{"as_of":"2026-08-13T11:09:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:3ed1a979b5aac00ccfbb3f22544617495fdc9ada2f2d179d41642d81ce14e0f5","coverage":[{"denominator":90,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":90,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-05T20:19:12.496555Z","state":"measured"},{"denominator":90,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":90,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-13T06:32:02.005865+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/2508.10840/citation-record","integrity":"/paper/2508.10840/integrity","json":"/paper/2508.10840/citation-record.json","paper":"/paper/2508.10840"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2005.00928","last_updated":"2020-05-31T16:59:40Z","snapshot_observed_at":"2026-08-10T11:20:26.295031Z","submitted_at":"2020-05-02T21:45:27Z","title":"Quantifying Attention Flow in Transformers","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2005.00928","snapshot_observed_at":"2026-08-05T20:19:02.105165Z","title":"Abnar and W","venue":null,"work_id":null,"year":2005},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:02.105165Z"},"links":{"cited_paper":"/paper/2005.00928","citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:ba2c67f7a9c8ed678c30854d37f640bc8e7ec4df11b63939e016accff02df509","observation_id":"7eb3a107-96c1-4951-881f-f8b38204efee","resolution":{"observed_at":"2026-08-05T20:19:02.105165Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2111.04263","last_updated":"2021-11-09T16:37:10Z","snapshot_observed_at":"2026-08-06T07:03:02.521207Z","submitted_at":"2021-11-08T03:58:28Z","title":"Federated Learning Based on Dynamic Regularization","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2111.04263","snapshot_observed_at":"2026-08-05T20:19:02.157280Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:02.157280Z"},"links":{"cited_paper":"/paper/2111.04263","citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:33d0e5a25b157dcdf439a2a2e89c5af81e344d9c31a0534bf33db60f0204e8d1","observation_id":"92e11ab8-45aa-43e8-8e81-4d6d1f371385","resolution":{"observed_at":"2026-08-05T20:19:02.157280Z","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":"2026-08-05T20:19:02.277559Z","title":"Achituve, A","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:02.277559Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:e7136c019a3ecde3a31227e051fa52deace2fbbb404f43971bee4aae7ad6cda4","observation_id":"eb5c03ff-013c-4182-a27b-a7142a225260","resolution":{"observed_at":"2026-08-05T20:19:02.277559Z","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":"2026-08-05T20:19:02.381913Z","title":"Alberti, A","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:02.381913Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:6560f8a78cce194724275ce59f6dd40ed147e6a3f9b1e5c0b320890de8497413","observation_id":"0835fc43-3b04-4806-a6fe-adb235f81091","resolution":{"observed_at":"2026-08-05T20:19:02.381913Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1912.00818","last_updated":"2019-12-02T14:29:00Z","snapshot_observed_at":"2026-08-12T16:18:55.704115Z","submitted_at":"2019-12-02T14:29:00Z","title":"Federated Learning with Personalization Layers","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.00818","snapshot_observed_at":"2026-08-05T20:19:02.438852Z","title":null,"venue":null,"work_id":null,"year":1912},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:02.438852Z"},"links":{"cited_paper":"/paper/1912.00818","citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:052508f6a41411e7f54af301008941eab9f74dfc7eb25bb48f10289909a9f47a","observation_id":"01518d65-eca5-4d3d-96aa-5a2b6c8d853e","resolution":{"observed_at":"2026-08-05T20:19:02.438852Z","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":"2026-08-05T20:19:02.572208Z","title":"Ashraf, F","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:02.572208Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:5e0872b56b5e63b401db8d71c9624123e46a0dcdc4e7f46142df3d4c93261552","observation_id":"42f4602f-0039-469a-9209-cbcfc872c1b9","resolution":{"observed_at":"2026-08-05T20:19:02.572208Z","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":"2026-08-05T20:19:02.702324Z","title":"Caron, H","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:02.702324Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:4b5c0884133809a2d1844e7a63c137441bbd072711ccb1e973b909a3adf0567f","observation_id":"1e681b38-2068-4d15-a6e1-24e6a9aa0a5d","resolution":{"observed_at":"2026-08-05T20:19:02.702324Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2107.00778","last_updated":"2022-07-11T02:47:28Z","snapshot_observed_at":"2026-08-09T03:11:40.819888Z","submitted_at":"2021-07-02T00:25:48Z","title":"On Bridging Generic and Personalized Federated Learning for Image Classification","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2107.00778","snapshot_observed_at":"2026-08-05T20:19:02.856519Z","title":"Chen and W.-L","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:02.856519Z"},"links":{"cited_paper":"/paper/2107.00778","citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:32a459514365fd469a2d3d01770f0bf31ebc5a8689215863d2fa50dbb1123e8f","observation_id":"e9d1d401-b044-4c6c-87b9-75da603e1ff9","resolution":{"observed_at":"2026-08-05T20:19:02.856519Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2206.11488","last_updated":"2023-03-23T03:27:40Z","snapshot_observed_at":"2026-08-12T22:15:18.988296Z","submitted_at":"2022-06-23T06:02:33Z","title":"On the Importance and Applicability of Pre-Training for Federated Learning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2206.11488","snapshot_observed_at":"2026-08-05T20:19:02.973609Z","title":"Chen, C.-H","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:02.973609Z"},"links":{"cited_paper":"/paper/2206.11488","citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:d837a2e6e77a849d1d0afa9a25b9787d36b34c8e2d23bbfb5d4f6f951fe5c8d6","observation_id":"09b1e05e-494b-4989-b2da-ee19e65a260b","resolution":{"observed_at":"2026-08-05T20:19:02.973609Z","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":"2026-08-05T20:19:03.088431Z","title":"Collins, H","venue":null,"work_id":null,"year":2089},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:03.088431Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:995ea3ed37d304b9171a23391a589167428a817a525a67f86ea355e9c49d885d","observation_id":"b7e7ccaf-0f7e-409b-9c5e-e370e0672cd7","resolution":{"observed_at":"2026-08-05T20:19:03.088431Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2010.11929","last_updated":"2021-06-03T13:08:56Z","snapshot_observed_at":"2026-08-13T02:40:23.887636Z","submitted_at":"2020-10-22T17:55:59Z","title":"An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.11929","snapshot_observed_at":"2026-08-05T20:19:03.245843Z","title":"Dosovitskiy, L","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:03.245843Z"},"links":{"cited_paper":"/paper/2010.11929","citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:3b6a5ce464963ae950ccdc1fc00883225783081021101faaefbf7358edfa4836","observation_id":"be02abcc-1586-4ca1-bffd-104a8aec5bbd","resolution":{"observed_at":"2026-08-05T20:19:03.245843Z","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":"2026-08-05T20:19:03.465650Z","title":"Fallah, A","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:03.465650Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:c577b154d51c42c4ff2753d96d1787337eeef34fde0a8fc1629b52bd75c29d4e","observation_id":"d896b6a2-c653-4a0b-9911-7a6674532ed2","resolution":{"observed_at":"2026-08-05T20:19:03.465650Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.04686","last_updated":"2024-12-19T03:09:23Z","snapshot_observed_at":"2026-08-13T05:29:53.561038Z","submitted_at":"2023-11-08T13:46:58Z","title":"Robust and Communication-Efficient Federated Domain Adaptation via Random Features","version":2},"cited_work":{"arxiv_id":"2311.04686","doi":null,"metadata_source":"pith","pith_arxiv_id":"2311.04686","snapshot_observed_at":"2026-08-05T20:19:12.773836Z","title":"Robust and Communication-Efficient Federated Domain Adaptation via Random Features","venue":"cs.LG","work_id":"055aefde-909c-43f0-9321-b84dd44a795d","year":2023},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:03.628842Z"},"links":{"cited_paper":"/paper/2311.04686","citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:9bbe8430b7ba3e0681f3844ff0caaf08e40a69aecd890173e08f6f69325c78bd","observation_id":"1fe7d2a1-2a40-4f00-93b1-876219edbe73","resolution":{"observed_at":"2026-08-05T20:19:12.814615Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-05T20:19:03.767026Z","title":"Ganin and V","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:03.767026Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:cfafc4b81a06182e26aa5e7e14b0fcbd573ad7a8503813cdcf32aa8478ce044a","observation_id":"f7e57d50-c3dd-4a1c-a3e7-3e92d4184124","resolution":{"observed_at":"2026-08-05T20:19:03.767026Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1811.12231","last_updated":"2022-11-09T23:15:15Z","snapshot_observed_at":"2026-08-02T03:51:09.933624Z","submitted_at":"2018-11-29T15:04:05Z","title":"ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1811.12231","snapshot_observed_at":"2026-08-05T20:19:03.956798Z","title":"Geirhos, P","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:03.956798Z"},"links":{"cited_paper":"/paper/1811.12231","citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:bb64aee13f223ea60446da8216b8f7ad8fed6bbe61ad3727de6ee5f24493a290","observation_id":"ea7bb462-9e85-4f35-8bb7-3a9c9923a95a","resolution":{"observed_at":"2026-08-05T20:19:03.956798Z","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":"2026-08-05T20:19:04.088976Z","title":"Ghosh, J","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:04.088976Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:b1582f163f6cd102e73642dfeadb9373868959318582f99a102893b9d98fdfe4","observation_id":"4a6c5f6a-7e1d-452a-8517-7f61c47fb831","resolution":{"observed_at":"2026-08-05T20:19:04.088976Z","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":"2026-08-05T20:19:04.233829Z","title":null,"venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:04.233829Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:2c70d3a4be157ec86d79eef6d62c5885a857feaf4e72f0e87f6c0fe385f1d4b2","observation_id":"45b7b477-5f27-444b-86c0-3efb66d72b46","resolution":{"observed_at":"2026-08-05T20:19:04.233829Z","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":"2026-08-05T20:19:04.337627Z","title":"Griffin, A","venue":null,"work_id":null,"year":2007},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:04.337627Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:f90f03b7a55e968889e90ed61607b6e0228ea7ea54ea91ab648ab0d90bdea7e0","observation_id":"be7ec21f-ea88-47c1-9fe6-ee9dae4c0a48","resolution":{"observed_at":"2026-08-05T20:19:04.337627Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1609.09106","last_updated":"2016-12-01T10:08:15Z","snapshot_observed_at":"2026-08-08T11:39:44.107967Z","submitted_at":"2016-09-27T05:57:00Z","title":"HyperNetworks","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1609.09106","snapshot_observed_at":"2026-08-05T20:19:04.506685Z","title":null,"venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:04.506685Z"},"links":{"cited_paper":"/paper/1609.09106","citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:4bfe4e0dfe1c6b827a94bd63e5152abdfc7cb2a0a151efb943d21963c20435e3","observation_id":"9a4f08ea-dfc1-436b-8533-30cd1e7248cc","resolution":{"observed_at":"2026-08-05T20:19:04.506685Z","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":"2026-08-05T20:19:21.098028Z","title":"Hanzely, S","venue":null,"work_id":"348ce4f8-801e-4e01-ba61-444d34f01549","year":2020},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:04.638048Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:e1aa32e764f39767d5c3c71df296f60885480bd6f4ffd0d427c7e93b35266a45","observation_id":"5d25bed1-d403-4e42-8ecd-f55a300c9908","resolution":{"observed_at":"2026-08-05T20:19:21.202741Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-05T20:19:20.951741Z","title":null,"venue":null,"work_id":"dac5a4cb-b90e-4eb3-b4dd-cbd839a4720a","year":2016},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:04.760619Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:f73a8fb59442d9a4dc94c8a78b5db83eeb4e5727bc891e510a9aeb49240617e6","observation_id":"af73ec09-b4f3-41a4-9297-d63b2539cb00","resolution":{"observed_at":"2026-08-05T20:19:21.006243Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-05T20:19:20.772554Z","title":"Hoyer, D","venue":null,"work_id":"d436b3ac-53e3-47e8-9ff6-f47fe6ec87c2","year":2022},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:04.867300Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:8ea82fc4a309b840cbd16dddf2d1cfadf4e2e0aa68ed513b70495a7ac7a6f6b0","observation_id":"d3282607-a99d-4ea7-8671-6fc9c3a2e596","resolution":{"observed_at":"2026-08-05T20:19:20.866581Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-05T20:19:20.603935Z","title":"Hsieh, A","venue":null,"work_id":"e7299775-f3cd-489a-81a7-24516e7437a8","year":2020},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:04.965648Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:bbe2b92b372e6a26a42dd941059020ac9e60234c3028802040f4eae8979d4d53","observation_id":"5dd3971d-e4b4-4c76-a308-47d258c772b6","resolution":{"observed_at":"2026-08-05T20:19:20.684749Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-05T20:19:20.448769Z","title":null,"venue":null,"work_id":"fa68ac7e-d687-47eb-93ab-e12dd52fe742","year":2020},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:05.141845Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:9e5160eeabc1e5a47dc1b7cb04fe7f94384fc32cbafdb90c42ae50059d8fc1a1","observation_id":"44efbc90-5637-49d9-ac4d-e0de651d6d7a","resolution":{"observed_at":"2026-08-05T20:19:20.514332Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-05T20:19:20.320687Z","title":"Huang, L","venue":null,"work_id":"5962a0ce-5796-4eed-a08b-cb4d50458208","year":2021},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:05.275011Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:1b2bfbc3a4cacc404fda913b8cfa373994a1b70f9bd60b149517b32aa5ccd06a","observation_id":"71a1912b-c1fd-45df-acb5-be590745c681","resolution":{"observed_at":"2026-08-05T20:19:20.388844Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-05T20:19:20.158753Z","title":"Johnson, M","venue":null,"work_id":"5b4fbfd3-1c1d-4732-bd25-056c7a5daed3","year":2019},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:05.372608Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:64c191f0c749bbcbd8c39ea0ff7d1a3edf32773abd9df5acd6f3cec38f7dcdc4","observation_id":"9713aa20-183f-41c6-994f-138ae85997ef","resolution":{"observed_at":"2026-08-05T20:19:20.239283Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-05T20:19:19.973992Z","title":null,"venue":null,"work_id":"03d7f228-f151-4362-9675-fcf34a676c97","year":2020},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:05.496383Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:f58bca96251ae8c395727910b5ab2d1fed74c8205eb1e184d1420240f0d1ce8e","observation_id":"772074f0-7da7-4979-ab09-5891e5ef1ee1","resolution":{"observed_at":"2026-08-05T20:19:20.060656Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2008.03606","last_updated":"2021-06-08T08:14:57Z","snapshot_observed_at":"2026-08-10T13:39:15.908251Z","submitted_at":"2020-08-08T21:55:07Z","title":"Mime: Mimicking Centralized Stochastic Algorithms in Federated Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2008.03606","snapshot_observed_at":"2026-08-05T20:19:05.655015Z","title":null,"venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:05.655015Z"},"links":{"cited_paper":"/paper/2008.03606","citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:7b773c7b571bf1aade5a473f21b905b7e9b4c3be9763fbb1a6dbb43e41d0358d","observation_id":"8cb534a3-488e-4bd9-8879-46b1821e8d09","resolution":{"observed_at":"2026-08-05T20:19:05.655015Z","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":"2026-08-05T20:19:19.802959Z","title":null,"venue":null,"work_id":"368d1962-86d0-4360-9e1f-010a3870da44","year":2020},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:05.769218Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:43187cb43d9b1e4fc5d427d26ab4b2b5f3647a751706fa59c5725ac9bd8a19f1","observation_id":"9a3d5980-e3e0-44bd-a055-3e2658209a29","resolution":{"observed_at":"2026-08-05T20:19:19.876978Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-05T20:19:19.627884Z","title":"Kermany, K","venue":null,"work_id":"93eef638-5a15-4093-908e-f6d24d1f60a1","year":2018},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:05.875716Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:4f43e8eb186633e596b16de8a9de33deec7d662ebb43fd9afd532ff31d23992d","observation_id":"ac2bf920-f413-47bc-9754-e95b9a7af673","resolution":{"observed_at":"2026-08-05T20:19:19.732976Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-05T20:19:19.450017Z","title":null,"venue":null,"work_id":"ec86930f-35b3-4b25-bfa0-5a996c043211","year":2024},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:06.007746Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:e651c0fe7455e55fe4b5f7c89f381849cde32485969333a2225d210c7a3dfab3","observation_id":"d8537782-6a5a-48e3-9ebf-c5f688404aea","resolution":{"observed_at":"2026-08-05T20:19:19.531195Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-05T20:19:06.090125Z","title":"Krizhevsky, G","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:06.090125Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:9dd9fc56f01a3342d008183ef2f680afd3d6c8e5ed1160eef7ec85688be381b5","observation_id":"52c1a269-87eb-4813-8056-7b0164cecb46","resolution":{"observed_at":"2026-08-05T20:19:06.090125Z","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":"2026-08-05T20:19:19.301886Z","title":null,"venue":null,"work_id":"275c5234-450b-45a6-8b26-82cf96783e94","year":2021},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:06.235424Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:ae8daefb152f69d87f4e9299eb673c453b67004bed44080fae7ebd53ae998475","observation_id":"4ae4cb70-ae9b-4413-b264-982975a2da37","resolution":{"observed_at":"2026-08-05T20:19:19.395380Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1910.03581","last_updated":"2019-10-08T18:00:00Z","snapshot_observed_at":"2026-08-12T16:52:56.503034Z","submitted_at":"2019-10-08T18:00:00Z","title":"FedMD: Heterogenous Federated Learning via Model Distillation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.03581","snapshot_observed_at":"2026-08-05T20:19:06.321027Z","title":"Li and J","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:06.321027Z"},"links":{"cited_paper":"/paper/1910.03581","citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:409e4221891f553a4bd6c15d9c7efc6f4f53619405182f01049aec7cb263c678","observation_id":"3c3b7dfe-71b1-4bfa-9bc0-ede69c42e1f1","resolution":{"observed_at":"2026-08-05T20:19:06.321027Z","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":"2026-08-05T20:19:19.150873Z","title":null,"venue":null,"work_id":"a9c76391-dff8-49d6-b339-9be8bea2cece","year":2023},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:06.382527Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:40c867d3903a55dd671421827d8bf1f02209556f15b2b388d57b1a57cbe215ad","observation_id":"05212ec4-6f92-415f-b2e0-3df80ec51097","resolution":{"observed_at":"2026-08-05T20:19:19.198313Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-05T20:19:06.436860Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:06.436860Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:8f0eaa03184932fd38f3b07a5231dac277238f94bad497f729cfe76c6a78342c","observation_id":"9f899572-3d22-4740-abbd-302ccd76b063","resolution":{"observed_at":"2026-08-05T20:19:06.436860Z","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":"2026-08-05T20:19:19.034067Z","title":null,"venue":null,"work_id":"1ad036df-d361-45fc-b2af-f37f58176b0e","year":2021},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:06.517570Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:f88bade6098fe1cd3047174acbcd6ecd1aeb4d3e509a253e76e2a757f2d97b16","observation_id":"04c74f9b-362e-4d79-b3d5-619f51fc04fd","resolution":{"observed_at":"2026-08-05T20:19:19.072625Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2102.07623","last_updated":"2021-05-11T14:21:00Z","snapshot_observed_at":"2026-08-09T15:59:31.104495Z","submitted_at":"2021-02-15T16:04:10Z","title":"FedBN: Federated Learning on Non-IID Features via Local Batch Normalization","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2102.07623","snapshot_observed_at":"2026-08-05T20:19:06.606351Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:06.606351Z"},"links":{"cited_paper":"/paper/2102.07623","citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:ef5eecdea33ba38a4255cd11b70a3e3920070eba3f12f644817d3f68480431db","observation_id":"eeed44e1-a1ae-4e65-8c98-c2236bfa095d","resolution":{"observed_at":"2026-08-05T20:19:06.606351Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1603.04779","last_updated":"2016-11-08T06:11:30Z","snapshot_observed_at":"2026-07-06T04:49:33.981350Z","submitted_at":"2016-03-15T17:44:32Z","title":"Revisiting Batch Normalization For Practical Domain Adaptation","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1603.04779","snapshot_observed_at":"2026-08-05T20:19:06.764445Z","title":null,"venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:06.764445Z"},"links":{"cited_paper":"/paper/1603.04779","citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:fd3cad579ec38f08325caf4315b50e0e7c6146a0d2f1a5e543ab73b4a6e9efac","observation_id":"cdcf5a42-2679-4a94-bd53-50f748e9d012","resolution":{"observed_at":"2026-08-05T20:19:06.764445Z","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":"2026-08-05T20:19:18.846146Z","title":null,"venue":null,"work_id":"8238ace2-c650-4b66-be83-cf428e266b05","year":1949},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:06.859509Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:894618b7e1237d72a6a7c85aee7dceac5f05c2c93ac74d847e3619381d44e153","observation_id":"fbe8a8ac-8658-4c5f-8ac8-dffc3cf39d87","resolution":{"observed_at":"2026-08-05T20:19:18.918608Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-05T20:19:18.736288Z","title":null,"venue":null,"work_id":"1222d0ad-a98f-4d81-94d5-1ef216d451fa","year":2023},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:06.955898Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:a45753571c77c5f9dee21f6492a1ac776e0b94a4d923daeb75709abf5f3776b1","observation_id":"715ee60b-407a-4b6a-91e8-014e4c108767","resolution":{"observed_at":"2026-08-05T20:19:18.784714Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-05T20:19:18.608791Z","title":null,"venue":null,"work_id":"cba20889-2a41-4a07-8ac9-57248fcc66c3","year":2019},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:07.038668Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:481171d1809baf254e2daf811ceda6879c3c23eda7d4240244dbc42d7d6d352c","observation_id":"65686d8d-fada-4ba8-96fb-4ae1ee20e15b","resolution":{"observed_at":"2026-08-05T20:19:18.669092Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2001.01523","last_updated":"2020-07-14T08:12:35Z","snapshot_observed_at":"2026-08-10T05:11:49.961881Z","submitted_at":"2020-01-06T12:40:21Z","title":"Think Locally, Act Globally: Federated Learning with Local and Global Representations","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2001.01523","snapshot_observed_at":"2026-08-05T20:19:07.124917Z","title":null,"venue":null,"work_id":null,"year":2001},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:07.124917Z"},"links":{"cited_paper":"/paper/2001.01523","citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:5bd08f1777d1d191e3fd463c15db1cc121f8162e0765bd32d936a4e02c71420a","observation_id":"1c89d1cb-32e7-454e-ab36-b06819324026","resolution":{"observed_at":"2026-08-05T20:19:07.124917Z","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":"2026-08-05T20:19:18.465087Z","title":null,"venue":null,"work_id":"30701e97-5b06-4ed0-8e76-f97ad15c2ad4","year":2021},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:07.269512Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:95e43fc84d0a344637cfd57d5d6c104929c34760db3915345e43108601f26765","observation_id":"aacc9534-a13c-477f-84f7-ac14ac25b392","resolution":{"observed_at":"2026-08-05T20:19:18.538051Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-05T20:19:18.334771Z","title":null,"venue":null,"work_id":"a9d9f12a-6ed4-4752-96ea-b80032a2b393","year":2021},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:07.408175Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:f6fb1231666497e6d03a7c1cae484bb57b6f8e70ee1a631603aa8e1f6082fe0c","observation_id":"810b59e9-4810-4629-926c-e6c48cbf9c3f","resolution":{"observed_at":"2026-08-05T20:19:18.395112Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-05T20:19:18.220465Z","title":null,"venue":null,"work_id":"6a19fb61-aacf-43b8-b11c-8316c1d314cd","year":2015},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:07.538836Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:2d7a39704bbb14dbce5f2aeabf96107aeb97b39f557c77bb88684d09707f9f05","observation_id":"7a3673e1-867d-4759-8880-84eed0b5eba3","resolution":{"observed_at":"2026-08-05T20:19:18.260039Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-05T20:19:18.084069Z","title":null,"venue":null,"work_id":"aaee25d2-b382-4bbe-89ab-3be2cd1204ae","year":2019},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:07.654758Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:b324bdbf705c9593e0aaf39e3169bdbcc0841508096d4671f0d5715eead2f5e9","observation_id":"81c37fcc-216a-4360-8c64-e1c2fb6a31b4","resolution":{"observed_at":"2026-08-05T20:19:18.140723Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-05T20:19:17.947794Z","title":null,"venue":null,"work_id":"353f9979-49c0-42f3-bc04-17518f2b79b5","year":2022},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:07.762178Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:3ae462b7a8b84d16335742d3d1ae78b0ce16e96a1009863a1a29f8caf8873cce","observation_id":"93ca3489-c46f-4020-ac81-7260c302db7b","resolution":{"observed_at":"2026-08-05T20:19:18.008490Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2002.10619","last_updated":"2020-07-19T21:02:14Z","snapshot_observed_at":"2026-08-08T00:10:09.692416Z","submitted_at":"2020-02-25T01:36:43Z","title":"Three Approaches for Personalization with Applications to Federated Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2002.10619","snapshot_observed_at":"2026-08-05T20:19:07.921328Z","title":"Mansour, M","venue":null,"work_id":null,"year":2002},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":49,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:07.921328Z"},"links":{"cited_paper":"/paper/2002.10619","citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:d90aa372fdc6593dc022c6ecca6063233ee22bfc9cfb50de191d7b8da25e047f","observation_id":"8bbceb6b-6779-4284-9cf3-5b69e68ad720","resolution":{"observed_at":"2026-08-05T20:19:07.921328Z","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":"2026-08-05T20:19:17.813407Z","title":"Marfoq, G","venue":null,"work_id":"7773d6c6-ba7d-40e2-9c47-8934e5aa36c0","year":2022},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":50,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:07.988970Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:63bb551954ff77bfd14dca0c966996b54af86a7a3515083f4b28b122e87f3b11","observation_id":"aa69245a-6128-4d74-8db3-14136cf1b6d7","resolution":{"observed_at":"2026-08-05T20:19:17.878098Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-05T20:19:17.686042Z","title":"Maria Carlucci, L","venue":null,"work_id":"5b6ef1f3-2a6e-4f2f-aa0d-ecc40e1d8bba","year":2017},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":51,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:08.115323Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:2cf1233ea947b57f392bde5d468f791c953d86b9356c14aaa8c907aefa48baa1","observation_id":"2d2aedd0-b968-42a6-bf2b-90a8b0d58f43","resolution":{"observed_at":"2026-08-05T20:19:17.738167Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-05T20:19:17.571796Z","title":"Communication-efficient learning of deep networks from decentralized data","venue":null,"work_id":"223a01fe-8c86-42ea-b6b8-ac8f98477f77","year":2017},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":52,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:08.251500Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:fafeab92d42ae21d657a7f3ae71213a9029cfa949900e4d7a55b4e12ad79d350","observation_id":"4078fc8c-ba33-4d18-9163-f99f11154375","resolution":{"observed_at":"2026-08-05T20:19:17.619235Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-05T20:19:17.500627Z","title":"Mendieta, T","venue":null,"work_id":"4984b6d3-db7f-4ae5-bad0-d337d8eb5ead","year":2022},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":53,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:08.360260Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:0db7f688056814acd9d33ce51befe9180cd2412557aaf6c4c9f9d03ce9dfcd66","observation_id":"9346b14f-ec90-4d86-90c1-44ba6560fa70","resolution":{"observed_at":"2026-08-05T20:19:17.539006Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2206.15387","last_updated":"2023-03-24T19:09:30Z","snapshot_observed_at":"2026-07-06T13:26:29.394426Z","submitted_at":"2022-06-30T16:18:21Z","title":"Where to Begin? On the Impact of Pre-Training and Initialization in Federated Learning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2206.15387","snapshot_observed_at":"2026-08-05T20:19:08.451372Z","title":"Nguyen, J","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":54,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:08.451372Z"},"links":{"cited_paper":"/paper/2206.15387","citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:c225ab8c39540251d89b22cd47603d183244498ddeda5bc946cc94993ce66bcb","observation_id":"1c4e627f-0965-4375-8540-c3380a2d72d9","resolution":{"observed_at":"2026-08-05T20:19:08.451372Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1911.02054","last_updated":"2025-08-24T12:07:07Z","snapshot_observed_at":"2026-08-03T05:02:32.419407Z","submitted_at":"2019-11-05T19:45:49Z","title":"Federated Adversarial Domain Adaptation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1911.02054","snapshot_observed_at":"2026-08-05T20:19:08.558553Z","title":null,"venue":null,"work_id":null,"year":1911},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":55,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:08.558553Z"},"links":{"cited_paper":"/paper/1911.02054","citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:447f50c628aea9b747581a7a3eeaf057e4b8e4dc6b575dcfa2866aa920c02496","observation_id":"b14e98ee-8dc7-4136-a4ab-aae043677921","resolution":{"observed_at":"2026-08-05T20:19:08.558553Z","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":"2026-08-05T20:19:17.383552Z","title":null,"venue":null,"work_id":"d271e863-68e8-4738-ab36-c3a4d0797ffc","year":2022},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":56,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:08.741737Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:f94c26ee1017fe463d1fdc772b4e65c3af36ce5842b51a6d961c8dd2e1670cdb","observation_id":"5bcd8653-6b8c-4a77-8bac-84f962b8d67a","resolution":{"observed_at":"2026-08-05T20:19:17.442292Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-05T20:19:17.257167Z","title":"Ramachandran, N","venue":null,"work_id":"49f951b8-e1dd-47db-be1b-023acafe7318","year":2019},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":57,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:08.895272Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:1fdbcf0eecf3b02e8f599792e4cbb2027b5a668fd7ea78ac763013152159034e","observation_id":"c4d6cab6-cccb-40b2-8dc2-ef0abd4a11d3","resolution":{"observed_at":"2026-08-05T20:19:17.314925Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-05T20:19:17.099537Z","title":null,"venue":null,"work_id":"ed013157-9a9b-4a30-beee-1156670c64d3","year":2016},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":58,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:09.016597Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:69dd978618e2852de022427e331b15dff194ac3a41db7de2554caf460c5a8458","observation_id":"cfbc8949-be19-4226-8bf3-401daa32c2a8","resolution":{"observed_at":"2026-08-05T20:19:17.183531Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-05T20:19:16.960511Z","title":"Saenko, B","venue":null,"work_id":"ddf2d8b9-3b85-40f0-9216-ec8b668eee1f","year":2010},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":59,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:09.134066Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:e4688d1a55b8b0977fde0fdfc13aa8fbc1dcd1ba9a159e90a874bbc869e3e80e","observation_id":"79953342-54cb-492c-8bfe-3a36e6006b1e","resolution":{"observed_at":"2026-08-05T20:19:17.025127Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-05T20:19:16.828924Z","title":"Saito, K","venue":null,"work_id":"6fe86113-16b4-4c16-bffc-f0e350d1064b","year":2018},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":60,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:09.331577Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:54e3969cecf4ba0a30de52876f0ceee80f63fc6ee5f6390bccf1df902f666234","observation_id":"b26a2cdf-9ea9-4cfd-9021-266066b6b542","resolution":{"observed_at":"2026-08-05T20:19:16.895338Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-05T20:19:16.704634Z","title":"Sattler, S","venue":null,"work_id":"d75415bb-db93-4173-87f7-168bad621f4b","year":2019},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":61,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:09.546149Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:4f27df9622598eab595671f1fdacf348564bf41bff56eefb6229edb228c8d884","observation_id":"fb8920e6-9d59-4955-a240-7a8b49e1020b","resolution":{"observed_at":"2026-08-05T20:19:16.759932Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-05T20:19:16.610947Z","title":"Sattler, K.-R","venue":null,"work_id":"fcad1008-2b14-4ec8-a4a7-1ec2c5114db8","year":2020},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":62,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:09.736886Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:da5e318a007e3a16e6f4173d5bb46d3cbded7c24aeb1e19965227aad14cb11e9","observation_id":"498c9f7d-4d4c-41e2-8651-eb81c4b56ce3","resolution":{"observed_at":"2026-08-05T20:19:16.658249Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-05T20:19:16.487445Z","title":"Shakespeare","venue":null,"work_id":"e25be6ac-9d65-414c-aa0f-e291848a9b9f","year":1994},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":63,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:09.842509Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:b5af34dbe804478053fca8acc694df46939ad230ad009e222179189016a2c26d","observation_id":"c5c5294a-31b0-418d-84dd-a2163b321de7","resolution":{"observed_at":"2026-08-05T20:19:16.543972Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-05T20:19:16.383176Z","title":null,"venue":null,"work_id":"c0871a74-f3f4-47e0-be8d-286cab2f181c","year":2023},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":64,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:09.892769Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:3c989be971d9f14092fd2ba55d1ed6caf30e355dfcdbbdf5e3e82cf59273223b","observation_id":"0442c004-51b2-4e8f-b8f6-35d521a7a56e","resolution":{"observed_at":"2026-08-05T20:19:16.426976Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-05T20:19:16.274959Z","title":"T Dinh, N","venue":null,"work_id":"8949b079-22c0-4ecb-81f9-a11fc46a2eec","year":2020},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":65,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:09.969163Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:fce6d6468320886e3b3f85d4972c1acaf93c489ab3f8b817c7e1355c8a8cc213","observation_id":"e8a42539-6871-4b01-a7f0-657e28accc00","resolution":{"observed_at":"2026-08-05T20:19:16.330685Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-05T20:19:16.153908Z","title":"Towards personalized federated learning","venue":null,"work_id":"59f18d8e-b25e-401a-bad5-67ac45fc051d","year":2022},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":66,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:10.022402Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:6abdeadbd9b1b787fba1bafa047a35d3655819956d7751d32909e67251525dce","observation_id":"f12a27a1-b290-4da5-b74b-1cdebc0ea94c","resolution":{"observed_at":"2026-08-05T20:19:16.209086Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-05T20:19:16.023619Z","title":"Testolina, F","venue":null,"work_id":"3fcb7dd9-8588-45cd-9961-75afc05ea0d9","year":2023},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":67,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:10.093806Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:fff71e7f7a88da27fe5e35ee90429cea89537f8eb5c954472817d0e6f279582d","observation_id":"49ece07b-41bb-4608-a62a-d2228c5726db","resolution":{"observed_at":"2026-08-05T20:19:16.080831Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-05T20:19:15.914603Z","title":"Toldo, A","venue":null,"work_id":"342a3990-25c0-4b96-baad-6ae9f9fc4e4a","year":2020},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":68,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:10.174567Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:df24f5da79a2515566df51c66ec6b4bb19aabf33dc8318cd6d37b1f0b76e38cf","observation_id":"89e3edf2-48ab-406f-b8f3-0b504cdbad9a","resolution":{"observed_at":"2026-08-05T20:19:15.975533Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-05T20:19:15.784475Z","title":null,"venue":null,"work_id":"5f3df536-b429-4871-8c2a-c1e6b8e86dcf","year":2019},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":69,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:10.264759Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:e4c022c4eb14cc9311f44bc4a3e6e88fdf994a1b29ab50202fbf70adf5a71dc0","observation_id":"54f58797-3e74-4ddc-847a-bb8c3e6309e5","resolution":{"observed_at":"2026-08-05T20:19:15.838352Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-05T20:19:15.687110Z","title":"Tsai, W.-C","venue":null,"work_id":"c931d73f-a221-47fb-9137-4e63872326ee","year":2018},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":70,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:10.357111Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:3ef8e7ae51d3217fd9cf761f26fb55fae452a27d0311c6c0ff87bad9eec933d4","observation_id":"27b126f5-8a82-4190-a78c-b63648f4e29b","resolution":{"observed_at":"2026-08-05T20:19:15.734349Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-05T20:19:15.564387Z","title":"Varno, M","venue":null,"work_id":"5e739e61-1890-4b64-95fe-5406dd4a37f7","year":2022},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":71,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:10.441898Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:c80deddea1a3452837f811debe3cfd4c3f2c4f99c8c3ab9c501d6ec82e19871d","observation_id":"3c370f7b-8b44-4bb1-95ec-f2bb0a6f3860","resolution":{"observed_at":"2026-08-05T20:19:15.621904Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-05T20:19:15.436078Z","title":"Vaswani, N","venue":null,"work_id":"cb50eb9c-89be-46b9-bf4f-e8bea5b08337","year":2017},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":72,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:10.514939Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:98cde776427a3701db190545a7e165ec7af70efbc658e7a8f491aa34fb3b1b1e","observation_id":"d8c52205-5df6-424d-b239-a1c94c6ac8af","resolution":{"observed_at":"2026-08-05T20:19:15.492359Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10252","last_updated":"2019-10-22T22:16:15Z","snapshot_observed_at":"2026-08-09T23:56:41.965832Z","submitted_at":"2019-10-22T22:16:15Z","title":"Federated Evaluation of On-device Personalization","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.10252","snapshot_observed_at":"2026-08-05T20:19:10.607827Z","title":null,"venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":73,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:10.607827Z"},"links":{"cited_paper":"/paper/1910.10252","citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:4e20a79c78d99cbd817f711b8cc7184bbfd77ba893866c0d7f7e3321e2ee8038","observation_id":"ae97cc5f-8ce9-4b49-90b6-0ceb7ff1676c","resolution":{"observed_at":"2026-08-05T20:19:10.607827Z","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":"2026-08-05T20:19:15.295025Z","title":null,"venue":null,"work_id":"bb7659aa-903d-41c0-b4d7-32301696fcaf","year":2023},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":74,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:10.713683Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:a37d08337850a09a5c7c0729da0eea8ee6ab3896af6fe86411c33ac8b3a5fa8a","observation_id":"f3f2cb04-6977-4e33-bbfb-ef40622a7c14","resolution":{"observed_at":"2026-08-05T20:19:15.351470Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-05T20:19:15.114548Z","title":null,"venue":null,"work_id":"d7c540e1-cd59-4298-b585-041d4ebb69b6","year":2097},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":75,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:10.862608Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:46321107b17cd5744bfac697f6a83e6d276bff0c8ba017967fb4476f993f4436","observation_id":"5d14d8b5-83d6-40a6-95cd-e340c4ee12a8","resolution":{"observed_at":"2026-08-05T20:19:15.201703Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2106.10874","last_updated":"2021-06-21T06:16:19Z","snapshot_observed_at":"2026-08-12T22:47:04.833334Z","submitted_at":"2021-06-21T06:16:19Z","title":"FedCM: Federated Learning with Client-level Momentum","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2106.10874","snapshot_observed_at":"2026-08-05T20:19:10.998252Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":76,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:10.998252Z"},"links":{"cited_paper":"/paper/2106.10874","citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:65b369d96ad71070d1bb0d3b8d2271eb871fe3d3df037dc013ebcdf3daac9d8f","observation_id":"9512fa90-b500-4de3-a0b0-c3e629664bbe","resolution":{"observed_at":"2026-08-05T20:19:10.998252Z","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":"2026-08-05T20:19:14.945083Z","title":null,"venue":null,"work_id":"2d1a3a12-bbf8-4b89-91ef-1d17e15374a1","year":2022},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":77,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:11.156210Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:f411422000de17f90b8730cb6480d6eaabbf97b11dbc1419801f9b899ce326c1","observation_id":"59af3330-a7e9-4beb-aa46-e9591c844008","resolution":{"observed_at":"2026-08-05T20:19:15.026230Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-05T20:19:14.797021Z","title":"Yang and S","venue":null,"work_id":"1e5c8927-73bc-4a44-9ece-d1e03a7c1faf","year":2020},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":78,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:11.292057Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:851fe2e0e6c29389ecffb781debc59615c1dcb75da65c44f2a0d74887ca5b062","observation_id":"93f84074-5f70-48b5-88f2-df2272ce4df1","resolution":{"observed_at":"2026-08-05T20:19:14.876411Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-05T20:19:14.648012Z","title":null,"venue":null,"work_id":"b90d987a-7c3b-4cd3-8655-7fa13e8fc233","year":2022},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":79,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:11.379851Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:7dbe0e435e77d191aa17bbd531d95cbb7fcd76135a55380218149a8b4f46adad","observation_id":"895730d5-d4a0-42eb-b9f0-01c7f73279d5","resolution":{"observed_at":"2026-08-05T20:19:14.720241Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-05T20:19:14.526767Z","title":"Zhang, S","venue":null,"work_id":"2c035358-d847-4be8-b76f-4e3d42b47242","year":2021},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":80,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:11.472022Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:59b5e3c5cbc298252e0902bc373ac9aaeca765a6a093bccbf2c416f346e860a0","observation_id":"78fa0d82-a8e8-4c48-8dbf-95a25cd3461c","resolution":{"observed_at":"2026-08-05T20:19:14.584899Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-05T20:19:14.411188Z","title":"Zhang, Z","venue":null,"work_id":"1dab0e7d-05d7-42f3-a51c-7e1b4f4077a4","year":2021},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":81,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:11.611326Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:c241900aeb15f72a40274222a0ccb4093723c929a4b01145857269b1440e3b83","observation_id":"0bd9bf44-de6a-4dff-bb8a-72483f52a5de","resolution":{"observed_at":"2026-08-05T20:19:14.462303Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-05T20:19:14.283065Z","title":"Zhang, Y","venue":null,"work_id":"003905c9-75d0-4458-bf99-7380e4a81f51","year":2023},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":82,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:11.703851Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:27a47e1043c18f5cbe12c01b191015a63874075073126d41f0ff81d8a37f9f2f","observation_id":"556c8d2c-6bd9-4bb4-ab48-8a52b40ff7cd","resolution":{"observed_at":"2026-08-05T20:19:14.341021Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-05T20:19:14.161348Z","title":"Zhang, Y","venue":null,"work_id":"24aed28b-58fa-477d-add3-bab415e4e65c","year":2023},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":83,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:11.771844Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:a3fee7d82a8f832c87a509b92852e85bc6269d470b6d6f9a57fcc946230d94fb","observation_id":"e1f871e2-5653-4013-80ee-6fce62f324e6","resolution":{"observed_at":"2026-08-05T20:19:14.217982Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-05T20:19:14.013686Z","title":"Zhang, Y","venue":null,"work_id":"84175cba-22ff-4651-8b7e-ef40081ef062","year":2022},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":84,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:11.879565Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:3db05195cbee9e989cdf169a2595edea751d8ca8fef952a082da0d12e28d59b5","observation_id":"aff8d264-1b06-4464-adb6-8a7210470949","resolution":{"observed_at":"2026-08-05T20:19:14.081446Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-05T20:19:13.870699Z","title":"Zhang, X","venue":null,"work_id":"fb181f32-8a69-48e6-883b-c1be98c53cd4","year":2022},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":85,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:11.979196Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:e3d9ffc309fd20ea0a10727eb01b3b6ca1c94d837200dfce88b3fa08536943a5","observation_id":"dc2e5c48-9426-449a-a6d4-441282ac726f","resolution":{"observed_at":"2026-08-05T20:19:13.934363Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-05T20:19:13.744992Z","title":"Zhang, F","venue":null,"work_id":"5dd5ded5-f8de-46e8-89ae-6d0443eee3b5","year":2022},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":86,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:12.050188Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:08bead84ddeadd82156d539e386d1bfe91f0a3484e7031ff6a849edb71e2e317","observation_id":"15f68cb9-6d71-4817-89a1-671e030dbf80","resolution":{"observed_at":"2026-08-05T20:19:13.798154Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1806.00582","last_updated":"2022-07-21T12:33:15Z","snapshot_observed_at":"2026-07-06T06:42:35.645776Z","submitted_at":"2018-06-02T04:45:58Z","title":"Federated Learning with Non-IID Data","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1806.00582","snapshot_observed_at":"2026-08-05T20:19:12.161831Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":87,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:12.161831Z"},"links":{"cited_paper":"/paper/1806.00582","citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:72608191a9a5fa98eb89f103b216426ffb35160db384d880d19a99257b80cfe9","observation_id":"874cf6b6-17e3-4525-98a8-0f3c5ce9f3d2","resolution":{"observed_at":"2026-08-05T20:19:12.161831Z","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":"2026-08-05T20:19:13.506591Z","title":null,"venue":null,"work_id":"49f0cc45-db2e-4ce1-9840-3306e0e310cf","year":2021},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":88,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:12.307276Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:2ef9027d3d5d88ff31d18d55e89afb2337d2084267860ac0d79dcbc91ab3f98d","observation_id":"832fc946-e82e-4712-a755-db472559f33f","resolution":{"observed_at":"2026-08-05T20:19:13.648588Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-05T20:19:13.206921Z","title":"Zou, Z.-Y","venue":null,"work_id":"26064a70-726e-4cc7-a1ff-903b2919177c","year":2023},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":89,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:12.386021Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:6c145a3ef6db9196cc20ae3e833e3e1a36dd67ef7f480c326ea17c4333727503","observation_id":"3f9d61db-9db9-4740-a8c7-aa19d570a6c9","resolution":{"observed_at":"2026-08-05T20:19:13.333631Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-05T20:19:12.975570Z","title":null,"venue":null,"work_id":"bcd7559f-2093-41f7-98f1-0d5f67d7573a","year":2018},"citing_paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation","version":1},"reference_index":90,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:12.496555Z"},"links":{"citing_paper":"/paper/2508.10840"},"observation_digest":"sha256:c3f9c8164a41397bd50b0e7aa7abb9127013f3c5d65ea244a1821b58ec586af8","observation_id":"c5d4702e-2c30-4f0a-9466-a232fee98bef","resolution":{"observed_at":"2026-08-05T20:19:13.019019Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2508.10840","last_updated":"2025-08-14T17:06:50Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-12T04:30:12.862599Z","submitted_at":"2025-08-14T17:06:50Z","title":"Generalizable Federated Learning using Client Adaptive Focal Modulation"},"reference_resolution":{"displayed":90,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":57,"verified_exact":1,"verified_fuzzy":32},"total_outbound_references":90},"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":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"thesis":"As of 13 August 2026, this Paper Citation Record lists 90 of 90 outbound references and 0 inbound Pith citation observations for arXiv:2508.10840."}