025},"citing_paper":{"arxiv_id":"2607.05735","last_updated":"2026-07-07T01:41:42Z","snapshot_observed_at":"2026-08-07T03:43:40.481601Z","submitted_at":"2026-07-07T01:41:42Z","title":"Width-Robust Learnability in Mean-Field Bayesian Neural Networks","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-07-11T02:50:06.746659Z"},"links":{"cited_paper":"/paper/2504.16920","citing_paper":"/paper/2607.05735"},"observation_digest":"sha256:4c619a9545fa5814b24e69a433d93579d1932598a1942ab6ce4bc4c2e0b287a4","observation_id":"81dda550-f4a4-431b-9622-6c14dd890e1c","resolution":{"observed_at":"2026-07-11T02:57:47.236988Z","resolver_source":"local_arxiv","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"}}],"paper":{"arxiv_id":"2607.05735","last_updated":"2026-07-07T01:41:42Z","latest_version":1,"primary_category":"stat.ML","snapshot_observed_at":"2026-08-07T03:43:40.481601Z","submitted_at":"2026-07-07T01:41:42Z","title":"Width-Robust Learnability in Mean-Field Bayesian Neural Networks"},"reference_resolution":{"displayed":24,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":1,"verified_exact":5,"verified_fuzzy":17},"total_outbound_references":24},"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 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2607.05735."}