{"as_of":"2026-08-10T07:29:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:ed6851732fea0df9c0be538d3834cfa6a37ab8a1f4adb90257ed24fee4f94f37","coverage":[{"denominator":114,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":100,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-01T20:07:13.478929Z","state":"measured"},{"denominator":100,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":100,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+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/2607.16761/citation-record","integrity":"/paper/2607.16761/integrity","json":"/paper/2607.16761/citation-record.json","paper":"/paper/2607.16761"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"1506.06966","last_updated":"2018-06-22T15:19:48Z","snapshot_observed_at":"2026-08-04T02:14:02.270748Z","submitted_at":"2015-06-23T12:15:03Z","title":"Rates in the Central Limit Theorem and diffusion approximation via Stein's Method","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1506.06966","snapshot_observed_at":"2026-08-01T20:07:00.951280Z","title":"arXiv preprint arXiv:1506.06966 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:00.951280Z"},"links":{"cited_paper":"/paper/1506.06966","citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:97d3875a85b8344cf8983a9a6b04ad84708ae1abe05480768581a885fb5fdecf","observation_id":"e0ce02e6-01ff-410b-86fd-2ea513031e63","resolution":{"observed_at":"2026-08-01T20:07:00.951280Z","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":"2026-08-01T20:07:01.059958Z","title":"Probability theory and related fields , volume=","venue":null,"work_id":null,"year":2001},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:01.059958Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:0822fdc14a454d6e106fd9eaca2a5a6202fb6593a86584565a5d785c231b8a77","observation_id":"94fda2ac-1e85-4682-a16b-696e8e069c5b","resolution":{"observed_at":"2026-08-01T20:07:01.059958Z","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":"2026-08-01T20:07:01.184764Z","title":"arXiv preprint arXiv:2509.10167 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:01.184764Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:632ab43791dac5c5d08341024d484b7299a281d4b246bf6703ac289f65a5725c","observation_id":"6a66125e-95c5-4198-823c-4b84140f38a2","resolution":{"observed_at":"2026-08-01T20:07:01.184764Z","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":"2026-08-01T20:07:01.332858Z","title":"The Annals of Applied Probability , volume=","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:01.332858Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:982d3905bb24d6e5c2dec4945d61aa221b2aaaf543881991b6cdfd4e89e26518","observation_id":"2503512b-dfde-4f40-b721-3eb937c13980","resolution":{"observed_at":"2026-08-01T20:07:01.332858Z","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":"2026-08-01T20:07:01.444548Z","title":"Electronic Journal of Probability , volume=","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:01.444548Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:acef19be70769a56996eef9dbe73b84aa53befa7ea7b94cb1075ae0e9c2d41e3","observation_id":"459b25e7-4ebe-4b2e-afec-cc45c85a5853","resolution":{"observed_at":"2026-08-01T20:07:01.444548Z","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":"2026-08-01T20:07:01.469107Z","title":"1998 , publisher=","venue":null,"work_id":null,"year":1998},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:01.469107Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:612ef4d6c558a2d34d502fd28880932c8d560e76380f15dde926b892b06f8669","observation_id":"ca8c16bd-e7b9-4862-8238-f2558ff690b2","resolution":{"observed_at":"2026-08-01T20:07:01.469107Z","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":"2026-08-01T20:07:01.547086Z","title":"Probability theory and related fields , volume=","venue":null,"work_id":null,"year":1993},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:01.547086Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:5d4642fdd79b47e5a12e740c547c87553d21733b8249e7a238257187867aae52","observation_id":"52456b6d-634d-448a-a23c-34d26dcd080d","resolution":{"observed_at":"2026-08-01T20:07:01.547086Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/bf02214649","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":null,"venue":"Journal of Theoretical Probability","work_id":"4d263e9b-c60a-4f65-93be-74a7df2aafd1","year":1996},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:01.681456Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:a0a11025e6481be852edb15f3fcf6ecef3adf9b0b1105f1af5406bb4a8f8cb0a","observation_id":"650776ac-0ecd-4885-add6-eec27f374199","resolution":{"observed_at":"2026-08-01T20:08:46.533035Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-01T20:07:01.799786Z","title":"Journal of Multivariate Analysis , volume=","venue":null,"work_id":null,"year":1989},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:01.799786Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:d8de99d3fe4090c0bb95b90e272eea560360933e1dd5535d42b9f36242ffc593","observation_id":"82e7bca4-d612-455b-9098-7571a0113c71","resolution":{"observed_at":"2026-08-01T20:07:01.799786Z","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":"2026-08-01T20:07:01.942964Z","title":"2023 , eprint=","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:01.942964Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:b7bf93369c37d3fffc732fd4dbfdc6b2ab6fd726fa33130b297a26404c9c76ef","observation_id":"bb4fe608-d6df-40c5-af87-c082dbc3fd1b","resolution":{"observed_at":"2026-08-01T20:07:01.942964Z","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":"2026-08-01T20:07:02.066218Z","title":"High-dimensional probability","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:02.066218Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:1ea33cf382e3536eeaeceeb4fd32c47f6569f8ee17debf84ab3a797c994f8355","observation_id":"08e35f05-449a-4329-94e5-e1e5f731bf99","resolution":{"observed_at":"2026-08-01T20:07:02.066218Z","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":"2026-08-01T20:07:02.209963Z","title":"Probability Theory and Related Fields , volume=","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:02.209963Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:829874c190230857b3c124ae436b52636c7bc6633f8f10ff41a67e4805884c78","observation_id":"198c985d-9ed9-40ae-a939-4ee92174e073","resolution":{"observed_at":"2026-08-01T20:07:02.209963Z","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":"2026-08-01T20:07:02.366212Z","title":"Moving beyond sub-Gaussianity in high-dimensional statistics: applications in covariance estimation and linear regression , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:02.366212Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:fe21a3f87dd51d00a991cc561ff0d3cc73c0fe01cbcc1a7ad5beab1404734f98","observation_id":"3b4e2a8d-ab06-4732-8604-61f227e8379d","resolution":{"observed_at":"2026-08-01T20:07:02.366212Z","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":"2026-08-01T20:07:02.502317Z","title":"The Annals of Probability , volume =","venue":null,"work_id":null,"year":1994},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:02.502317Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:6ffa883027917caeb62ee0d71d5cba9a2a7f8309a7f9c44e499061a4433a6c74","observation_id":"d23dde5f-12e7-4603-89eb-62cea179478b","resolution":{"observed_at":"2026-08-01T20:07:02.502317Z","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":"2026-08-01T20:07:02.651856Z","title":"International Conference on Learning Representations , year =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:02.651856Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:ea6f9056a6b8651316505f31e344a82170ed57b99b6e45416010006f5ed0a327","observation_id":"25729ca1-9849-43ad-a240-73a5f32080fe","resolution":{"observed_at":"2026-08-01T20:07:02.651856Z","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":"2026-08-01T20:07:02.736321Z","title":"Advances in Neural Information Processing Systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:02.736321Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:bdc26a164da023213540d05cf73637fdcbefd626d03c946c8400f734284b2027","observation_id":"040e8742-6951-419b-9bb9-2afdc342a7e0","resolution":{"observed_at":"2026-08-01T20:07:02.736321Z","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":"2026-08-01T20:07:02.890339Z","title":"2023 , eprint=","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:02.890339Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:57e5d69bcb43b9159b97363c2c52469160469ae1a5a8253b9f54cee61bb92ecc","observation_id":"f707e559-9a7e-41ba-90f4-8670ba71814d","resolution":{"observed_at":"2026-08-01T20:07:02.890339Z","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":"2026-08-01T20:07:03.043802Z","title":"2023 , eprint=","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:03.043802Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:2f1f8b2eb61d61490d9148f0489865ff9f15302bab614df0447f3a51df055e54","observation_id":"e857ffc6-2f8d-4c85-8036-2e37b6630f5f","resolution":{"observed_at":"2026-08-01T20:07:03.043802Z","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":"2026-08-01T20:07:03.151324Z","title":"2022 , eprint=","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:03.151324Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:9a473bb4be5d4cb8c798a30ef25b9dc3f4d4a719074cb9a6e9a3d22b4fdb39db","observation_id":"ff7dd32c-cbcf-41ec-b195-4afacd651a3e","resolution":{"observed_at":"2026-08-01T20:07:03.151324Z","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":"2026-08-01T20:07:03.311425Z","title":"2023 , eprint=","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:03.311425Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:ed009c6219c2731947e7b507e3dcc7ffcddde5f04bb5573642d1ad5a1b0aa4e7","observation_id":"d3b3e5f9-dd0c-48b8-b085-d86f9ea6b84a","resolution":{"observed_at":"2026-08-01T20:07:03.311425Z","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":"2026-08-01T20:07:03.425408Z","title":"2026 , booktitle=","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:03.425408Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:c1ec6d1dfea8e2374f269789aabd5614ac58768a4ae1a75c10fc159f90a4d7dd","observation_id":"48c394c6-22af-4bf8-aed0-b8c1034992ac","resolution":{"observed_at":"2026-08-01T20:07:03.425408Z","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":"2026-08-01T20:07:03.534941Z","title":"Non-Gaussian Tensor Programs , url =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:03.534941Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:069cb4e2cebab425d5a659f5d3e1e8aa1f29f62d9899fa0f75fba79c63c6dbb8","observation_id":"0327607d-329c-4331-9c39-3d28e1b3d13d","resolution":{"observed_at":"2026-08-01T20:07:03.534941Z","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":"2026-08-01T20:07:03.634425Z","title":"Proceedings of the 38th International Conference on Machine Learning , pages =","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:03.634425Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:2f70c5d72bc24868fcdde96d58aa58324815b211b7bd8e9d74e606866c39b752","observation_id":"5dbeb5a4-0fa6-4cdf-801b-ecca87686330","resolution":{"observed_at":"2026-08-01T20:07:03.634425Z","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":"2026-08-01T20:07:03.796661Z","title":"2023 , eprint=","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:03.796661Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:08e3c4c061f66db3f97c9767c0ecd6dc1f7b997841bcca0f83ed7dc32984efe6","observation_id":"e7a1b864-a027-4ccd-ac8b-482d7f7ffb84","resolution":{"observed_at":"2026-08-01T20:07:03.796661Z","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":"2026-08-01T20:07:03.972772Z","title":"2023 , eprint=","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:03.972772Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:96f58bcf8a4983b62935905785676b59b375d17d72d6c905892c2b6b0ff14297","observation_id":"a5278cfe-5186-458c-8eb3-7cf59244c9f7","resolution":{"observed_at":"2026-08-01T20:07:03.972772Z","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":"2026-08-01T20:07:04.055483Z","title":"2020 , eprint=","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:04.055483Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:6d7e7981732a960c8f5fe07868fa8da3414bc60bde0fedfd3ab1b79b6c7a8a57","observation_id":"ccfd3c27-d11c-466d-9704-d534ffe07c32","resolution":{"observed_at":"2026-08-01T20:07:04.055483Z","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":"2026-08-01T20:07:04.155662Z","title":"2025 , eprint=","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:04.155662Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:b07d076f07ea375f8413ad26f76c4ac14a16c627bccac233292f33c59a6246ac","observation_id":"9ec8b363-a5f3-4fb0-be7b-8ba21169499b","resolution":{"observed_at":"2026-08-01T20:07:04.155662Z","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":"2026-08-01T20:07:04.242502Z","title":"Preprint , year =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:04.242502Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:d1170fd05cb5449936f784c30f9962c5a1d2122ebb4cc94bf22b75d42bfc38b8","observation_id":"8517833e-2270-4c6d-af6d-9c86ccab564d","resolution":{"observed_at":"2026-08-01T20:07:04.242502Z","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":"2026-08-01T20:07:04.307570Z","title":"Spin glass theory and beyond: An introduction to the replica method and its applications","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:04.307570Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:fdb4d4c54169226a64ffd3a98af1817335b241443dfb29dd7c1e1a37126c46d3","observation_id":"2128831f-df74-461a-98af-2ecb55bc4391","resolution":{"observed_at":"2026-08-01T20:07:04.307570Z","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":"2026-08-01T20:07:04.458679Z","title":"Cavity method: message-passing from a physics perspective , ISBN =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:04.458679Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:a51f4a72062ef5a1a389e2c621d57a2932c9893c45147ba98b1e2ef3227a7a7c","observation_id":"d0518168-b293-481a-bee9-63513cd78c6d","resolution":{"observed_at":"2026-08-01T20:07:04.458679Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1142/9789811273926_0019","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"The Cavity Method: From Exact Solutions to Algorithms , ISBN =","venue":"WORLD SCIENTIFIC eBooks","work_id":"6c2a14ee-3081-4bcb-b6ac-b34b0aab0149","year":null},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:04.613506Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:a8b051f47619b5ffddc71289cdca7b1e2e2d168d0a56471f40ce6330bdbc7838","observation_id":"eac3eca8-027f-405c-897e-2ce674804b5d","resolution":{"observed_at":"2026-08-01T20:08:46.227949Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1103/physrevb.25.6860","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"and Zippelius, Annette , year =","venue":"Physical review. B, Condensed matter","work_id":"f594d62f-9220-4890-bf08-44d9946e334a","year":null},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:04.732897Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:5afb2fdc2fb4d5bf2eace8198efa025f6ef1bef77d10390702db88a135e7e0d5","observation_id":"26839983-6792-45a0-8fd5-6ee1d6571151","resolution":{"observed_at":"2026-08-01T20:08:46.006609Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-01T20:07:04.894646Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:04.894646Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:f5c0fe6fd10fb1a67ede7c0bd1250f76d7718675186ec8b05001d6508b9372ae","observation_id":"50b59b8f-cc5a-4288-bf57-0ba3ded7276e","resolution":{"observed_at":"2026-08-01T20:07:04.894646Z","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":"2026-08-01T20:07:05.036177Z","title":"Advances in neural information processing systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:05.036177Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:55d702d9452f0060c0c37a5ba39b3be2e82cfa930156a530707f4b17fd0f9924","observation_id":"c482e43a-3a5f-416b-847c-f6e0427be449","resolution":{"observed_at":"2026-08-01T20:07:05.036177Z","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":"2026-08-01T20:07:05.142722Z","title":"Advances in neural information processing systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:05.142722Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:4e211ec652c5c9f22cd574140421ef6420792531ba971454a4d6ea2f32f92f66","observation_id":"70d8237c-d7c6-4bc9-918d-b2bf56470f28","resolution":{"observed_at":"2026-08-01T20:07:05.142722Z","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":"2026-08-01T20:07:05.279685Z","title":"A mean field view of the landscape of two-layer neural networks , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:05.279685Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:5a8082a14215b1c51723853102d57a1ed59e91d0451d8edbd16b91a9965a9af4","observation_id":"f90fc5a3-ff30-44eb-8f97-9fc2462c947c","resolution":{"observed_at":"2026-08-01T20:07:05.279685Z","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":"2026-08-01T20:07:05.423124Z","title":"SIAM Journal on Applied Mathematics , volume=","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:05.423124Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:c6c723c25e470ef6d64e3bbdb071cd1a261eb759f787206262716f1579f1bd75","observation_id":"f2926191-409b-421b-87ec-c667ccd09e35","resolution":{"observed_at":"2026-08-01T20:07:05.423124Z","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":"2026-08-01T20:07:05.501679Z","title":"Trainability and Accuracy of Artificial Neural Networks: An Interacting Particle System Approach , volume =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:05.501679Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:0dd7855f584ca81a1c5c284aae3a4288e97ea3015a6483cd9b12e8150a5847e1","observation_id":"cb17c48c-6d9a-4418-811a-f85481da37a0","resolution":{"observed_at":"2026-08-01T20:07:05.501679Z","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":"2026-08-01T20:07:05.582078Z","title":"Advances in Neural Information Processing Systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:05.582078Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:0e779f541976cee6bda3eab147878dd9f315671864c8f57ae633c723d16c9b27","observation_id":"8fb547d7-11c6-4957-9116-541c1226db0b","resolution":{"observed_at":"2026-08-01T20:07:05.582078Z","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":"2026-08-01T20:07:05.684416Z","title":"Communications on Pure and Applied Mathematics , volume=","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:05.684416Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:be2ab45245921f5c8a44ee27cc0ae29d943da963bf8261880e3cffcccc2154d2","observation_id":"0d9ee35c-033d-45f8-b915-5fccb6127731","resolution":{"observed_at":"2026-08-01T20:07:05.684416Z","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":"2026-08-01T20:07:05.740049Z","title":"Proceedings of the IEEE conference on computer vision and pattern recognition , pages=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:05.740049Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:2cc9505a71eb8cddafb6e8c206ba58dfae401deb33648b8a939eb411da61ad8d","observation_id":"e97b3619-1a8b-42cb-bd0d-a4d5cfa7865b","resolution":{"observed_at":"2026-08-01T20:07:05.740049Z","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":"2026-08-01T20:07:05.819620Z","title":"Advances in neural information processing systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:05.819620Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:2f69468e1d6a28cbbff177318744845a6ff7c7bb18ad666ab9cf15c0f580480a","observation_id":"cf44715f-576d-4e08-aaf9-bf1c3f892615","resolution":{"observed_at":"2026-08-01T20:07:05.819620Z","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":"2026-08-01T20:07:05.972046Z","title":"International Conference on Machine Learning , pages=","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:05.972046Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:1f948f13602b9c4ad42dd98d781178627b8f363d22451f792b2554e4c38dbb4d","observation_id":"b9d2fa39-aa54-48b2-9455-c610f322e118","resolution":{"observed_at":"2026-08-01T20:07:05.972046Z","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":"2026-08-01T20:07:06.083417Z","title":"2024 , eprint=","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:06.083417Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:b0c13c3e2499cba2b738c1da7ea2de4d0721e0b4ca0f83959b96eea90d6a262f","observation_id":"ea3287dc-68ca-4a68-b9c8-00211e3d76a4","resolution":{"observed_at":"2026-08-01T20:07:06.083417Z","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":"2026-08-01T20:07:06.231058Z","title":"Journal of machine learning research , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:06.231058Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:c75ceb2f74d06f9d0082b5c8bb152005e9304ba485e5c42173f685032f27db27","observation_id":"66302ecb-abef-499e-a079-3bf4ab564b4a","resolution":{"observed_at":"2026-08-01T20:07:06.231058Z","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":"2026-08-01T20:07:06.394414Z","title":"2021 , eprint=","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:06.394414Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:fb3f4bd4e2156a5297a21683c0f1f48096196f6ec0e6edc21d9989716d885ec6","observation_id":"84ffdeb3-da2a-45c6-ae8a-15e54c090d9d","resolution":{"observed_at":"2026-08-01T20:07:06.394414Z","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":"2026-08-01T20:07:06.525681Z","title":"Advances in Neural Information Processing Systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:06.525681Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:8f814677ccd52a8f6eba374161ff2c2599fe85c73d5ee8cf6b8a225ea1f294f3","observation_id":"a2f48920-dda4-457c-b7c1-6ecb16a686e7","resolution":{"observed_at":"2026-08-01T20:07:06.525681Z","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":"2026-08-01T20:07:06.664241Z","title":"Neural Information Processing Systems , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:06.664241Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:cea6afc23d45511ab8c1c6aa38598df4aec02aec8228b03e388254448c746e4c","observation_id":"5d325dee-0d95-482d-9323-246096de5100","resolution":{"observed_at":"2026-08-01T20:07:06.664241Z","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":"2026-08-01T20:07:06.830668Z","title":"Communications in Mathematics and Statistics , volume=","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":49,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:06.830668Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:535d847d24e5ba8278e980e5b123be302853a83ff7a35c5c8d474fdc35b2fc4b","observation_id":"91618507-5d9c-42f7-afca-078baf5bca41","resolution":{"observed_at":"2026-08-01T20:07:06.830668Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1712.05438","last_updated":"2017-12-14T20:12:02Z","snapshot_observed_at":"2026-08-07T19:17:14.888226Z","submitted_at":"2017-12-14T20:12:02Z","title":"Stochastic Particle Gradient Descent for Infinite Ensembles","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1712.05438","snapshot_observed_at":"2026-08-01T20:07:06.986199Z","title":"arXiv preprint arXiv:1712.05438 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":50,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:06.986199Z"},"links":{"cited_paper":"/paper/1712.05438","citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:0b2b061d7c0c8207aa06865453756fd99fc554e7d5ac67a5618a86a5cc6bc372","observation_id":"1f75074b-0b28-4c94-b585-1a2ef492fc2c","resolution":{"observed_at":"2026-08-01T20:07:06.986199Z","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":"2026-08-01T20:07:07.128394Z","title":"International conference on machine learning , pages=","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":51,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:07.128394Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:d6e5452622dc02d15f0667154c0d3c0624db6d24e6b2cd56822b31afb3123fc3","observation_id":"a41c21fb-270c-43c0-8dcd-d37104f667d2","resolution":{"observed_at":"2026-08-01T20:07:07.128394Z","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":"2026-08-01T20:07:07.306320Z","title":"Advances in Neural Information Processing Systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":52,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:07.306320Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:41f2fc65a323e1e44714fcf561ca310ca5a67451a20887002ff778f918a2a194","observation_id":"c992c729-f6c9-4e1e-a3aa-786735e167bb","resolution":{"observed_at":"2026-08-01T20:07:07.306320Z","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":"2026-08-01T20:07:07.428776Z","title":"Journal of Statistical Mechanics: Theory and Experiment , volume=","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":53,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:07.428776Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:19eb1b8990f3a2da48d4ca8a342cae155db7d09cdd4564ac27d61e8711576467","observation_id":"dd8f12e7-71a6-44b0-b51b-669fe26f84f9","resolution":{"observed_at":"2026-08-01T20:07:07.428776Z","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":"2026-08-01T20:07:07.590247Z","title":"Advances in Neural Information Processing Systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":54,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:07.590247Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:6c360ba71d5c0be18ad06dc817ac05b115aec50780f3286e4e7e480f333342e8","observation_id":"2bded603-4ea2-4119-b11b-d1c06c832e91","resolution":{"observed_at":"2026-08-01T20:07:07.590247Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2507.08486","last_updated":"2025-07-11T11:04:46Z","snapshot_observed_at":"2026-08-08T12:46:52.942418Z","submitted_at":"2025-07-11T11:04:46Z","title":"Genericity of Polyak-Lojasiewicz Inequalities for Entropic Mean-Field Neural ODEs","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2507.08486","snapshot_observed_at":"2026-08-01T20:07:07.749632Z","title":"Genericity of","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":55,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:07.749632Z"},"links":{"cited_paper":"/paper/2507.08486","citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:7ea731f8e564283f2e59439d0e195d73cc752d62852904023f6856ed11e74474","observation_id":"0590d328-7ed2-4ce2-a7b9-911e30ff9245","resolution":{"observed_at":"2026-08-01T20:07:07.749632Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.15365","last_updated":"2026-07-22T02:39:17Z","snapshot_observed_at":"2026-08-08T09:01:29.542415Z","submitted_at":"2023-11-26T17:44:29Z","title":"A convergence result of a continuous model of deep learning via a \\L{}ojasiewicz--Simon inequality","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.15365","snapshot_observed_at":"2026-08-01T20:07:07.891741Z","title":"arXiv preprint arXiv:2311.15365 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":56,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:07.891741Z"},"links":{"cited_paper":"/paper/2311.15365","citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:86dea46813a43e350fddb4ed2cc2d04de38ee0b4951adf6d9fe521d6f25868e7","observation_id":"314b522b-1abf-42c4-b374-702bc8488dbd","resolution":{"observed_at":"2026-08-01T20:07:07.891741Z","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":"2026-08-01T20:07:08.058135Z","title":"Nonlinear Analysis , volume=","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":57,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:08.058135Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:23db1a8f37d8034f6fef2efb881a6a64bdf5e65c9723b466ae5e7bd8e6a4c0bd","observation_id":"58b8b223-0c0e-4bd9-8096-dcc4ece076eb","resolution":{"observed_at":"2026-08-01T20:07:08.058135Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1912.05475","last_updated":"2021-03-16T20:11:15Z","snapshot_observed_at":"2026-07-30T19:56:53.814842Z","submitted_at":"2019-12-11T17:13:06Z","title":"Mean-Field Neural ODEs via Relaxed Optimal Control","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.05475","snapshot_observed_at":"2026-08-01T20:07:08.237329Z","title":"Mean-field neural","venue":null,"work_id":null,"year":1912},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":58,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:08.237329Z"},"links":{"cited_paper":"/paper/1912.05475","citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:198559c08d3c2f9271eced86f7cdce2a17a77e6d8f781c4da5f10b2814033bc8","observation_id":"dca11aca-9676-41eb-86ba-fba486ddf377","resolution":{"observed_at":"2026-08-01T20:07:08.237329Z","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":"2026-08-01T20:07:08.353216Z","title":"Journal de Math","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":59,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:08.353216Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:ec33fb59e84aaacfe442079a3f9b2436dbaa9eac1a6952a2b45de7377af5088f","observation_id":"35d70ee9-ee28-43fc-9e76-3bd002525f98","resolution":{"observed_at":"2026-08-01T20:07:08.353216Z","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":"2026-08-01T20:07:08.510257Z","title":"Advances in Neural Information Processing Systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":60,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:08.510257Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:c415e9c95a1dba9b35a0380befaac708d77241a3be95d65de1a30888f7b8d315","observation_id":"952cfb68-6949-4cee-b210-b74adfad900d","resolution":{"observed_at":"2026-08-01T20:07:08.510257Z","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":"2026-08-01T20:07:08.648384Z","title":"Advances in Neural Information Processing Systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":61,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:08.648384Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:c667cf52f5e9fb36d116927681794b5a8ac62af8c0c062b371335b95670c1db4","observation_id":"0260758e-83a7-462a-a0e2-4e5bca7adc09","resolution":{"observed_at":"2026-08-01T20:07:08.648384Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2006.14548","last_updated":"2020-11-30T03:30:09Z","snapshot_observed_at":"2026-08-09T14:14:48.992996Z","submitted_at":"2020-06-25T16:45:23Z","title":"Tensor Programs II: Neural Tangent Kernel for Any Architecture","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2006.14548","snapshot_observed_at":"2026-08-01T20:07:08.799888Z","title":"arXiv preprint arXiv:2006.14548 , year=","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":62,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:08.799888Z"},"links":{"cited_paper":"/paper/2006.14548","citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:7e046b09f6cc7cc84ff0cb99ae83b6cbd7fa0446e90fc51aa0bf7472e2451e0a","observation_id":"8a1e2870-13a6-4667-993d-3ce10fe622f8","resolution":{"observed_at":"2026-08-01T20:07:08.799888Z","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":"2026-08-01T20:07:08.921667Z","title":"Communications on Pure and Applied Mathematics , volume=","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":63,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:08.921667Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:b6a8fc8552eb58e04ceaad364f4ec03a88db3a966d5e0fb4314a63f9b1743282","observation_id":"e5617dec-2011-4f7c-b0b5-72fc32eb98e3","resolution":{"observed_at":"2026-08-01T20:07:08.921667Z","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":"2026-08-01T20:07:09.087489Z","title":"IEEE Transactions on Information Theory , volume=","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":64,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:09.087489Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:05f30cbeb588a7c0b1f6c4cda9cedae6c805fb33c97313a1d40a73d03f744aeb","observation_id":"67de3448-295e-45ca-8e1f-d22460e259f9","resolution":{"observed_at":"2026-08-01T20:07:09.087489Z","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":"2026-08-01T20:07:09.174162Z","title":"2025 , school=","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":65,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:09.174162Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:0ed923da9052560adb281f42245d9dcedeef4bc479d64e52252968eeb63ea9f1","observation_id":"941e8c50-9428-4773-8d00-69951cf80bef","resolution":{"observed_at":"2026-08-01T20:07:09.174162Z","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":"2026-08-01T20:07:09.292699Z","title":"arXiv preprint arXiv:2504.15556 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":66,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:09.292699Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:368e3441623a53f31a1cb36488227a9b6b74bb948a09418990f6ad8ad31c882b","observation_id":"26401217-6209-4d4d-abd9-3079342bed0f","resolution":{"observed_at":"2026-08-01T20:07:09.292699Z","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":"2026-08-01T20:07:09.419988Z","title":"SIAM Journal on Mathematics of Data Science , volume=","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":67,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:09.419988Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:ec8fc97a92271f6d6b78ab92c9765b42a3dbc20f9b940653bbacb1c34279e1a6","observation_id":"4049ea24-1699-4abc-aa12-7709c707742b","resolution":{"observed_at":"2026-08-01T20:07:09.419988Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.03220","last_updated":"2024-06-30T17:01:45Z","snapshot_observed_at":"2026-08-08T07:14:14.108661Z","submitted_at":"2024-02-05T17:30:42Z","title":"The Benefits of Reusing Batches for Gradient Descent in Two-Layer Networks: Breaking the Curse of Information and Leap Exponents","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.03220","snapshot_observed_at":"2026-08-01T20:07:09.528204Z","title":"arXiv preprint arXiv:2402.03220 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":68,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:09.528204Z"},"links":{"cited_paper":"/paper/2402.03220","citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:da85de7673331cac94c3fd6a26383f8a75a2f3025467f2930a4b9026eaeaea5e","observation_id":"6e911876-1422-407c-9f65-5361d10257ef","resolution":{"observed_at":"2026-08-01T20:07:09.528204Z","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":"2026-08-01T20:07:09.631264Z","title":"Advances in Neural Information Processing Systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":69,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:09.631264Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:b89760595622920c0f70c6d54aaf202d09c9b4876f54e6e90b88e55a4ff4611b","observation_id":"e074334b-bb0e-4aa6-ba56-efb859dd031e","resolution":{"observed_at":"2026-08-01T20:07:09.631264Z","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":"2026-08-01T20:07:09.708303Z","title":"International Conference on Machine Learning , pages=","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":70,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:09.708303Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:ede29985dd0de69b74746b0885aab57f9a1f1e954f5390c22377ca610d800019","observation_id":"c0b478d3-9537-43b6-9b7b-d570ce3007f6","resolution":{"observed_at":"2026-08-01T20:07:09.708303Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.07810","last_updated":"2023-05-13T01:10:49Z","snapshot_observed_at":"2026-08-07T18:53:50.315363Z","submitted_at":"2023-05-13T01:10:49Z","title":"Depth Dependence of $\\mu$P Learning Rates in ReLU MLPs","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.07810","snapshot_observed_at":"2026-08-01T20:07:09.748386Z","title":"arXiv preprint arXiv:2305.07810 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":71,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:09.748386Z"},"links":{"cited_paper":"/paper/2305.07810","citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:8220ce407c4006b9668a3023ce8fab910f4e1afec5b4d0dc0c65321af50f13ec","observation_id":"f036c8a2-8a48-49b3-8025-7f011af87534","resolution":{"observed_at":"2026-08-01T20:07:09.748386Z","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":"2026-08-01T20:07:09.862061Z","title":"Advances in Neural Information Processing Systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":72,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:09.862061Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:b6c67c481dcc11f2c42422732cee4c930268fd26ea3f4dab89f960d59b909a00","observation_id":"df3f8099-6ee1-4d36-94b9-798bccc886aa","resolution":{"observed_at":"2026-08-01T20:07:09.862061Z","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":"2026-08-01T20:07:10.002276Z","title":"Advances in Neural Information Processing Systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":73,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:10.002276Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:b6066c4e24287d95906666c6d82924995954cb52f10e35710f4b27e55860015d","observation_id":"9328213c-6f17-4bec-928d-d7489f97e4f6","resolution":{"observed_at":"2026-08-01T20:07:10.002276Z","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":"2026-08-01T20:07:10.160121Z","title":"arXiv preprint arXiv:2603.18168 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":74,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:10.160121Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:ef0c349431f3e16bde8dfbd1c25af0135655e8fbfe026b1bff1edd674845e7d2","observation_id":"02c69d1a-d9c6-417e-ac76-6d9cf11c45b6","resolution":{"observed_at":"2026-08-01T20:07:10.160121Z","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":"2026-08-01T20:07:10.291909Z","title":"arXiv preprint arXiv:2510.07554 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":75,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:10.291909Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:e20af54745b4096c50a4d1053e59a91e8ef383978f6dd04235ae410fc3bc7618","observation_id":"96b638c7-9427-4a62-a4a3-db2563bd0262","resolution":{"observed_at":"2026-08-01T20:07:10.291909Z","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":"2026-08-01T20:07:10.410257Z","title":"2026 , eprint=","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":76,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:10.410257Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:3051d94d6b4863f1637cd7a4df80299b7e423d08e2c73ff6cd986acae5a515f6","observation_id":"db119149-3e7c-4212-88bf-8f65af68f155","resolution":{"observed_at":"2026-08-01T20:07:10.410257Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1207.0580","last_updated":"2012-07-03T06:35:15Z","snapshot_observed_at":"2026-07-06T02:51:07.275676Z","submitted_at":"2012-07-03T06:35:15Z","title":"Improving neural networks by preventing co-adaptation of feature detectors","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1207.0580","snapshot_observed_at":"2026-08-01T20:07:10.526406Z","title":"arXiv preprint arXiv:1207.0580 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":77,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:10.526406Z"},"links":{"cited_paper":"/paper/1207.0580","citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:62704aa7764fdb5a71f2e13df2a0459de92541ea69b3786be00230a0b7f269f0","observation_id":"a085e19f-0cd7-4762-b796-b913ca8f3efd","resolution":{"observed_at":"2026-08-01T20:07:10.526406Z","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":"2026-08-01T20:07:10.608872Z","title":"Journal of Machine Learning Research , year =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":78,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:10.608872Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:6e010fc185a96843c41a677591b4ebf9e4ef521f80acb5c1aeff1dc2596a550f","observation_id":"ba746f04-3429-4e2f-be3b-8d88da29c573","resolution":{"observed_at":"2026-08-01T20:07:10.608872Z","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":"2026-08-01T20:07:10.696205Z","title":"Advances in neural information processing systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":79,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:10.696205Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:9c553f6b477fc29cfd5859a6d0ed79181433f0c83b369819a823f870d5358288","observation_id":"253bdc10-3dd5-4489-8175-b64925869418","resolution":{"observed_at":"2026-08-01T20:07:10.696205Z","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":"2026-08-01T20:07:10.782951Z","title":"International conference on machine learning , pages=","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":80,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:10.782951Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:9497c73a3d7601776eaaed6ed25e20d29acfb5567fecdce19053747a5f07c294","observation_id":"b7b25f33-06a2-4e98-9928-66a2d9e7dcb7","resolution":{"observed_at":"2026-08-01T20:07:10.782951Z","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":"2026-08-01T20:07:10.861033Z","title":"Proceedings of the 38th International Conference on Machine Learning , pages =","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":81,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:10.861033Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:19d28cb2d100ea42f7d338e422c4d5655503b2280bf10d134da245c21ab43c32","observation_id":"09b266a2-4e2a-45ea-afa4-9f49b7b6b1d5","resolution":{"observed_at":"2026-08-01T20:07:10.861033Z","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":"2026-08-01T20:07:11.011454Z","title":"2023 , booktitle=","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":82,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:11.011454Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:b3f8d997dc133c9c75bb06e68fc9af2715902a14dd9eb1c215a94705237e84f5","observation_id":"d605d45d-7f7a-4891-9f6f-f339084b5c36","resolution":{"observed_at":"2026-08-01T20:07:11.011454Z","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":"2026-08-01T20:07:11.098692Z","title":"Advances in Neural Information Processing Systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":83,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:11.098692Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:ec90ad4e33139c9c09660d57d9ab2a5c7991e7f583a3a5492282592ac77b75d2","observation_id":"7c96e258-b886-41ca-bd14-f2a913986a4c","resolution":{"observed_at":"2026-08-01T20:07:11.098692Z","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":"2026-08-01T20:07:11.192275Z","title":"International Conference on Machine Learning , pages=","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":84,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:11.192275Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:3ea34e31b9beb8e07c6b2fdda460550939e4d01254d8737828cfef40e5fd072e","observation_id":"9e10199d-bb12-42ba-ae16-d59808ce97d9","resolution":{"observed_at":"2026-08-01T20:07:11.192275Z","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":"2026-08-01T20:07:11.251040Z","title":"Advances in Neural Information Processing Systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":85,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:11.251040Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:f143ac30e558e0e489c0f9e7bcd57ec3e5e9026cf986ac1a8f51c2576a91967a","observation_id":"6a9fe0af-7e0a-4ab4-bd23-717856bce68c","resolution":{"observed_at":"2026-08-01T20:07:11.251040Z","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":"2026-08-01T20:07:11.389060Z","title":"arXiv preprint arXiv:2602.15322 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":86,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:11.389060Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:e14ccc276501c6728e97bb2d4c51e4ca802f1bcacfb2053c6bd910baa6ed6a6a","observation_id":"64d8220f-ade4-45c3-b2da-d4ca633d58cb","resolution":{"observed_at":"2026-08-01T20:07:11.389060Z","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":"2026-08-01T20:07:11.556672Z","title":"The Journal of Machine Learning Research , volume=","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":87,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:11.556672Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:31e6c6ef1f992491899d60d7ca91f731041bc0b236f313723f490e1cac624669","observation_id":"2312279d-bf8b-4e58-9f94-8b23c166036b","resolution":{"observed_at":"2026-08-01T20:07:11.556672Z","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":"2026-08-01T20:07:11.658450Z","title":"Proceedings of the 35th International Conference on Machine Learning , pages =","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":88,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:11.658450Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:9c80ed10f48c3a576712acab2ac52293d8805e579802bba70728ce64c786ac67","observation_id":"6c477483-0624-4f08-8d96-07d72847f1dc","resolution":{"observed_at":"2026-08-01T20:07:11.658450Z","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":"2026-08-01T20:07:11.835632Z","title":"European conference on computer vision , pages=","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":89,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:11.835632Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:cf635e2bd150898edd25044a30262037e9d87f3173c25861a46fd81b6d8e4e9d","observation_id":"1e45d8f3-3891-45a3-a01f-f53a8e2bd0c0","resolution":{"observed_at":"2026-08-01T20:07:11.835632Z","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":"2026-08-01T20:07:11.998493Z","title":"International conference on machine learning , pages=","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":90,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:11.998493Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:64836cb26dca4dd379c3b79d52f3512e5c2187eb30f49c1436cee1ef2ce8d91c","observation_id":"156a4a2d-5a0f-40ce-9dcb-3f14f0fe97b4","resolution":{"observed_at":"2026-08-01T20:07:11.998493Z","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":"2026-08-01T20:07:12.186048Z","title":"2018 , eprint=","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":91,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:12.186048Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:5ce90f51b5cafc182f2e7b591134c81ae0784ecf639b31f8122f5349384f8c40","observation_id":"4b928e33-eddd-46e8-ab21-71524458b6ad","resolution":{"observed_at":"2026-08-01T20:07:12.186048Z","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":"2026-08-01T20:07:12.315319Z","title":"2024 , eprint=","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":92,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:12.315319Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:970d9229311a07268562a2e8e67065fd4a033dba3207af81dd716cbc339c08af","observation_id":"a6fce390-5ca8-4906-9264-5560925625f0","resolution":{"observed_at":"2026-08-01T20:07:12.315319Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1705.07485","last_updated":"2017-05-23T13:36:46Z","snapshot_observed_at":"2026-08-06T23:32:24.977250Z","submitted_at":"2017-05-21T18:51:27Z","title":"Shake-Shake regularization","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1705.07485","snapshot_observed_at":"2026-08-01T20:07:12.472967Z","title":"arXiv preprint arXiv:1705.07485 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":93,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:12.472967Z"},"links":{"cited_paper":"/paper/1705.07485","citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:5c44bbe3b007964249b58fc4d74c9df456b221d77c4b561b465b44bf52ed81a6","observation_id":"8631a397-a0bd-48a5-b88c-fcea9e03612c","resolution":{"observed_at":"2026-08-01T20:07:12.472967Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1301.3557","last_updated":"2013-01-16T02:12:07Z","snapshot_observed_at":"2026-08-03T12:35:12.187137Z","submitted_at":"2013-01-16T02:12:07Z","title":"Stochastic Pooling for Regularization of Deep Convolutional Neural Networks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1301.3557","snapshot_observed_at":"2026-08-01T20:07:12.594333Z","title":"arXiv preprint arXiv:1301.3557 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":94,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:12.594333Z"},"links":{"cited_paper":"/paper/1301.3557","citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:bd17b6088a66602150586a5fa114fc452c9f308c8b92547c52dc4e508d5dfea2","observation_id":"db89b709-b601-4c91-8628-c55b551c1861","resolution":{"observed_at":"2026-08-01T20:07:12.594333Z","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":"2026-08-01T20:07:12.776049Z","title":"International Conference on Learning Representations , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":95,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:12.776049Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:ea5af3094cd701a227390d89ec9523ca91544a3cdd5047619ba04a3d2ce5f8fe","observation_id":"5b53dcb2-3424-4609-a743-8f4974827b15","resolution":{"observed_at":"2026-08-01T20:07:12.776049Z","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":"2026-08-01T20:07:12.893913Z","title":"Advances in neural information processing systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":96,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:12.893913Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:32f86e8fcc1fe7875fe9828b368251a302af3c91b75b67f1edef50b0953291d2","observation_id":"72ccf012-6c22-4106-ad44-650470540376","resolution":{"observed_at":"2026-08-01T20:07:12.893913Z","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":"2026-08-01T20:07:13.035768Z","title":"2016 , eprint=","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":97,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:13.035768Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:32ff793b4b5d0464d6b4ef44f89146b30fc74c5b064ecc264c9bcc41ad5fc1f8","observation_id":"76519bc1-0773-4e6f-9510-6e3573cbfc3d","resolution":{"observed_at":"2026-08-01T20:07:13.035768Z","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":"2026-08-01T20:07:13.179765Z","title":"Advances in neural information processing systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":98,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:13.179765Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:00bbb14d116cc57f6d461456f77ff4f4c4f2c561ef818257b81d7185f2c8fd30","observation_id":"4dd234e0-81bd-42a4-bb04-74c4b13ec8ed","resolution":{"observed_at":"2026-08-01T20:07:13.179765Z","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":"2026-08-01T20:07:13.357640Z","title":"Mathematical Programming , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":99,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:13.357640Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:909a6fbf2e1e8b1f9cce4b1d7bd38dfbb1776b5c6b94980ae3a5aa8cc5f173ed","observation_id":"6d4e7ecf-0dd7-4579-9a75-aac48357513d","resolution":{"observed_at":"2026-08-01T20:07:13.357640Z","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":"2026-08-01T20:07:13.478929Z","title":"Advances in neural information processing systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets","version":1},"reference_index":100,"source":"arxiv_source","source_observed_at":"2026-08-01T20:07:13.478929Z"},"links":{"citing_paper":"/paper/2607.16761"},"observation_digest":"sha256:0666651650ca4e02dddc1f7d0fbddb89a71f6027f8ef531770788cea9adcd6d2","observation_id":"6c75ed4b-0870-4b41-a14c-f3c9bda3cf4f","resolution":{"observed_at":"2026-08-01T20:07:13.478929Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2607.16761","last_updated":"2026-07-18T10:57:27Z","latest_version":1,"primary_category":"stat.ML","snapshot_observed_at":"2026-08-08T21:46:27.170281Z","submitted_at":"2026-07-18T10:57:27Z","title":"Dropout and Random Gradient Masking Are Asymptotically Equivalent in Large ResNets"},"reference_resolution":{"displayed":100,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":97,"verified_exact":3,"verified_fuzzy":0},"total_outbound_references":114},"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":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 100 of 114 outbound references and 0 inbound Pith citation observations for arXiv:2607.16761."}