{"as_of":"2026-08-21T12:04:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:8bce15a89f8f61f900459297a7ddc4ac1355c9fa01a13a6e70c437f72f08ae14","coverage":[{"denominator":68,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":68,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-05T05:35:21.607774Z","state":"measured"},{"denominator":68,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":68,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-21T06:32:19.484+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/2509.05192/citation-record","integrity":"/paper/2509.05192/integrity","json":"/paper/2509.05192/citation-record.json","paper":"/paper/2509.05192"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T05:35:29.234736Z","title":null,"venue":null,"work_id":"12fb9f14-2ca5-4f5a-9daa-04a62eb26cd0","year":2023},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:18.520817Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:5c12fd159c7b4364d39499c4f41de8054bf2104683c8f5bcd74156e8e1c677f0","observation_id":"0e6ebc36-ecb6-45f8-b6c5-e0ca14aa3e52","resolution":{"observed_at":"2026-08-05T05:35:29.308127Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T05:35:29.086447Z","title":null,"venue":null,"work_id":"ff69ad3a-90a7-423a-a303-7d41937ee8f3","year":2019},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:18.578615Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:5fe2cabe304a3d8189cbdc270cd6a690ddee08b660d3cb3017ffd9e1d9a0ca23","observation_id":"2bfa5b66-4307-4cce-913e-3cd9a2e22483","resolution":{"observed_at":"2026-08-05T05:35:29.154264Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"8644.36903","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T05:35:23.419882Z","title":null,"venue":null,"work_id":"587e14ba-093a-4bfe-b948-88b64285bfbd","year":2024},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:18.669589Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:b169814f5e95c4e7165a08836cc486fec6f2687a1545d3216576fbe80288304e","observation_id":"bd2fab1a-0541-4b3b-957a-3cffded0a778","resolution":{"observed_at":"2026-08-05T05:35:23.470254Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T05:35:28.880419Z","title":null,"venue":null,"work_id":"f8870eb7-eb17-4121-822f-478194c7bded","year":2021},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:18.747680Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:646ff76de82e1d9c99bd508afe775e07e533c8a02a9ae718bf61bb282310c99c","observation_id":"8ab9a720-f8a8-4835-9ef3-3604beb0ca6d","resolution":{"observed_at":"2026-08-05T05:35:29.032911Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T05:35:28.788880Z","title":null,"venue":null,"work_id":"23ca90bf-ce99-4b5b-a947-3d799a1ec7c1","year":2020},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:18.853564Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:b73636ba60801a1e5f239806b9e56fcd10deac19c32486f33e82fda7da6e0827","observation_id":"3ff88242-3fe4-44a7-95ea-6e3c67d03ba2","resolution":{"observed_at":"2026-08-05T05:35:28.831403Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T05:35:28.695881Z","title":null,"venue":null,"work_id":"f9e1d198-40c5-4745-a1e2-2e9dced8a509","year":2019},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:18.958164Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:3fa3266a4c621f3964765d6b30f7a091a2359f6f2d8c334ac67693266513431c","observation_id":"0ed6d62d-e1d1-4732-9368-6f3172cfd7dd","resolution":{"observed_at":"2026-08-05T05:35:28.737174Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2007.14390","last_updated":"2022-03-05T20:30:32Z","snapshot_observed_at":"2026-07-06T09:42:35.058716Z","submitted_at":"2020-07-28T17:59:07Z","title":"Flower: A Friendly Federated Learning Research Framework","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2007.14390","snapshot_observed_at":"2026-08-05T05:35:19.020792Z","title":"Beutel et al","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:19.020792Z"},"links":{"cited_paper":"/paper/2007.14390","citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:e4aa35d833428b9c1bc2dfc70b5729bfd08007b597e164f35a2df7f464dc66d6","observation_id":"596d2dcc-db54-4a59-9b67-a1d9e9c5dc20","resolution":{"observed_at":"2026-08-05T05:35:19.020792Z","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":"2026-08-05T05:35:28.606543Z","title":null,"venue":null,"work_id":"a5b24964-5a86-4ba9-8698-41ab3bc2597f","year":2019},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:19.093597Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:aeae5082b8a51c10949062300cdf4b7890411caaf1356cd5589154e3ebf8d2c8","observation_id":"aabc3f81-aebd-435d-8e5d-3f3178d0e958","resolution":{"observed_at":"2026-08-05T05:35:28.648452Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T05:35:28.527183Z","title":null,"venue":null,"work_id":"588be952-0885-479e-9f13-2fef8ba83559","year":2017},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:19.190966Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:a1ea96269bf232d1f026db7ba9a1187eeda8d8426587a0f3c8adf91cc5eb8c33","observation_id":"b1550994-ee94-49b3-9cf5-db79b4bf64b8","resolution":{"observed_at":"2026-08-05T05:35:28.565424Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T05:35:28.415351Z","title":null,"venue":null,"work_id":"5077f8af-cfb2-4b7f-b20b-7970af9322f6","year":null},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:19.259763Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:3bc1e81e8c352b2ce5cbd23ad9a3393e0d2b734dd8c65dfb22d972f50881c321","observation_id":"e4beb1d3-ee83-4a7e-bd88-af23753e6653","resolution":{"observed_at":"2026-08-05T05:35:28.456601Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T05:35:28.302864Z","title":"1998.Statistical Power Analysis for the Behavioral Sciences","venue":null,"work_id":"cd1e5c2d-8c01-4ad6-ace5-053b625563e4","year":1998},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:19.383583Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:f9fcccb24c71217b97e5da41043a3f42861ae0d79e94be7984ad9c83dc8165b3","observation_id":"3d689b4a-df65-40a7-b96c-df64dbb4787d","resolution":{"observed_at":"2026-08-05T05:35:28.344328Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T05:35:28.212541Z","title":"Zico Kolter, and Ameet Talwalkar","venue":null,"work_id":"73681990-1859-4613-9d61-e832cc798bbc","year":2021},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:19.456652Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:b99f8a28de80e3a899de127f0758787fd213dda70d6a1945db30f6b5350750e8","observation_id":"2e145d1e-0485-443c-aeef-7cd85d876520","resolution":{"observed_at":"2026-08-05T05:35:28.254848Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T05:35:28.104141Z","title":null,"venue":null,"work_id":"e66efd03-24fa-4431-b194-d254d8d34248","year":2020},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:19.516829Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:2262b86ea85dab4a885ea348d35a3bdc124005bc074585bdfea04139f1c72beb","observation_id":"72eee1cc-40cc-4346-b525-747148a518c4","resolution":{"observed_at":"2026-08-05T05:35:28.178658Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T05:35:27.969031Z","title":null,"venue":null,"work_id":"3635d005-1ce3-4724-832f-9f775925062b","year":2024},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:19.533695Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:c2cd475cef803f1f93361ec932badf0556cb1af38a28963f24ae10fd66e95136","observation_id":"a685344a-eb4c-43e4-af97-cc18d05f4ee4","resolution":{"observed_at":"2026-08-05T05:35:28.008386Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T05:35:27.797165Z","title":null,"venue":null,"work_id":"cbcc0806-ba9c-4937-8347-b1dd2cf78925","year":2023},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:19.592857Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:d657a74e03596678d68963a9ae1d5b0506b05ef21797a4abe8bf70ba2df169b0","observation_id":"76701513-9772-4282-a4fa-e564a80e9428","resolution":{"observed_at":"2026-08-05T05:35:27.892129Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.08892","last_updated":"2025-03-03T04:14:17Z","snapshot_observed_at":"2026-08-16T13:10:17.639540Z","submitted_at":"2024-10-11T15:10:38Z","title":"Federated Learning in Practice: Reflections and Projections","version":2},"cited_work":{"arxiv_id":"2410.08892","doi":null,"metadata_source":"pith","pith_arxiv_id":"2410.08892","snapshot_observed_at":"2026-08-05T05:35:23.199070Z","title":"Federated Learning in Practice: Reflections and Projections","venue":"cs.LG","work_id":"4362ac00-ecf6-4a29-8c1f-cca59c07fa14","year":2024},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:19.625360Z"},"links":{"cited_paper":"/paper/2410.08892","citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:bfd9b06e90fa1b237b8242841d68a5c190f2d0e20c79dbb9dc664dabec3203e3","observation_id":"c369e143-7a36-46ea-936c-42cdeb1e6023","resolution":{"observed_at":"2026-08-05T05:35:23.239353Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T05:35:27.658069Z","title":"Meyarivan","venue":null,"work_id":"eb2ac35b-84a9-4b6a-b025-f55cb4082ef5","year":null},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:19.690045Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:93f48a7889db388c9d1f9a3f495c4fe52d3c75da826a98a3abe6ec0989cd6d8d","observation_id":"46e5574a-49cb-47de-b6f1-599c30fd9647","resolution":{"observed_at":"2026-08-05T05:35:27.720565Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1609/aaai.v37i10.263","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T05:35:22.091618Z","title":null,"venue":null,"work_id":"c15f1afb-1be4-4d3f-91c1-13f5777fc194","year":2023},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:19.823658Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:2ec71530c1640473f7e91b34682195b37b4b10b75d2f3f62d212796e4db6c7eb","observation_id":"f7ab1ce9-e062-46d3-a4b1-e2ebc3f20022","resolution":{"observed_at":"2026-08-05T05:35:22.134835Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T05:35:27.526264Z","title":null,"venue":null,"work_id":"7ee09471-d9b8-4cad-8202-d50dd0895f82","year":2022},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:19.867986Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:2f9ad7a6854660281c6210111fec63c1a6243a6f3d2d9c89025fca871ca1ccee","observation_id":"09f989d9-7e6d-4289-a629-51c43236d1ce","resolution":{"observed_at":"2026-08-05T05:35:27.599649Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2024.23620","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T05:35:23.080879Z","title":null,"venue":null,"work_id":"51a11935-07dd-4786-ab00-dc191faa9924","year":2024},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:19.896846Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:577f15fed7b7b9c8950b00aa35ca9d1cc23d6355fc8168d5dfffc80cd1baaafc","observation_id":"a1a38198-9e02-403b-9b55-19ade8b62e34","resolution":{"observed_at":"2026-08-05T05:35:23.134542Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T05:35:27.316280Z","title":null,"venue":null,"work_id":"b44aa6f6-f914-4840-93a5-56a9c4e4779b","year":2020},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:19.960840Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:e5e958cd3a8e8932034f2126a8f043d3124f5f87ff4d2bf86a8badaa6e180745","observation_id":"77f3b756-3b90-465c-bb86-f0a2401d04f8","resolution":{"observed_at":"2026-08-05T05:35:27.425409Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T05:35:27.182110Z","title":"2016.Deep Learning","venue":null,"work_id":"06bc0ea5-b851-4505-88ea-a7893729761f","year":2016},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:20.001042Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:d1167e1e385487bc1c687c7733403b92740d290d8e585817f0631370a92c468e","observation_id":"2e5aff73-6636-40b6-8dab-56f4b2748871","resolution":{"observed_at":"2026-08-05T05:35:27.253876Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1708.06733","last_updated":"2019-03-11T20:45:33Z","snapshot_observed_at":"2026-08-12T15:43:59.037380Z","submitted_at":"2017-08-22T17:31:54Z","title":"BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1708.06733","snapshot_observed_at":"2026-08-05T05:35:20.068787Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:20.068787Z"},"links":{"cited_paper":"/paper/1708.06733","citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:e441b58b7150a59cbc97b3bae44dc69c6efe0c259b5118035280f271bf5a54c4","observation_id":"debf20c2-a4dd-4785-8577-a4606e0a5d53","resolution":{"observed_at":"2026-08-05T05:35:20.068787Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1811.03604","last_updated":"2019-02-28T21:07:51Z","snapshot_observed_at":"2026-08-15T21:55:07.573045Z","submitted_at":"2018-11-08T18:37:03Z","title":"Federated Learning for Mobile Keyboard Prediction","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1811.03604","snapshot_observed_at":"2026-08-05T05:35:20.097673Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:20.097673Z"},"links":{"cited_paper":"/paper/1811.03604","citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:ff4974d06231b800cf3034e0325fa2010d79678c312298b12edd60fb5a3b37e1","observation_id":"4b48eeb6-667a-4b62-acf3-f5fef2ad7e77","resolution":{"observed_at":"2026-08-05T05:35:20.097673Z","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":"2026-08-05T05:35:26.976299Z","title":null,"venue":null,"work_id":"20dea881-c9bb-4564-b01a-c5ecb4fca464","year":2019},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:20.117989Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:bb36214b8ff3dfae5ceef6dc581eb8f52a80ea643e022c12d4c8f53d20fa96c0","observation_id":"dfc860e2-4383-4b8f-9e76-1acbc2e56e7c","resolution":{"observed_at":"2026-08-05T05:35:27.043415Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T05:35:20.155287Z","title":null,"venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:20.155287Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:96b0015bfca1ede3073b9c61c443717c5f60582797cf1c6296823c1ad4599481","observation_id":"facc75ca-1c2b-4ab1-be22-d00aa2d2de9c","resolution":{"observed_at":"2026-08-05T05:35:20.155287Z","resolver_source":null,"status":"malformed_identifier"},"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":"2026-08-05T05:35:20.200597Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:20.200597Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:dc1a6237f4f24a7d2f42be78686718859e55b81627b4a69d7e044c08d14c79c5","observation_id":"9a3049a2-5c65-4c63-a41d-fc76b9f411e6","resolution":{"observed_at":"2026-08-05T05:35:20.200597Z","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":"2026-08-05T05:35:26.765349Z","title":"Krizhevsky","venue":null,"work_id":"c192b3cc-0164-450a-9feb-3f803b213883","year":2009},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:20.241340Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:7b185456c16466873a1718cbdbeeb8b26d6fd173e9232a668dadb7f533797c0b","observation_id":"5bc1518d-8d48-4a2c-9645-c962fa094d53","resolution":{"observed_at":"2026-08-05T05:35:26.841853Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T05:35:26.649885Z","title":null,"venue":null,"work_id":"7b636e87-bb66-4cb2-bf16-b51a250e5729","year":1991},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:20.282981Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:9cbaf583d5f6836937f6c2997541b547af129b3ed47704ed2dcfc088eff53a0c","observation_id":"133b0e41-8a53-457a-828c-95e948baf7ef","resolution":{"observed_at":"2026-08-05T05:35:26.701583Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T05:35:20.315900Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:20.315900Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:88c3eae739ef2da0316baec79b650fcd39620df7095584205e64a816df26af95","observation_id":"44df5dd0-a2e9-4945-8d2a-a08f7457d318","resolution":{"observed_at":"2026-08-05T05:35:20.315900Z","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":"2026-08-05T05:35:26.469969Z","title":null,"venue":null,"work_id":"96b2daf5-9cb4-4f03-983c-e99d0c6ca48c","year":2024},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:20.349180Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:9ac68f1a6053be218e4200643d463f700e8510dc9a11b6f5fbd2fdbe1738cf23","observation_id":"4b732f4f-0b9b-43f8-a80e-f7cadefa45a8","resolution":{"observed_at":"2026-08-05T05:35:26.545882Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T05:35:26.216464Z","title":null,"venue":null,"work_id":"36f6ddb2-d4dc-454e-b84e-baddc4c0b655","year":2020},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:20.386484Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:cfdb2207087c5296eccc7b638b55d6c8db150326dddba29d2ee7ca8a19dca307","observation_id":"dbf29fd6-cfdd-44e1-bfea-5535e05567d2","resolution":{"observed_at":"2026-08-05T05:35:26.334727Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T05:35:20.398001Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:20.398001Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:b77fa9b1ffcce3495b8523e7bb1fad06a2630425c480c61f9197a26a9152228b","observation_id":"f980eb0a-92ba-40e9-8d85-c89011a6aef5","resolution":{"observed_at":"2026-08-05T05:35:20.398001Z","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":"2026-08-05T05:35:26.074156Z","title":null,"venue":null,"work_id":"6534740e-389d-4842-aeeb-ab463c616b40","year":2018},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:20.439333Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:a27a7a0c506567401a4b03bb83a2445ff589460d85550a0d330fea4e31273264","observation_id":"f2fb661d-b31a-4136-931c-f44818474908","resolution":{"observed_at":"2026-08-05T05:35:26.135236Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T05:35:20.454946Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:20.454946Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:26bda702a7fa2409914a984f6881ffad267aba5b0818b327df707b9809ba6557","observation_id":"ad0194cd-fa79-4dd9-acf2-43ed426f3d43","resolution":{"observed_at":"2026-08-05T05:35:20.454946Z","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":"2026-08-05T05:35:25.951692Z","title":null,"venue":null,"work_id":"790dae36-5e1f-4f49-ad6d-91177d1b4d9f","year":2023},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:20.480179Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:6550b2eb20fe3d1ed363429223698e3d9b0f866edc2241d1504503f796440224","observation_id":"60b4ea53-b361-4060-9ee6-ca5fe3f0acbe","resolution":{"observed_at":"2026-08-05T05:35:26.023624Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T05:35:25.807794Z","title":null,"venue":null,"work_id":"20b9bb41-6560-42b2-8b2a-d0c95e16db89","year":2017},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:20.514515Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:3bdcf67f4e358e288fa5fe1491cbe9b54a9d3506c3ef0e307a155710dd6aa6ad","observation_id":"3e1d2fee-113e-4ba7-be89-560cd9a0ac04","resolution":{"observed_at":"2026-08-05T05:35:25.880896Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1602.05629","last_updated":"2023-01-26T22:54:08Z","snapshot_observed_at":"2026-08-17T13:07:20.583520Z","submitted_at":"2016-02-17T23:40:56Z","title":"Communication-Efficient Learning of Deep Networks from Decentralized Data","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1602.05629","snapshot_observed_at":"2026-08-05T05:35:20.547044Z","title":"Brendan McMahan, Eider Moore, Daniel Ramage, Seth Hampson, and Blaise Ag ¨uera y Arcas","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:20.547044Z"},"links":{"cited_paper":"/paper/1602.05629","citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:c978edcaf90c21bef5ca8155fb5593ab6d758d4b04865f09351b0cb9ae17eec8","observation_id":"d64601c9-1da8-4f06-b49c-135b96be4aa0","resolution":{"observed_at":"2026-08-05T05:35:20.547044Z","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":"2026-08-05T05:35:25.640701Z","title":null,"venue":null,"work_id":"975d4224-7ef0-4e50-ab1c-ed5e4af1ce25","year":2018},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:20.580044Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:5e406fd82648eee4c200fe07f02d5ad7db74e6c103014ba13d103190a111ccfe","observation_id":"c8087adc-6421-414c-a92b-0d5252fbb2db","resolution":{"observed_at":"2026-08-05T05:35:25.711363Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T05:35:25.493895Z","title":null,"venue":null,"work_id":"9d071b21-a3a7-4685-91ef-7992a7314b1e","year":2018},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:20.618163Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:729ce35c9c0f2d9922c65b9450671ee22cf93dd9f5ec4c557ef93d56f70deeb4","observation_id":"e1dec84e-6832-41ad-89b2-7a0b78c500a8","resolution":{"observed_at":"2026-08-05T05:35:25.564459Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T05:35:25.360256Z","title":"Doan, and Kok Seng Wong","venue":null,"work_id":"8b4a4425-28a9-4363-92c6-c36528869c99","year":2023},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:20.635120Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:55cdbbb9787fb478d624a2aa00a1f341c87b0ca3706ee2b37aacc18c8c887208","observation_id":"afeb42c0-f744-4d59-b7ae-3d6047b95db9","resolution":{"observed_at":"2026-08-05T05:35:25.420032Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1609/aaai.v35i10.17118","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":null,"venue":null,"work_id":"8ddd6e74-0539-4a79-957f-fecb93e9e860","year":2021},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:20.670561Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:1bc167fd7ecc873316b8ef4c898f7f23a2d43daf797ba66cb2be1f18207e18d4","observation_id":"a531f831-4fb5-473f-a0b3-bec37aa2d5e2","resolution":{"observed_at":"2026-08-05T05:35:22.017863Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2102.08503","last_updated":"2021-02-16T23:57:20Z","snapshot_observed_at":"2026-08-19T10:59:51.499595Z","submitted_at":"2021-02-16T23:57:20Z","title":"Federated Evaluation and Tuning for On-Device Personalization: System Design & Applications","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2102.08503","snapshot_observed_at":"2026-08-05T05:35:20.693462Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:20.693462Z"},"links":{"cited_paper":"/paper/2102.08503","citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:364b1fedcafaee29f48fc71c75203930fb58272bbd73e23c0b39536c4ac43aa3","observation_id":"86a2ec3f-af2d-43dc-b69b-b91c3dcb0751","resolution":{"observed_at":"2026-08-05T05:35:20.693462Z","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":"2026-08-05T05:35:25.211264Z","title":null,"venue":null,"work_id":"a6a31692-2db0-45a1-a568-f317cf8c388e","year":2024},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:20.734894Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:b35c3d21f671019f4941150606e55b11df5e87e8a2d60e59b90cb6ec8e0a20f2","observation_id":"1f8c6f61-36b0-4708-a9cd-d308e04f3f2d","resolution":{"observed_at":"2026-08-05T05:35:25.288142Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.24963/ijcai.2022/306","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":null,"venue":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","work_id":"6376cf71-70e6-4568-b6a2-4569bec68bc8","year":2022},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:20.767387Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:ddc610277928091f4412f7707925f904d9f44eabc07b6ced278522f5c95266e1","observation_id":"fdded8cd-ff5e-48c9-a49c-958d09aabdd8","resolution":{"observed_at":"2026-08-05T05:35:21.854063Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T05:35:20.807606Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:20.807606Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:b4dc0854e3ff4d2eb21a76f786197fed2c7fd8298487c4136c43b4784d423cf8","observation_id":"8b4ed682-647a-40ab-9da4-4dc9a20d7033","resolution":{"observed_at":"2026-08-05T05:35:20.807606Z","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":"2026-08-05T05:35:20.832657Z","title":"Howard, Menglong Zhu, Andrey Zhmogi- nov, and Liang-Chieh Chen","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:20.832657Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:b568409d7f3919cedc7d4cb0112087b8bed13fd4e1fea940665fd935f96461e9","observation_id":"7ae325a0-cf8d-4389-8c50-49beca5f98c4","resolution":{"observed_at":"2026-08-05T05:35:20.832657Z","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":"2026-08-05T05:35:20.870191Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:20.870191Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:f7f448dce801736b85b75384844d0300457b28ab5a0f1a4cb10b5d2e87ee3080","observation_id":"664c2f7e-e3d0-4c71-a473-a3754a501250","resolution":{"observed_at":"2026-08-05T05:35:20.870191Z","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":"2026-08-05T05:35:25.096745Z","title":null,"venue":null,"work_id":"511eed0b-66d0-408a-9cdf-2be0dc381345","year":2018},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:20.887294Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:99a309388a25bb6abcfa3a1dec41baeb9ec0daecd15294b03ef12f368e91cdfb","observation_id":"bfb75d95-0f63-4e2f-a9ee-4bb6504026fa","resolution":{"observed_at":"2026-08-05T05:35:25.164212Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T05:35:24.908729Z","title":null,"venue":null,"work_id":"d1ea1b7d-7270-4ccf-b38d-bc7099221353","year":2015},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:20.923192Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:9a624c711b3d1dd070e7db7b859dd58e834da801461c3af93e840273a4f75dd5","observation_id":"64583903-3e0c-4c0d-a3df-75e115dbbff7","resolution":{"observed_at":"2026-08-05T05:35:25.023847Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T05:35:24.821845Z","title":null,"venue":null,"work_id":"0f821fbb-528b-4b62-ab03-71bda87aa0a4","year":2015},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:20.957798Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:703710a3e2f597d2d50e65f6196b735eae0ff123937be6e3c230ebf36b88041e","observation_id":"037d0232-64b8-4b41-aa1c-439b50d4dc1f","resolution":{"observed_at":"2026-08-05T05:35:24.863480Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1109/cvp","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T05:35:22.642156Z","title":null,"venue":null,"work_id":"a4d7d0d1-572c-4f18-83e8-aacb1001ceef","year":2019},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:20.965190Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:4393aa0886eefe9009ff412d11b0c400d512443efc98846db26338ec8a14c93e","observation_id":"8789f034-9e59-4bb7-b739-e9c435c96012","resolution":{"observed_at":"2026-08-05T05:35:22.687719Z","resolver_source":"doi_truncated","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1911.07963","last_updated":"2019-12-02T19:00:11Z","snapshot_observed_at":"2026-08-17T17:57:37.740446Z","submitted_at":"2019-11-18T21:25:03Z","title":"Can You Really Backdoor Federated Learning?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1911.07963","snapshot_observed_at":"2026-08-05T05:35:21.009070Z","title":"Brendan McMahan","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:21.009070Z"},"links":{"cited_paper":"/paper/1911.07963","citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:cb2d2f2692e0f492d14c28bec84324588c807ab553624f301eee3c25b33afe10","observation_id":"62a6ea08-b47a-4333-9d61-a5e8148a09c7","resolution":{"observed_at":"2026-08-05T05:35:21.009070Z","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":"2026-08-05T05:35:24.677077Z","title":"Dahl, and Geoffrey E","venue":null,"work_id":"0cf60fc9-c3a6-4ecd-af35-326c09495982","year":2013},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:21.049861Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:85c75f9b63daa7e91efb45d7ef8123ad0b1a4e6ca7baf26220ddf8a1931a87d4","observation_id":"3d97e268-2dd9-4d08-966d-41098d68bdae","resolution":{"observed_at":"2026-08-05T05:35:24.748357Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1312.6199","last_updated":"2014-02-19T16:33:14Z","snapshot_observed_at":"2026-08-15T16:41:15.505782Z","submitted_at":"2013-12-21T03:36:08Z","title":"Intriguing properties of neural networks","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1312.6199","snapshot_observed_at":"2026-08-05T05:35:21.087737Z","title":null,"venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:21.087737Z"},"links":{"cited_paper":"/paper/1312.6199","citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:884a901a9e50fa959f76f98543316e0e7fa53232d0da236dbf385b0702b07f14","observation_id":"775869a9-c937-41a5-bcc0-198b7de5184c","resolution":{"observed_at":"2026-08-05T05:35:21.087737Z","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":"2026-08-05T05:35:21.123245Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:21.123245Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:1a57628044f956369e54802742bfc85eda67d3835d9ecc44867e7479e65b7c29","observation_id":"7cf76181-1822-43d0-9edb-47160393dbd0","resolution":{"observed_at":"2026-08-05T05:35:21.123245Z","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":"2026-08-05T05:35:24.447634Z","title":null,"venue":null,"work_id":"bc4e4658-c2f5-4ea0-a745-1088c7252244","year":2020},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:21.188916Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:e7aa8bb37922850425b483f440fcb595b43392c1613efd8234fc0f1a12128d73","observation_id":"9e886183-195f-4801-9da5-69a85133254f","resolution":{"observed_at":"2026-08-05T05:35:24.592230Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T05:35:24.163147Z","title":"Wikipedia","venue":null,"work_id":"c7102ba6-8cbe-4c87-9823-d2fdca752dcf","year":2025},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:21.213912Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:8a2abadc7ecf198ab77b747e0169c1b6a6ce8ed429028803251e21108ad91960","observation_id":"3af5365b-c010-448a-88d6-9d44b1d6b8bb","resolution":{"observed_at":"2026-08-05T05:35:24.290419Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T05:35:23.990881Z","title":null,"venue":null,"work_id":"601b797e-4259-4037-97d3-a1199c04e12f","year":2020},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:21.249869Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:2f984e6ac6e827e3f1619000177bf9c76bc7644db58d65cc360e7d33a4c29fc9","observation_id":"e01906db-57b8-4e70-b651-67ce03c7b647","resolution":{"observed_at":"2026-08-05T05:35:24.017879Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T05:35:23.879800Z","title":"Gonzalez, Kannan Ramchandran, and Michael W","venue":null,"work_id":"b2882343-c961-4779-8a87-8b7b609ecf58","year":2020},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:21.291737Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:2bfb040e063919f033b2161dcbf24980eaf92e8e7e304c58de3b25740d41499e","observation_id":"1eaa1c57-8f17-427f-bd1d-a791f6db6c94","resolution":{"observed_at":"2026-08-05T05:35:23.939613Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T05:35:23.769282Z","title":null,"venue":null,"work_id":"b9f022d4-654a-492f-a76f-d124a8fd22cf","year":null},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:21.323056Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:6a6ea3eb858d1565649a2353d2a4af30a6c93b05a1e689c1cf79ff1119709f0e","observation_id":"a77a1972-11b9-4920-971e-6fef196268dd","resolution":{"observed_at":"2026-08-05T05:35:23.828973Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.18653/v1/2022.emnlp-main.6","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":null,"venue":null,"work_id":"cbd7c6bf-8c7e-4254-9acd-1feb0c297c90","year":2022},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:21.419611Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:aa5a0517043fa89f8e866e5b93c9d1e10918a6b121649acabba70dbce2859418","observation_id":"0c71d987-5176-4ff8-ac19-392a5fba2e61","resolution":{"observed_at":"2026-08-05T05:35:21.744534Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T05:35:23.734956Z","title":null,"venue":null,"work_id":"a8db70b3-f3b3-45cc-abcc-a501b68f6fc2","year":null},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:21.473527Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:fca63d483214ffeb22bea9b6fbbb119db9d91007ba97ebc31a0025233a2bf009","observation_id":"8d09b1b4-ec3a-43ee-91c9-f7b00648ead2","resolution":{"observed_at":"2026-08-05T05:35:23.746371Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T05:35:21.578877Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:21.578877Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:6d78744661b6efd7ad3b075649b2b97e42372c22b05751c5e71722611ce705e7","observation_id":"abee1d01-b497-481e-8e43-c3b4a544c337","resolution":{"observed_at":"2026-08-05T05:35:21.578877Z","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":"2026-08-05T05:35:23.519698Z","title":"Stochastic","venue":null,"work_id":"f4249dbc-33c8-49bb-ad9f-26a210123495","year":2022},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:21.607774Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:34b5bca3df04d1271d609497cbee94d0cee41192f33f809ffcb3828cda4cc252","observation_id":"abb82a85-e244-4a94-9d0d-d07243669b40","resolution":{"observed_at":"2026-08-05T05:35:23.575997Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T05:35:23.623719Z","title":"InNeurIPS","venue":null,"work_id":"1740e03f-3672-4dd2-ba20-fe414ac3b6d1","year":null},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:21.530427Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:fb630062c2e67284cb2f2b07eb08bc4a4fa0c368a9ae35df3749f6d7e958676b","observation_id":"231ac1e3-146a-4ea7-a803-e3670d30e204","resolution":{"observed_at":"2026-08-05T05:35:23.671779Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1109/4235.9","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T05:35:22.193576Z","title":"IEEE Transactions on Evolutionary Computation","venue":null,"work_id":"a8d23f9d-362f-4449-8232-ddde56b160d1","year":null},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":2002,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:19.761287Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:7a65145c7f41a8ec036f66a8118c28f6cd8b38af04e19491196fa5ba32b3474e","observation_id":"9dc72027-d2e8-493e-b190-30a009ff05bb","resolution":{"observed_at":"2026-08-05T05:35:22.250926Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T05:35:21.366934Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning","version":2},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-05T05:35:21.366934Z"},"links":{"citing_paper":"/paper/2509.05192"},"observation_digest":"sha256:fab58cb2c49a57c5288492c6e2a5c015690a7ba06c0feffb4b6a16ecca497f79","observation_id":"b898bce7-3be9-4abe-af44-a2943ffd19ad","resolution":{"observed_at":"2026-08-05T05:35:21.366934Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2509.05192","last_updated":"2025-09-08T13:52:25Z","latest_version":2,"primary_category":"cs.CR","snapshot_observed_at":"2026-08-13T10:15:46.852308Z","submitted_at":"2025-09-05T15:46:03Z","title":"On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning"},"reference_resolution":{"displayed":68,"state_counts":{"malformed_identifier":4,"metadata_mismatch":2,"parse_uncertain":0,"unresolved":46,"verified_exact":6,"verified_fuzzy":10},"total_outbound_references":68},"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":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"thesis":"As of 21 August 2026, this Paper Citation Record lists 68 of 68 outbound references and 0 inbound Pith citation observations for arXiv:2509.05192."}