{"as_of":"2026-08-18T05:54:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:50fb7197144638214a7232278a59cd03618082d1189dc19bc61f9ebf8b93bc9d","coverage":[{"denominator":56,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":56,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-15T18:39:48.502591Z","state":"measured"},{"denominator":56,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":56,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-17T06:30:58.91139+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/2506.19396/citation-record","integrity":"/paper/2506.19396/integrity","json":"/paper/2506.19396/citation-record.json","paper":"/paper/2506.19396"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T18:39:48.238527Z","title":"write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.238527Z"},"links":{"citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:76c1dda5ff172c6ea265a3c61f58b071651aa01958e079adab2512d1cc30b404","observation_id":"42cf6aec-a17d-4899-af39-ea43814ef9ed","resolution":{"observed_at":"2026-08-15T18:39:48.238527Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T18:39:49.555933Z","title":"L., Gruber, L., Holzleitner, M., and Brandstetter, J","venue":null,"work_id":"aee6cb1b-aa59-47fe-97dd-104d246a64de","year":2024},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.244502Z"},"links":{"citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:9fa9d52d13d6e9af382dd715725a541fac2fd11d38d42d61d5f43e6e6a9b755d","observation_id":"8a2eab68-6454-4fb8-b550-680ece440a38","resolution":{"observed_at":"2026-08-15T18:39:49.560701Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T18:39:48.250022Z","title":"Y., Deiseroth, B., Cruz-Salinas, A","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.250022Z"},"links":{"citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:2deb0e9f499c7172f67abb624d5ca9ecb6a7533c9a835f0b3d3221d7525e9c0c","observation_id":"4a7da4ad-4a2d-4d18-926a-d0b0fe10188c","resolution":{"observed_at":"2026-08-15T18:39:48.250022Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T18:39:49.531196Z","title":"B., Hanin, B., and Pehlevan, C","venue":null,"work_id":"720712d7-22a5-4bcb-82ca-610937ee7b32","year":2024},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.255054Z"},"links":{"citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:c987d9eb798561dedd63b7556328dad6d22f2300b09c9517b0f3c5cdf4ef3fc8","observation_id":"d16b33f6-42eb-4541-a46d-e028e1e76f2c","resolution":{"observed_at":"2026-08-15T18:39:49.535867Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T18:39:48.259559Z","title":"B., Levine, M","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.259559Z"},"links":{"citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:2aa81f220e63d70c433cadf14916b89ca3ae46c2f352ba048234e69ffdf401df","observation_id":"190b7930-bf23-41e8-8b32-3133e04b3fed","resolution":{"observed_at":"2026-08-15T18:39:48.259559Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T18:39:49.514831Z","title":"Choose a transformer: Fourier or galerkin","venue":null,"work_id":"fa9f1cb1-7a40-433c-a9f3-813cc77bd3f1","year":2021},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.264718Z"},"links":{"citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:5d315c92a29fbce2544e5f0f14c1fb731734a2f776bf29e45ab38ddf9a40fc08","observation_id":"7bcd479d-f93e-480d-844b-5b023c273f6e","resolution":{"observed_at":"2026-08-15T18:39:49.519636Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T18:39:49.489013Z","title":"Principled architecture-aware scaling of hyperparameters","venue":null,"work_id":"dd6fc445-cc6f-4e71-be8d-4f6dbee8e73a","year":2024},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.269220Z"},"links":{"citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:45a4bc5f3362b52b24b46f94c079a413d576099e45a6b181f7f619043f3aafa7","observation_id":"677f9b7f-356e-4a64-81ae-cad28c2fd770","resolution":{"observed_at":"2026-08-15T18:39:49.494139Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T18:39:49.474338Z","title":"and Mishra, S","venue":null,"work_id":"75ea6362-2d71-4b6f-9989-33845784bdc6","year":2022},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.274953Z"},"links":{"citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:126e51cbb5bd589bca07bfdf9320ae8ac764b933d55d2f576673f551718ad382","observation_id":"12c69ddd-4c11-4214-a476-21137e75cb89","resolution":{"observed_at":"2026-08-15T18:39:49.479027Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2304.03208","last_updated":"2023-04-06T16:43:16Z","snapshot_observed_at":"2026-08-18T04:17:03.903884Z","submitted_at":"2023-04-06T16:43:16Z","title":"Cerebras-GPT: Open Compute-Optimal Language Models Trained on the Cerebras Wafer-Scale Cluster","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.03208","snapshot_observed_at":"2026-08-15T18:39:48.279372Z","title":"Cerebras-gpt: Open compute-optimal language models trained on the cerebras wafer-scale cluster","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.279372Z"},"links":{"cited_paper":"/paper/2304.03208","citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:330f9c6bc5cba28e975ff9e66ae72c2681382685369aa932a14ed394ef0570b6","observation_id":"c82d999f-4886-446c-81dd-2fa049f2fca6","resolution":{"observed_at":"2026-08-15T18:39:48.279372Z","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":"2026-08-15T18:39:48.284568Z","title":"Physics-informed inference time scaling via simulation-calibrated scientific machine learning","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.284568Z"},"links":{"citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:5273b6eb577e90dfaf79771b3a81de54b0c822189df8da997610e8cee05001f2","observation_id":"35e52478-7d3a-413d-9e60-ede82047b9bd","resolution":{"observed_at":"2026-08-15T18:39:48.284568Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T18:39:49.457693Z","title":"J., Zhao, J., Kossaifi, J., Li, Z., and Anandkumar, A","venue":null,"work_id":"85c24d7c-3a4a-4e6b-9c95-d512ff67fd9c","year":2024},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.289360Z"},"links":{"citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:6fc0829018ba0df5bde0c8bd78b8ca57fc0433b497d095c746770bd2abdec853","observation_id":"89b714d2-5737-4ceb-bf2a-d944c4440647","resolution":{"observed_at":"2026-08-15T18:39:49.463538Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T18:39:49.441427Z","title":"Multiwavelet-based operator learning for differential equations","venue":null,"work_id":"a2239a0d-0932-43cf-a419-abb7b542248d","year":2021},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.293697Z"},"links":{"citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:66fb9c13642b3b27c544bba479476894d6913252f7ba32425f111002bb0e18c9","observation_id":"5a7a8556-dac5-4d6f-9073-d398d3fdae8d","resolution":{"observed_at":"2026-08-15T18:39:49.446618Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T18:39:49.424882Z","title":"Solving high-dimensional partial differential equations using deep learning","venue":null,"work_id":"3bd566c6-20ca-4a0a-8a9e-f960d1f81c9b","year":2018},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.299051Z"},"links":{"citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:1047a5a289035159ffee74a7e8b0585e0ca2d69c67cc68aca08c45e9fb5b28db","observation_id":"40d82a80-ea9e-445b-b6fb-adeb0462dd03","resolution":{"observed_at":"2026-08-15T18:39:49.430483Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T18:39:49.408154Z","title":"Learning physics-informed neural networks without stacked back-propagation","venue":null,"work_id":"b827c99d-dfac-43c2-b8de-f75a7bc91c06","year":2023},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.303245Z"},"links":{"citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:6d7d6a1a8d0ab7376222d8e0f99794d1d302237594dc43a2616300a3d27fbed9","observation_id":"5e0ff353-b7e0-4684-8f44-e266eb513a53","resolution":{"observed_at":"2026-08-15T18:39:49.413178Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2010.14701","last_updated":"2020-11-06T04:16:36Z","snapshot_observed_at":"2026-07-06T10:09:17.078776Z","submitted_at":"2020-10-28T02:17:24Z","title":"Scaling Laws for Autoregressive Generative Modeling","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.14701","snapshot_observed_at":"2026-08-15T18:39:48.307620Z","title":"B., Dhariwal, P., Gray, S., et al","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.307620Z"},"links":{"cited_paper":"/paper/2010.14701","citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:f6e010305d5680bcb246ac8da698d1950195555d3a5385d493e15e927f532b5e","observation_id":"aa03964d-ae3e-4a62-913b-ff164f533f2e","resolution":{"observed_at":"2026-08-15T18:39:48.307620Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2203.15556","last_updated":"2022-03-29T13:38:03Z","snapshot_observed_at":"2026-08-09T19:52:33.533277Z","submitted_at":"2022-03-29T13:38:03Z","title":"Training Compute-Optimal Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.15556","snapshot_observed_at":"2026-08-15T18:39:48.312205Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.312205Z"},"links":{"cited_paper":"/paper/2203.15556","citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:7b5bb2dbd158c78ad0501f606bebd8d4cdcd5118d180cfdd428839a8463782ae","observation_id":"6b9e2874-f3bf-4cd4-a47a-1f08d3c94ade","resolution":{"observed_at":"2026-08-15T18:39:48.312205Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T18:39:49.393031Z","title":"Meta-auto-decoder for solving parametric partial differential equations","venue":null,"work_id":"3f0e2ce1-222f-41f6-90dd-19c6911cc7da","year":2022},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.317799Z"},"links":{"citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:b8b30126848cedaa40462f2c785283c054702707b8e5916ec74495836061f3dc","observation_id":"9d640d7e-9974-46fe-b8da-da18798edbdf","resolution":{"observed_at":"2026-08-15T18:39:49.397803Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T18:39:49.378173Z","title":"and Karakida, R","venue":null,"work_id":"a03e1622-8593-4c51-9af4-9392ff09fd77","year":2024},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.322086Z"},"links":{"citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:ac439c3049f1efcea82162c8099877100a62f43cd698d063a75689ac8171811c","observation_id":"5e09df85-7be1-42cc-a0bf-d808ae758509","resolution":{"observed_at":"2026-08-15T18:39:49.383359Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2104.03113","last_updated":"2021-04-15T10:03:37Z","snapshot_observed_at":"2026-08-16T18:33:18.216422Z","submitted_at":"2021-04-07T13:34:25Z","title":"Scaling Scaling Laws with Board Games","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2104.03113","snapshot_observed_at":"2026-08-15T18:39:48.326802Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.326802Z"},"links":{"cited_paper":"/paper/2104.03113","citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:a265214f58e747d845bdd481eae13cf6519f1d52d72bf30d4ab3ee467f61f563","observation_id":"7e42f225-f98e-4078-870f-a6e8cea239e1","resolution":{"observed_at":"2026-08-15T18:39:48.326802Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2001.08361","last_updated":"2020-01-23T03:59:20Z","snapshot_observed_at":"2026-08-13T17:41:53.092611Z","submitted_at":"2020-01-23T03:59:20Z","title":"Scaling Laws for Neural Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2001.08361","snapshot_observed_at":"2026-08-15T18:39:48.332170Z","title":"B., Chess, B., Child, R., Gray, S., Radford, A., Wu, J., and Amodei, D","venue":null,"work_id":null,"year":2001},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.332170Z"},"links":{"cited_paper":"/paper/2001.08361","citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:be8db177eb7580e27de3179355df2e83c90c1b04cd0daa0cf83d8f3829e8fa00","observation_id":"f2134980-75e1-4217-91b1-abba567d92f4","resolution":{"observed_at":"2026-08-15T18:39:48.332170Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T18:39:49.363482Z","title":"Solving parametric pde problems with artificial neural networks","venue":null,"work_id":"3d29c59e-62f2-42c4-9268-a7244930658c","year":2021},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.336699Z"},"links":{"citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:2ddb5e92f440ae4ff1acea1c4a201b7216e8d7a7f8f89a8c52cbf26ea57516fb","observation_id":"9158ffc5-2f5c-4f7e-ac29-83023316f915","resolution":{"observed_at":"2026-08-15T18:39:49.368013Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T18:39:49.348800Z","title":"and Kang, M","venue":null,"work_id":"33ac5921-c2a2-44cf-97ed-e63a67287787","year":2024},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.340960Z"},"links":{"citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:2013fa4f9d02d57dc36311a5678a740b08a43aaf2001f1d10a409c02017caca2","observation_id":"086ac93f-49bd-4c7d-a90f-eb39dc1d1412","resolution":{"observed_at":"2026-08-15T18:39:49.353620Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1412.6980","last_updated":"2017-01-30T01:27:54Z","snapshot_observed_at":"2026-08-17T19:26:44.032537Z","submitted_at":"2014-12-22T13:54:29Z","title":"Adam: A Method for Stochastic Optimization","version":9},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1412.6980","snapshot_observed_at":"2026-08-15T18:39:48.345143Z","title":null,"venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.345143Z"},"links":{"cited_paper":"/paper/1412.6980","citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:ea31016d418f2bfd15f537d2bf520c3cafd18fa3eeb04f3813ac4c04db504903","observation_id":"f9de858b-063c-4251-bf4e-43521e792a68","resolution":{"observed_at":"2026-08-15T18:39:48.345143Z","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":"2026-08-15T18:39:48.350709Z","title":"A., Alieva, A., Wang, Q., Brenner, M","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.350709Z"},"links":{"citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:ffb724a1d8f17ea64a47a90cfaef58f4947f25dffe2173878b9655a8eb1d0468","observation_id":"d4748e65-5339-4384-a7b6-cc965a827459","resolution":{"observed_at":"2026-08-15T18:39:48.350709Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T18:39:49.323444Z","title":"Understanding the expressivity and trainability of fourier neural operator: A mean-field perspective","venue":null,"work_id":"afc67e84-8c4b-4cac-b199-9350fb784c5d","year":2024},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.354797Z"},"links":{"citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:fc8a275f23f30800f4d6e11457d4df0e6f0f762ca0808e05235031ef36c679a2","observation_id":"1afb2c08-eea4-477f-abb3-ff346c7ed84e","resolution":{"observed_at":"2026-08-15T18:39:49.328581Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T18:39:49.308931Z","title":"On universal approximation and error bounds for fourier neural operators","venue":null,"work_id":"fc5b34ed-0351-45fc-b7c9-a5ec1029d556","year":2021},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.359895Z"},"links":{"citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:47caf971bde285adcc041ba0779a8a29dc4f32c7447d92a734dbb896cc332be9","observation_id":"a320a7bf-41d7-4fb4-ad0b-133d9300e664","resolution":{"observed_at":"2026-08-15T18:39:49.313953Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T18:39:48.366893Z","title":"Neural operator: Learning maps between function spaces with applications to pdes","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.366893Z"},"links":{"citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:641c434c6562744f3d269fb1b12c1dba405887b1d1696f2ec06db274e07150dd","observation_id":"9bbe94ec-8b6f-4fb0-8583-667ea1612bc0","resolution":{"observed_at":"2026-08-15T18:39:48.366893Z","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":"2026-08-15T18:39:48.371430Z","title":"and Dik, M","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.371430Z"},"links":{"citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:40c8b345a9b0931852a79b8f1446063c24e807dd786f1bee9b467ece5d681499","observation_id":"49beb876-7198-4ef8-9763-e2c02532e9bd","resolution":{"observed_at":"2026-08-15T18:39:48.371430Z","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":"2026-08-15T18:39:48.375934Z","title":"Codepde: An inference framework for llm-driven pde solver generation","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.375934Z"},"links":{"citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:8a1591fd58733eafcc6625810312b85c9dfe4aded7aca485b4706ee15bafbb9f","observation_id":"fef2a451-93e9-4c6c-9895-468a4afc9690","resolution":{"observed_at":"2026-08-15T18:39:48.375934Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T18:39:49.285060Z","title":"Multipole graph neural operator for parametric partial differential equations","venue":null,"work_id":"b23c95d1-ee2a-4877-aabb-e85a45f16a70","year":2020},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.380317Z"},"links":{"citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:7408bb8693f2d280e0430275ad973d836116d9b0a3a7a405ba56b44d6e3fa10a","observation_id":"12ba117f-0b6e-4ec3-b735-d3a03ef32e1d","resolution":{"observed_at":"2026-08-15T18:39:49.289786Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T18:39:48.384653Z","title":"B., Azizzadenesheli, K., liu, B., Bhattacharya, K., Stuart, A., and Anandkumar, A","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.384653Z"},"links":{"citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:4b1ede8bf84aebb5f5a26199f7c1902a0d371fa39f3b9df8eaad9ba6885a4176","observation_id":"78de09d4-ec20-44be-b70c-92e6fa2bdcea","resolution":{"observed_at":"2026-08-15T18:39:48.384653Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T18:39:49.260555Z","title":"Physics-informed neural operator for learning partial differential equations","venue":null,"work_id":"bc8dcaeb-102a-4e90-80c4-66d135252657","year":2024},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.389019Z"},"links":{"citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:295c1fdd5aeb9f86426ed45ca8e5deea914473ec853f17e94651286c7b0bdfe6","observation_id":"63af6c56-43ac-4bef-8ab3-ae59769d2cc8","resolution":{"observed_at":"2026-08-15T18:39:49.265543Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.05728","last_updated":"2025-02-13T23:19:42Z","snapshot_observed_at":"2026-08-16T22:23:39.037897Z","submitted_at":"2024-04-08T17:59:44Z","title":"An Empirical Study of $\\mu$P Learning Rate Transfer","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.05728","snapshot_observed_at":"2026-08-15T18:39:48.393629Z","title":"A large-scale exploration of -transfer","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.393629Z"},"links":{"cited_paper":"/paper/2404.05728","citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:804991bc481eac4089590235d1f189e92f32ebb4fd35b2d98bcf48043b814156","observation_id":"ea2dd1dc-5995-42a1-80f5-e909fc6e68b1","resolution":{"observed_at":"2026-08-15T18:39:48.393629Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T18:39:49.245319Z","title":"PDE -net: Learning PDE s from data","venue":null,"work_id":"e4a7d2d8-eb49-45c1-9ad9-148385affff3","year":2018},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.398369Z"},"links":{"citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:90d477d76a4e7cfcbd129d78f5e65a822bdabb49ed993ead1b4dfb33c928bcdb","observation_id":"5f765edc-3709-4058-91b6-a10d9cc4fc81","resolution":{"observed_at":"2026-08-15T18:39:49.250409Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T18:39:48.403075Z","title":"Pde-net 2.0: Learning pdes from data with a numeric-symbolic hybrid deep network","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.403075Z"},"links":{"citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:7b328ad726b97e4adf16512252ce038016278681dfe1808c2f9e027e3c4e91c9","observation_id":"70bc079c-1a4c-4cf5-9647-ed95a037c430","resolution":{"observed_at":"2026-08-15T18:39:48.403075Z","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":"2026-08-15T18:39:48.407984Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.407984Z"},"links":{"citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:3fdea71353f2b7e61f17c8b0a101760db3dbc296464601cf8660a81f7b08e05b","observation_id":"e655de7e-be4e-44c3-b50b-134aabf6493e","resolution":{"observed_at":"2026-08-15T18:39:48.407984Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T18:39:49.212150Z","title":"Super consistency of neural network landscapes and learning rate transfer","venue":null,"work_id":"fe7f15a6-7b2b-4e8f-8af8-c2aba330a414","year":2024},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.412360Z"},"links":{"citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:3a030ef72fb04bf6a5e4b31afb2c5ab4e84c89a837ecce9866f9b8571f68315b","observation_id":"1fae80f4-2b2d-47fb-a550-cf6b9dca7898","resolution":{"observed_at":"2026-08-15T18:39:49.216926Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T18:39:48.416678Z","title":"Gpt-4 technical report, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.416678Z"},"links":{"citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:5c8bc03c438fc9ca44343160913cb0bf4e966c4744f1d614f2eac360e45195d9","observation_id":"ffaaa5b8-dbb0-4b13-8f45-71e45ba06f91","resolution":{"observed_at":"2026-08-15T18:39:48.416678Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T18:39:49.187104Z","title":"On the difficulty of training recurrent neural networks","venue":null,"work_id":"c59a4005-be7f-4a08-be35-faea07c3d25a","year":2013},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.421294Z"},"links":{"citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:3b0a18c78c579985cbd6edbc145d90dcc8e9b46c87ee33c1f3d555ea8955f5a9","observation_id":"3d40a94e-792f-4030-b99c-8a5a1520d11f","resolution":{"observed_at":"2026-08-15T18:39:49.192527Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T18:39:49.171749Z","title":"Py T orch: An imperative style, high-performance deep learning library","venue":null,"work_id":"cf9c8a4d-b5c7-4826-a86e-7244f48d700e","year":2019},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.426739Z"},"links":{"citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:e8e47c06979d8cd0a2fa9eac4e9e02096ebc0d93d282eba2c94ce14b256b255d","observation_id":"f049ca5e-1edd-4414-a02a-cb62d37ed0a2","resolution":{"observed_at":"2026-08-15T18:39:49.176735Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T18:39:48.431922Z","title":"and Xie, S","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.431922Z"},"links":{"citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:5b7ffec087d3b7587a86f6b0ad9d05fc7489fecd0ff514f0c9712e53b9d374d9","observation_id":"164843dc-b824-44e2-bfad-4f9441bfbe80","resolution":{"observed_at":"2026-08-15T18:39:48.431922Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T18:39:49.148119Z","title":"A., George, R","venue":null,"work_id":"fd54341c-fdd5-477a-824a-0c6dba804e90","year":2024},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.436138Z"},"links":{"citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:88dbf98f94996592301278e152da0a79a43fcb2b8a09465eccdba35d4b8128e6","observation_id":"cd23f720-25b8-4a56-b3fa-06c5ffd2eeee","resolution":{"observed_at":"2026-08-15T18:39:49.153358Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T18:39:48.441795Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.441795Z"},"links":{"citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:669eedf34360a776a7d566456d93304d6a4a19639165eece16186db403f3f0b7","observation_id":"058cb8af-5ea5-4c58-90f2-fd420c975743","resolution":{"observed_at":"2026-08-15T18:39:48.441795Z","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":"2026-08-15T18:39:48.446217Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.446217Z"},"links":{"citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:929de0f1aa62b3058bebb08e3445071f7562fbceda3b8d216ed56d460ee9378c","observation_id":"59476254-8c07-496a-bde2-503d7beefee4","resolution":{"observed_at":"2026-08-15T18:39:48.446217Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T18:39:49.113801Z","title":"and Spiliopoulos, K","venue":null,"work_id":"47389369-4811-4288-bf60-e0356f574494","year":2018},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.450527Z"},"links":{"citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:899c6a9ce09a11dcbb7603db19d9447b939090b1046ff94afd6bfbb88d360181","observation_id":"4472177c-3f24-4442-af9c-9585fcd5c292","resolution":{"observed_at":"2026-08-15T18:39:49.118593Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2408.03314","last_updated":"2024-08-06T17:35:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-08-06T17:35:05Z","title":"Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.03314","snapshot_observed_at":"2026-08-15T18:39:48.455050Z","title":"Scaling llm test-time compute optimally can be more effective than scaling model parameters","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.455050Z"},"links":{"cited_paper":"/paper/2408.03314","citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:3bb1f32162d012e35c6153351639cff399b373fc25db7393ec3e10268f2d400c","observation_id":"2591fe44-49b4-4854-b0bc-54fe41031325","resolution":{"observed_at":"2026-08-15T18:39:48.455050Z","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":"2026-08-15T18:39:48.460230Z","title":"High-dimensional probability: An introduction with applications in data science, volume 47","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.460230Z"},"links":{"citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:1d77f31e7ff175f8e1c543008e9ba7fbad939a82544fa2fba3d1c7f1cc11ccbd","observation_id":"f4eea107-d878-4828-b56d-9cea563a96c8","resolution":{"observed_at":"2026-08-15T18:39:48.460230Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T18:39:49.089358Z","title":"Is L^2 physics-informed loss always suitable for training physics-informed neural network? In Advances in Neural Information Processing Systems, 2022","venue":null,"work_id":"54c0f34d-e9a0-40e6-b2e3-2fce92cde529","year":2022},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.464748Z"},"links":{"citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:ab251e1cde641eff03e1ad61fd6feefadc406f3c47b548561725f196236ab7de","observation_id":"d58031c2-931c-4c43-931c-1816d84f4a70","resolution":{"observed_at":"2026-08-15T18:39:49.094209Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2408.05177","last_updated":"2026-07-26T05:09:22Z","snapshot_observed_at":"2026-08-16T13:27:25.044097Z","submitted_at":"2024-08-09T17:05:45Z","title":"Coarse Graining with Neural Operators for Simulating Chaotic Systems","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.05177","snapshot_observed_at":"2026-08-15T18:39:48.469255Z","title":"Beyond closure models: Learning chaotic-systems via physics-informed neural operators","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":49,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.469255Z"},"links":{"cited_paper":"/paper/2408.05177","citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:4468945fe9a0b09970db11fec11a6448e2250db5d309d9a3a11df7b41259dd93","observation_id":"5aa66ef5-d60d-41e4-8661-01dc10a921f0","resolution":{"observed_at":"2026-08-15T18:39:48.469255Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.00724","last_updated":"2025-03-03T07:53:32Z","snapshot_observed_at":"2026-08-13T03:06:10.986532Z","submitted_at":"2024-08-01T17:16:04Z","title":"Inference Scaling Laws: An Empirical Analysis of Compute-Optimal Inference for Problem-Solving with Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.00724","snapshot_observed_at":"2026-08-15T18:39:48.474681Z","title":"Inference scaling laws: An empirical analysis of compute-optimal inference for problem-solving with language models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":50,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.474681Z"},"links":{"cited_paper":"/paper/2408.00724","citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:ee0b5b9958b4e17fb639533fcc4b836f063beea725364b470be5dec495e6a4ca","observation_id":"caa70145-b295-4850-882a-5d5c7e16afef","resolution":{"observed_at":"2026-08-15T18:39:48.474681Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T18:39:49.074678Z","title":"and Hu, E","venue":null,"work_id":"92af9045-3211-4e4d-90c7-7da668dabfd8","year":2021},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":51,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.479650Z"},"links":{"citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:a19453394111ee629b5b1d6528ae6d1096f7999f46d5ea32c87d3af9b79b131a","observation_id":"72a991f9-6d5a-41c0-9e6e-a84d7cdb54c0","resolution":{"observed_at":"2026-08-15T18:39:49.079283Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2203.03466","last_updated":"2022-03-28T08:12:14Z","snapshot_observed_at":"2026-08-16T17:16:25.053180Z","submitted_at":"2022-03-07T15:37:35Z","title":"Tensor Programs V: Tuning Large Neural Networks via Zero-Shot Hyperparameter Transfer","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.03466","snapshot_observed_at":"2026-08-15T18:39:48.483926Z","title":"J., Babuschkin, I., Sidor, S., Liu, X., Farhi, D., Ryder, N., Pachocki, J., Chen, W., and Gao, J","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":52,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.483926Z"},"links":{"cited_paper":"/paper/2203.03466","citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:4e10f0b98f83210499591b252035f6babeeebb76bb28f6bc32ae77fb90cf8d27","observation_id":"5cbba771-d5f1-4a45-947a-98ab5715c760","resolution":{"observed_at":"2026-08-15T18:39:48.483926Z","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":"2026-08-15T18:39:48.488583Z","title":"Tensor programs VI : Feature learning in infinite depth neural networks","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":53,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.488583Z"},"links":{"citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:4c71e2f8358a6c5cfc7ad3ebe2cb6dfe68f393c495e39a97efa45d62fa1e295a","observation_id":"2f1f2781-7fe7-4493-ac68-a857bd583554","resolution":{"observed_at":"2026-08-15T18:39:48.488583Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T18:39:49.049708Z","title":"Pdeformer: Towards a foundation model for one-dimensional partial differential equations","venue":null,"work_id":"fdf455f1-978c-46df-9e1d-87423bb34569","year":2024},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":54,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.492883Z"},"links":{"citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:a71ae9eb67ed37ad3a7611950ef5c1bf5d27df51afc09d1a384bc6007ebe6a30","observation_id":"31d75605-6b2d-4dd9-b1b9-b3ed9d68b90e","resolution":{"observed_at":"2026-08-15T18:39:49.054470Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2206.10789","last_updated":"2022-06-22T01:11:29Z","snapshot_observed_at":"2026-08-14T02:29:38.306439Z","submitted_at":"2022-06-22T01:11:29Z","title":"Scaling Autoregressive Models for Content-Rich Text-to-Image Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2206.10789","snapshot_observed_at":"2026-08-15T18:39:48.497883Z","title":"Y., Luong, T., Baid, G., Wang, Z., Vasudevan, V., Ku, A., Yang, Y., Ayan, B","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":55,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.497883Z"},"links":{"cited_paper":"/paper/2206.10789","citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:e71c230935e44050743e3e83ba566468907742aba93d80de1573791b1853d419","observation_id":"90d8d3da-c749-4c1c-9466-5fde15666449","resolution":{"observed_at":"2026-08-15T18:39:48.497883Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T18:39:49.030467Z","title":"Weak adversarial networks for high-dimensional partial differential equations","venue":null,"work_id":"aa8b4456-de36-45b3-90f1-8c37119299cf","year":2020},"citing_paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators","version":1},"reference_index":56,"source":"arxiv_source","source_observed_at":"2026-08-15T18:39:48.502591Z"},"links":{"citing_paper":"/paper/2506.19396"},"observation_digest":"sha256:d4f3517ae186013f6284993dbb541b0312bc42142380433333e67fab223293ef","observation_id":"7f5e98f3-72e0-4c9d-bb4f-04a19ee116cc","resolution":{"observed_at":"2026-08-15T18:39:49.039414Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2506.19396","last_updated":"2025-06-24T07:53:34Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-15T18:30:23.167888Z","submitted_at":"2025-06-24T07:53:34Z","title":"Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators"},"reference_resolution":{"displayed":56,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":29,"verified_exact":0,"verified_fuzzy":27},"total_outbound_references":56},"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":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 56 of 56 outbound references and 0 inbound Pith citation observations for arXiv:2506.19396."}