{"as_of":"2026-08-08T19:46:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:056e9c57c387dcfb749c8160e6b064620710c7eb930a3b58fc9248faf372572a","coverage":[{"denominator":15,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":15,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T14:56:30.760294Z","state":"measured"},{"denominator":15,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":15,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+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/2505.17226/citation-record","integrity":"/paper/2505.17226/integrity","json":"/paper/2505.17226/citation-record.json","paper":"/paper/2505.17226"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:56:33.238556Z","title":"Advances in Neural Information Processing Systems30(2017)","venue":null,"work_id":"939ab316-d37b-4c86-b2bc-5bf9fe0ea145","year":2017},"citing_paper":{"arxiv_id":"2505.17226","last_updated":"2025-06-03T21:06:36Z","snapshot_observed_at":"2026-08-07T14:48:17.418607Z","submitted_at":"2025-05-22T19:01:09Z","title":"Secure and Private Federated Learning: Achieving Adversarial Resilience through Robust Aggregation","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T14:56:29.581353Z"},"links":{"citing_paper":"/paper/2505.17226"},"observation_digest":"sha256:a3e0e2a3501f0fbb59f6acdb67a6a4d2a66b77bc17cd315253ce7552e9cb2560","observation_id":"beaffadf-4c5d-4abb-9fbb-6585aac9151c","resolution":{"observed_at":"2026-08-07T14:56:33.345431Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:56:33.036262Z","title":"In: Proceedings of the Int’l ACM Symposium on Mobility Management and Wireless Access","venue":null,"work_id":"11183de0-1aa9-4d77-930d-37a3ea9188fe","year":2023},"citing_paper":{"arxiv_id":"2505.17226","last_updated":"2025-06-03T21:06:36Z","snapshot_observed_at":"2026-08-07T14:48:17.418607Z","submitted_at":"2025-05-22T19:01:09Z","title":"Secure and Private Federated Learning: Achieving Adversarial Resilience through Robust Aggregation","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T14:56:29.671462Z"},"links":{"citing_paper":"/paper/2505.17226"},"observation_digest":"sha256:9673a5c04ddd3d60514a7c9391d35ae7ec14414a361645791b60e7922e56fd14","observation_id":"38eb8edd-8612-44d0-b473-ec8cba7aa60e","resolution":{"observed_at":"2026-08-07T14:56:33.140469Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:56:32.786152Z","title":"In: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, volume 1 (long and short papers)","venue":null,"work_id":"cc9e74f3-cf91-424e-acb5-8c6faff3da14","year":2019},"citing_paper":{"arxiv_id":"2505.17226","last_updated":"2025-06-03T21:06:36Z","snapshot_observed_at":"2026-08-07T14:48:17.418607Z","submitted_at":"2025-05-22T19:01:09Z","title":"Secure and Private Federated Learning: Achieving Adversarial Resilience through Robust Aggregation","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T14:56:29.776887Z"},"links":{"citing_paper":"/paper/2505.17226"},"observation_digest":"sha256:ed4404927822c3e08a1c9df6f15b5b9e303109f6ff23dc198bc39389012a355f","observation_id":"420877b9-cede-4791-9856-84ecd4fe3a25","resolution":{"observed_at":"2026-08-07T14:56:32.880525Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:56:32.616055Z","title":"IEEE Transactions on Consumer Electronics (2025)","venue":null,"work_id":"a7301b65-f484-4645-bf30-63b2b19d4f22","year":2025},"citing_paper":{"arxiv_id":"2505.17226","last_updated":"2025-06-03T21:06:36Z","snapshot_observed_at":"2026-08-07T14:48:17.418607Z","submitted_at":"2025-05-22T19:01:09Z","title":"Secure and Private Federated Learning: Achieving Adversarial Resilience through Robust Aggregation","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T14:56:29.843622Z"},"links":{"citing_paper":"/paper/2505.17226"},"observation_digest":"sha256:e26d2ad67d5e8052878264a037bcd92e1af8fefdf61d10d3a519ff1664a071ee","observation_id":"e8d07270-a6b3-4673-bb57-40355f369b94","resolution":{"observed_at":"2026-08-07T14:56:32.641367Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.06917","last_updated":"2025-02-10T15:15:50Z","snapshot_observed_at":"2026-08-08T15:04:17.315052Z","submitted_at":"2025-02-10T15:15:50Z","title":"Krum Federated Chain (KFC): Using blockchain to defend against adversarial attacks in Federated Learning","version":1},"cited_work":{"arxiv_id":"2502.06917","doi":null,"metadata_source":"pith","pith_arxiv_id":"2502.06917","snapshot_observed_at":"2026-08-07T14:56:30.871762Z","title":"Krum Federated Chain (KFC): Using blockchain to defend against adversarial attacks in Federated Learning","venue":"cs.LG","work_id":"0356bf32-5f2e-4166-9e0c-cee630acae0a","year":2025},"citing_paper":{"arxiv_id":"2505.17226","last_updated":"2025-06-03T21:06:36Z","snapshot_observed_at":"2026-08-07T14:48:17.418607Z","submitted_at":"2025-05-22T19:01:09Z","title":"Secure and Private Federated Learning: Achieving Adversarial Resilience through Robust Aggregation","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T14:56:29.928203Z"},"links":{"cited_paper":"/paper/2502.06917","citing_paper":"/paper/2505.17226"},"observation_digest":"sha256:4e7a785c25c058cf76db4be01322c1beb262e7c5675c0b065709b66578b8fba0","observation_id":"3e424fb3-f2e5-4fa9-8634-a594d5434c84","resolution":{"observed_at":"2026-08-07T14:56:30.948417Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:56:32.390293Z","title":null,"venue":null,"work_id":"4642f414-5459-4e15-a852-4eec1e0861c6","year":2009},"citing_paper":{"arxiv_id":"2505.17226","last_updated":"2025-06-03T21:06:36Z","snapshot_observed_at":"2026-08-07T14:48:17.418607Z","submitted_at":"2025-05-22T19:01:09Z","title":"Secure and Private Federated Learning: Achieving Adversarial Resilience through Robust Aggregation","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T14:56:30.007359Z"},"links":{"citing_paper":"/paper/2505.17226"},"observation_digest":"sha256:76d639cef8f36c0cff54d8d5445c56c7f51de9637a71ccc96166b63af03522a1","observation_id":"dfad5096-4d82-4b4a-bf98-5b67184ada42","resolution":{"observed_at":"2026-08-07T14:56:32.499936Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:56:32.111018Z","title":"In: International Conference on Machine Learning","venue":null,"work_id":"23776148-f4bb-4767-a637-cbba5ee10c59","year":2021},"citing_paper":{"arxiv_id":"2505.17226","last_updated":"2025-06-03T21:06:36Z","snapshot_observed_at":"2026-08-07T14:48:17.418607Z","submitted_at":"2025-05-22T19:01:09Z","title":"Secure and Private Federated Learning: Achieving Adversarial Resilience through Robust Aggregation","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T14:56:30.116786Z"},"links":{"citing_paper":"/paper/2505.17226"},"observation_digest":"sha256:bb87e5a19999133a81a789827fead7ef8d2973580d5928fbda74369bc36c853c","observation_id":"1859c187-5438-431e-8c87-9ab207dc88be","resolution":{"observed_at":"2026-08-07T14:56:32.233942Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:56:30.226000Z","title":"Proceedings of the IEEE86(11), 2278–2324 (1998)","venue":null,"work_id":null,"year":1998},"citing_paper":{"arxiv_id":"2505.17226","last_updated":"2025-06-03T21:06:36Z","snapshot_observed_at":"2026-08-07T14:48:17.418607Z","submitted_at":"2025-05-22T19:01:09Z","title":"Secure and Private Federated Learning: Achieving Adversarial Resilience through Robust Aggregation","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T14:56:30.226000Z"},"links":{"citing_paper":"/paper/2505.17226"},"observation_digest":"sha256:2deca7048ecb02ba73d343674ec1233065450a40aeb056ba57baa199d368515e","observation_id":"a6160d3e-b459-4bc5-8738-860a24b25817","resolution":{"observed_at":"2026-08-07T14:56:30.226000Z","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":"2026-08-07T14:56:30.287959Z","title":"In: Artificial intelligence and statistics","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2505.17226","last_updated":"2025-06-03T21:06:36Z","snapshot_observed_at":"2026-08-07T14:48:17.418607Z","submitted_at":"2025-05-22T19:01:09Z","title":"Secure and Private Federated Learning: Achieving Adversarial Resilience through Robust Aggregation","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T14:56:30.287959Z"},"links":{"citing_paper":"/paper/2505.17226"},"observation_digest":"sha256:ced9c12de2bde3ca6ca5b4f354f1964bf7ff1ef2aa7ba4db3925f49482921190","observation_id":"6ed2bced-4ffa-4da9-a44a-06aab9aa2bfa","resolution":{"observed_at":"2026-08-07T14:56:30.287959Z","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":"2026-08-07T14:56:31.837214Z","title":"Electronics12(10), 2287 (2023)","venue":null,"work_id":"33e33aea-dd13-4623-9fca-efeee7bf63b3","year":2023},"citing_paper":{"arxiv_id":"2505.17226","last_updated":"2025-06-03T21:06:36Z","snapshot_observed_at":"2026-08-07T14:48:17.418607Z","submitted_at":"2025-05-22T19:01:09Z","title":"Secure and Private Federated Learning: Achieving Adversarial Resilience through Robust Aggregation","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T14:56:30.349444Z"},"links":{"citing_paper":"/paper/2505.17226"},"observation_digest":"sha256:a1dea44ef7fe1a3726cdd9146b803465c1ea277de941b6f5a74ff316e93ebea8","observation_id":"8727e48e-d335-4bb2-aef2-7e94a67ba570","resolution":{"observed_at":"2026-08-07T14:56:31.950686Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:56:31.653549Z","title":null,"venue":null,"work_id":"3e291c74-c61c-4061-adec-aa4747a3990d","year":2011},"citing_paper":{"arxiv_id":"2505.17226","last_updated":"2025-06-03T21:06:36Z","snapshot_observed_at":"2026-08-07T14:48:17.418607Z","submitted_at":"2025-05-22T19:01:09Z","title":"Secure and Private Federated Learning: Achieving Adversarial Resilience through Robust Aggregation","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T14:56:30.427393Z"},"links":{"citing_paper":"/paper/2505.17226"},"observation_digest":"sha256:bbaad61997514f7ebfbbd4a7447b1be856ea28c1ff505643e5620bb1309ce54b","observation_id":"fdb67679-fbfd-4c16-a4c8-61487f69d824","resolution":{"observed_at":"2026-08-07T14:56:31.757506Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:56:31.411598Z","title":null,"venue":null,"work_id":"e90169d8-074f-4737-8842-a0683c917ae1","year":2025},"citing_paper":{"arxiv_id":"2505.17226","last_updated":"2025-06-03T21:06:36Z","snapshot_observed_at":"2026-08-07T14:48:17.418607Z","submitted_at":"2025-05-22T19:01:09Z","title":"Secure and Private Federated Learning: Achieving Adversarial Resilience through Robust Aggregation","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T14:56:30.496968Z"},"links":{"citing_paper":"/paper/2505.17226"},"observation_digest":"sha256:60fad540e3f76191d3d0cd7a47eab3e1b5796b058071ab7b34b9a265f0568a71","observation_id":"a70b4b72-bd70-40ad-94cc-36c4b4e75c93","resolution":{"observed_at":"2026-08-07T14:56:31.520499Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:56:31.272647Z","title":"Digital Communications and Networks10(1), 126–134 (2024)","venue":null,"work_id":"b3c4127f-e8c8-42be-ad6c-e390f7e6983f","year":2024},"citing_paper":{"arxiv_id":"2505.17226","last_updated":"2025-06-03T21:06:36Z","snapshot_observed_at":"2026-08-07T14:48:17.418607Z","submitted_at":"2025-05-22T19:01:09Z","title":"Secure and Private Federated Learning: Achieving Adversarial Resilience through Robust Aggregation","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T14:56:30.578810Z"},"links":{"citing_paper":"/paper/2505.17226"},"observation_digest":"sha256:636ae8f9a6460da53d248540f9df0e839f64e3885fc15d1c510527d4f510eef9","observation_id":"1c36ce61-9999-4f13-87ff-4234feb24466","resolution":{"observed_at":"2026-08-07T14:56:31.325051Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:56:31.152652Z","title":"IEEE Transactions on Information Forensics and Security (2025)","venue":null,"work_id":"c23205c6-3529-41b1-b0d0-8a2835a47aa1","year":2025},"citing_paper":{"arxiv_id":"2505.17226","last_updated":"2025-06-03T21:06:36Z","snapshot_observed_at":"2026-08-07T14:48:17.418607Z","submitted_at":"2025-05-22T19:01:09Z","title":"Secure and Private Federated Learning: Achieving Adversarial Resilience through Robust Aggregation","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T14:56:30.692983Z"},"links":{"citing_paper":"/paper/2505.17226"},"observation_digest":"sha256:a009298de3a685c64616cb92f9d2e7881c88595b02441477271c0028957ecef1","observation_id":"cabf937f-d114-4ade-bb9f-f4d6905ed0e3","resolution":{"observed_at":"2026-08-07T14:56:31.205504Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:56:31.010547Z","title":"Authorea Preprints (2025)","venue":null,"work_id":"1b11869f-f84a-4c0b-84ab-d26587d6c9c2","year":2025},"citing_paper":{"arxiv_id":"2505.17226","last_updated":"2025-06-03T21:06:36Z","snapshot_observed_at":"2026-08-07T14:48:17.418607Z","submitted_at":"2025-05-22T19:01:09Z","title":"Secure and Private Federated Learning: Achieving Adversarial Resilience through Robust Aggregation","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T14:56:30.760294Z"},"links":{"citing_paper":"/paper/2505.17226"},"observation_digest":"sha256:f92acb87cc09b7c1d76bb75b3dc28acad4297c285b999c846ea3420d1926fdb4","observation_id":"1245aa86-72c8-4995-803f-a205d6e92a45","resolution":{"observed_at":"2026-08-07T14:56:31.063935Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2505.17226","last_updated":"2025-06-03T21:06:36Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-07T14:48:17.418607Z","submitted_at":"2025-05-22T19:01:09Z","title":"Secure and Private Federated Learning: Achieving Adversarial Resilience through Robust Aggregation"},"reference_resolution":{"displayed":15,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":5,"verified_exact":0,"verified_fuzzy":9},"total_outbound_references":15},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 0 inbound Pith citation observations for arXiv:2505.17226."}