{"as_of":"2026-08-10T23:27:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:d836ccd103ee8165bc670a1ad89cc764b0181a58728318464cbfbd34647b002e","coverage":[{"denominator":39,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":39,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T15:06:54.393518Z","state":"measured"},{"denominator":39,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":39,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2505.16403/citation-record","integrity":"/paper/2505.16403/integrity","json":"/paper/2505.16403/citation-record.json","paper":"/paper/2505.16403"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:06:56.322714Z","title":"Robust control of continuum robots using Cosserat rod theory.Mechanism and Machine Theory, 131:48–61, January","venue":null,"work_id":"2baea910-54d8-43ca-891a-79c24a972f8f","year":2019},"citing_paper":{"arxiv_id":"2505.16403","last_updated":"2025-05-29T00:20:42Z","snapshot_observed_at":"2026-08-07T14:59:28.408515Z","submitted_at":"2025-05-22T08:54:17Z","title":"Performance Guaranteed Poisoning Attacks in Federated Learning: A Sliding Mode Approach","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T15:06:50.572467Z"},"links":{"citing_paper":"/paper/2505.16403"},"observation_digest":"sha256:a2ce942e686025ba0901cd040604c744379eb8ad8fbf241a35abd58387618582","observation_id":"9fb94f65-1ee3-44f5-addd-efe31d061566","resolution":{"observed_at":"2026-08-07T15:06:56.326375Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:06:56.294660Z","title":"Ana- lyzing Federated Learning through an Adversarial Lens, November","venue":null,"work_id":"7895f948-3bfb-4532-af17-1409b8fc3cf6","year":2019},"citing_paper":{"arxiv_id":"2505.16403","last_updated":"2025-05-29T00:20:42Z","snapshot_observed_at":"2026-08-07T14:59:28.408515Z","submitted_at":"2025-05-22T08:54:17Z","title":"Performance Guaranteed Poisoning Attacks in Federated Learning: A Sliding Mode Approach","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T15:06:51.010373Z"},"links":{"citing_paper":"/paper/2505.16403"},"observation_digest":"sha256:be9de990789b84802e2c5f297f2b6abd1ba9874d00aa73b8331f2c970c2000ca","observation_id":"9cc989cf-9e61-45ce-b4f2-9d9cf27927e9","resolution":{"observed_at":"2026-08-07T15:06:56.298175Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1811.12470","last_updated":"2019-11-25T00:34:14Z","snapshot_observed_at":"2026-07-06T07:18:03.628376Z","submitted_at":"2018-11-29T20:27:14Z","title":"Analyzing Federated Learning through an Adversarial Lens","version":4},"cited_work":{"arxiv_id":"1811.12470","doi":null,"metadata_source":"pith","pith_arxiv_id":"1811.12470","snapshot_observed_at":"2026-08-07T15:06:54.509248Z","title":"Analyzing Federated Learning through an Adversarial Lens","venue":"cs.LG","work_id":"c413512a-6747-489b-9b49-ee6b894e97b7","year":2018},"citing_paper":{"arxiv_id":"2505.16403","last_updated":"2025-05-29T00:20:42Z","snapshot_observed_at":"2026-08-07T14:59:28.408515Z","submitted_at":"2025-05-22T08:54:17Z","title":"Performance Guaranteed Poisoning Attacks in Federated Learning: A Sliding Mode Approach","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T15:06:51.227880Z"},"links":{"cited_paper":"/paper/1811.12470","citing_paper":"/paper/2505.16403"},"observation_digest":"sha256:1728892130b0b0c7c5dc00c2845a4d73efd90277c4f6f67dbc7860ac2fb89850","observation_id":"b881ebaf-c650-4fbc-aebf-7f0446b2edc8","resolution":{"observed_at":"2026-08-07T15:06:54.581917Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:06:56.253301Z","title":"Park, and Li Ma","venue":null,"work_id":"3d4000df-a2bc-4da0-a6a3-9446da678417","year":2021},"citing_paper":{"arxiv_id":"2505.16403","last_updated":"2025-05-29T00:20:42Z","snapshot_observed_at":"2026-08-07T14:59:28.408515Z","submitted_at":"2025-05-22T08:54:17Z","title":"Performance Guaranteed Poisoning Attacks in Federated Learning: A Sliding Mode Approach","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T15:06:51.937725Z"},"links":{"citing_paper":"/paper/2505.16403"},"observation_digest":"sha256:b59166eb64cec7f7488fa34df1e5eb432124cb3deb3ac66544e740d42741f26e","observation_id":"a48a91fa-7a35-44e7-812d-f5cdb10242ff","resolution":{"observed_at":"2026-08-07T15:06:56.256385Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:06:54.676857Z","title":"In terms of running time, FedSA takes more time due to its more complex optimization process","venue":null,"work_id":"f9d36625-31f0-4948-8116-92ed76a0a2f3","year":2023},"citing_paper":{"arxiv_id":"2505.16403","last_updated":"2025-05-29T00:20:42Z","snapshot_observed_at":"2026-08-07T14:59:28.408515Z","submitted_at":"2025-05-22T08:54:17Z","title":"Performance Guaranteed Poisoning Attacks in Federated Learning: A Sliding Mode Approach","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T15:06:54.393518Z"},"links":{"citing_paper":"/paper/2505.16403"},"observation_digest":"sha256:ca1e3bcdde50404dcd6d173c4f1762f97506fbe068c7ef156250f7f035ec12e2","observation_id":"4a066a0a-c17f-4d13-af88-443e9d5a2775","resolution":{"observed_at":"2026-08-07T15:06:54.740210Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2012.13995","last_updated":"2022-04-12T01:56:47Z","snapshot_observed_at":"2026-07-06T10:28:06.533127Z","submitted_at":"2020-12-27T18:43:39Z","title":"FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2012.13995","snapshot_observed_at":"2026-08-07T15:06:52.401001Z","title":"[Khoo et al., 2009] Suiyang Khoo, Lihua Xie, and Zhihong Man","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2505.16403","last_updated":"2025-05-29T00:20:42Z","snapshot_observed_at":"2026-08-07T14:59:28.408515Z","submitted_at":"2025-05-22T08:54:17Z","title":"Performance Guaranteed Poisoning Attacks in Federated Learning: A Sliding Mode Approach","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T15:06:52.401001Z"},"links":{"cited_paper":"/paper/2012.13995","citing_paper":"/paper/2505.16403"},"observation_digest":"sha256:7240ded87baf4185b04eece8b8e63cc19ca645de492359ab509ed7202c388d02","observation_id":"e5309fc7-2dc3-4981-9b50-2d2ae188394a","resolution":{"observed_at":"2026-08-07T15:06:52.401001Z","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":"2026-08-07T15:06:56.187387Z","title":"Finite-time stabilization of stochas- tic nonlinear systems in strict-feedback form","venue":null,"work_id":"fef7cae4-30bb-489c-833f-b56eead1de1c","year":2013},"citing_paper":{"arxiv_id":"2505.16403","last_updated":"2025-05-29T00:20:42Z","snapshot_observed_at":"2026-08-07T14:59:28.408515Z","submitted_at":"2025-05-22T08:54:17Z","title":"Performance Guaranteed Poisoning Attacks in Federated Learning: A Sliding Mode Approach","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T15:06:52.490508Z"},"links":{"citing_paper":"/paper/2505.16403"},"observation_digest":"sha256:397279f70c5e058af13928283929db7dd9b9da9cf55ceb53797213df7749450c","observation_id":"3f2cee06-d66a-48b7-85b8-1a3f9347fa69","resolution":{"observed_at":"2026-08-07T15:06:56.190679Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:06:52.677447Z","title":"Tiny imagenet visual recognition challenge","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2505.16403","last_updated":"2025-05-29T00:20:42Z","snapshot_observed_at":"2026-08-07T14:59:28.408515Z","submitted_at":"2025-05-22T08:54:17Z","title":"Performance Guaranteed Poisoning Attacks in Federated Learning: A Sliding Mode Approach","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T15:06:52.677447Z"},"links":{"citing_paper":"/paper/2505.16403"},"observation_digest":"sha256:dd59d37e946235162fc3a3398c3c6c6a9b9a30dfa8d658660b4306885fc4420c","observation_id":"dd7a5d37-9fd5-4835-93d6-aa76fd195833","resolution":{"observed_at":"2026-08-07T15:06:52.677447Z","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":"2026-08-07T15:06:56.148864Z","title":"[Mahloujifar et al., 2019] Saeed Mahloujifar, Mohammad Mahmoody, and Ameer Mohammed","venue":null,"work_id":"5d80a6f4-430a-426c-9969-c3f212bc765a","year":2019},"citing_paper":{"arxiv_id":"2505.16403","last_updated":"2025-05-29T00:20:42Z","snapshot_observed_at":"2026-08-07T14:59:28.408515Z","submitted_at":"2025-05-22T08:54:17Z","title":"Performance Guaranteed Poisoning Attacks in Federated Learning: A Sliding Mode Approach","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T15:06:52.807651Z"},"links":{"citing_paper":"/paper/2505.16403"},"observation_digest":"sha256:97a8c416d46f1545ab3f0565d97ad73e6ba49bf4342ec89ca4f8479214bc71dc","observation_id":"6c7a7915-7502-469e-9ec8-0efb7e076542","resolution":{"observed_at":"2026-08-07T15:06:56.152074Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:06:56.138723Z","title":"Communication-Efficient Learning of Deep Networks from Decentralized Data","venue":null,"work_id":"3c0073bd-d90f-4879-9902-18918ef5650e","year":2017},"citing_paper":{"arxiv_id":"2505.16403","last_updated":"2025-05-29T00:20:42Z","snapshot_observed_at":"2026-08-07T14:59:28.408515Z","submitted_at":"2025-05-22T08:54:17Z","title":"Performance Guaranteed Poisoning Attacks in Federated Learning: A Sliding Mode Approach","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T15:06:52.868329Z"},"links":{"citing_paper":"/paper/2505.16403"},"observation_digest":"sha256:45db9a7f5fb623dcdb951c4242b8ae65dfd5ae235e96149ebcf454547d215252","observation_id":"c9196a0c-a473-48c2-9d38-ee733d5e60c0","resolution":{"observed_at":"2026-08-07T15:06:56.142177Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:06:56.129374Z","title":"The Hidden Vulnerabil- ity of Distributed Learning in Byzantium, July","venue":null,"work_id":"129c8016-0d75-43ad-8ef2-3621267f0e57","year":2018},"citing_paper":{"arxiv_id":"2505.16403","last_updated":"2025-05-29T00:20:42Z","snapshot_observed_at":"2026-08-07T14:59:28.408515Z","submitted_at":"2025-05-22T08:54:17Z","title":"Performance Guaranteed Poisoning Attacks in Federated Learning: A Sliding Mode Approach","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T15:06:52.949657Z"},"links":{"citing_paper":"/paper/2505.16403"},"observation_digest":"sha256:bcbada4204b3e6a257f7627f80e4c15ddb7251144a72c75a8dd5f2fca02d7b29","observation_id":"f46a4b5b-0650-45ea-8f76-4ff0f2d8d8fd","resolution":{"observed_at":"2026-08-07T15:06:56.132616Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1802.07927","last_updated":"2018-07-17T18:10:23Z","snapshot_observed_at":"2026-07-06T06:24:44.455684Z","submitted_at":"2018-02-22T07:42:00Z","title":"The Hidden Vulnerability of Distributed Learning in Byzantium","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1802.07927","snapshot_observed_at":"2026-08-07T15:06:53.020848Z","title":"[Mu˜noz-Gonz´alez et al., 2017] Luis Mu ˜noz-Gonz´alez, Bat- tista Biggio, Ambra Demontis, Andrea Paudice, Vasin Wongrassamee, Emil C","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2505.16403","last_updated":"2025-05-29T00:20:42Z","snapshot_observed_at":"2026-08-07T14:59:28.408515Z","submitted_at":"2025-05-22T08:54:17Z","title":"Performance Guaranteed Poisoning Attacks in Federated Learning: A Sliding Mode Approach","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T15:06:53.020848Z"},"links":{"cited_paper":"/paper/1802.07927","citing_paper":"/paper/2505.16403"},"observation_digest":"sha256:05bdef9e59295797e357a198972a83cf2e6a6d25c4c0590736911a9189d4082a","observation_id":"f1792798-0dce-4c09-8bd1-ea2d47ec1fbd","resolution":{"observed_at":"2026-08-07T15:06:53.020848Z","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":"2026-08-07T15:06:56.119486Z","title":"Manipulating the Byzantine: Optimiz- ing Model Poisoning Attacks and Defenses for Federated Learning","venue":null,"work_id":"d068cf72-9c15-446d-b800-692b40d56870","year":2021},"citing_paper":{"arxiv_id":"2505.16403","last_updated":"2025-05-29T00:20:42Z","snapshot_observed_at":"2026-08-07T14:59:28.408515Z","submitted_at":"2025-05-22T08:54:17Z","title":"Performance Guaranteed Poisoning Attacks in Federated Learning: A Sliding Mode Approach","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T15:06:53.124700Z"},"links":{"citing_paper":"/paper/2505.16403"},"observation_digest":"sha256:576245690aee7ad41eae4a66353120d69289cb73098904bacc6310cb369b6015","observation_id":"b635ff2c-2eff-4d78-9cfe-87f90684c421","resolution":{"observed_at":"2026-08-07T15:06:56.123173Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:06:56.108811Z","title":"Better Together: Attaining the Triad of Byzantine-robust Federated Learning via Lo- cal Update Amplification","venue":null,"work_id":"185ee6cd-c596-4bd0-851b-9e6b0ef86fde","year":2022},"citing_paper":{"arxiv_id":"2505.16403","last_updated":"2025-05-29T00:20:42Z","snapshot_observed_at":"2026-08-07T14:59:28.408515Z","submitted_at":"2025-05-22T08:54:17Z","title":"Performance Guaranteed Poisoning Attacks in Federated Learning: A Sliding Mode Approach","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T15:06:53.196989Z"},"links":{"citing_paper":"/paper/2505.16403"},"observation_digest":"sha256:7c332a374ffa2a04e0d6bc08fec3ce170e52e266e01d3d1e2afaf002a382f206","observation_id":"2ed58c37-32f0-49dd-b349-bc1d36dddae6","resolution":{"observed_at":"2026-08-07T15:06:56.112450Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:06:56.099298Z","title":"[Sun et al., 2019] Ziteng Sun, Peter Kairouz, Ananda Theertha Suresh, and H","venue":null,"work_id":"68d31931-ce75-4029-b406-f0379f59551d","year":2019},"citing_paper":{"arxiv_id":"2505.16403","last_updated":"2025-05-29T00:20:42Z","snapshot_observed_at":"2026-08-07T14:59:28.408515Z","submitted_at":"2025-05-22T08:54:17Z","title":"Performance Guaranteed Poisoning Attacks in Federated Learning: A Sliding Mode Approach","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T15:06:53.273927Z"},"links":{"citing_paper":"/paper/2505.16403"},"observation_digest":"sha256:41bb72bfeaa7bb7f0761f2363f27fe919ca81f78995bf0bb343ea9dc0fca0d4d","observation_id":"1ee1be44-1aa9-48b7-9977-75d4200708c2","resolution":{"observed_at":"2026-08-07T15:06:56.102437Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1911.07963","last_updated":"2019-12-02T19:00:11Z","snapshot_observed_at":"2026-08-09T08:16:29.597021Z","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":"2026-08-07T15:06:53.359807Z","title":"[Xie et al., 2020] Cong Xie, Oluwasanmi Koyejo, and In- dranil Gupta","venue":null,"work_id":null,"year":1911},"citing_paper":{"arxiv_id":"2505.16403","last_updated":"2025-05-29T00:20:42Z","snapshot_observed_at":"2026-08-07T14:59:28.408515Z","submitted_at":"2025-05-22T08:54:17Z","title":"Performance Guaranteed Poisoning Attacks in Federated Learning: A Sliding Mode Approach","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T15:06:53.359807Z"},"links":{"cited_paper":"/paper/1911.07963","citing_paper":"/paper/2505.16403"},"observation_digest":"sha256:59b2e1547914ff3e3510191560fcb82b8ab36a870c7d4d5bbfe1ef82f8ef44f9","observation_id":"094cabbc-7bd1-42a6-94dd-a71d0508035f","resolution":{"observed_at":"2026-08-07T15:06:53.359807Z","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":"2026-08-07T15:06:56.090178Z","title":"Learning feature pyramids for human pose estimation","venue":null,"work_id":"20511cc0-4b5a-4937-97cb-5608f9995546","year":2017},"citing_paper":{"arxiv_id":"2505.16403","last_updated":"2025-05-29T00:20:42Z","snapshot_observed_at":"2026-08-07T14:59:28.408515Z","submitted_at":"2025-05-22T08:54:17Z","title":"Performance Guaranteed Poisoning Attacks in Federated Learning: A Sliding Mode Approach","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T15:06:53.455967Z"},"links":{"citing_paper":"/paper/2505.16403"},"observation_digest":"sha256:d49bca3686395096ce2da0eed5036ed745245e82d8aad9e8afba0bd96190be2c","observation_id":"e2da1e1e-bf6e-4b80-a91c-587bd6ec4fac","resolution":{"observed_at":"2026-08-07T15:06:56.093276Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:06:56.080579Z","title":"Finite-time stability and instability of stochastic nonlinear systems","venue":null,"work_id":"a8be5f77-1fa6-41c7-8948-d4b71efb30b4","year":2011},"citing_paper":{"arxiv_id":"2505.16403","last_updated":"2025-05-29T00:20:42Z","snapshot_observed_at":"2026-08-07T14:59:28.408515Z","submitted_at":"2025-05-22T08:54:17Z","title":"Performance Guaranteed Poisoning Attacks in Federated Learning: A Sliding Mode Approach","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T15:06:53.544960Z"},"links":{"citing_paper":"/paper/2505.16403"},"observation_digest":"sha256:de081e41c1f39ff5441e82a0c708904c1c4649652602a7906161e29576a6bd38","observation_id":"e1ceed7a-4691-42b8-b2c4-4d16ef4ec4e2","resolution":{"observed_at":"2026-08-07T15:06:56.083910Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1803.01498","last_updated":"2021-02-25T06:34:39Z","snapshot_observed_at":"2026-07-06T06:26:35.067161Z","submitted_at":"2018-03-05T05:04:17Z","title":"Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1803.01498","snapshot_observed_at":"2026-08-07T15:06:53.735458Z","title":"[Young et al., 1999] K.D","venue":null,"work_id":null,"year":1999},"citing_paper":{"arxiv_id":"2505.16403","last_updated":"2025-05-29T00:20:42Z","snapshot_observed_at":"2026-08-07T14:59:28.408515Z","submitted_at":"2025-05-22T08:54:17Z","title":"Performance Guaranteed Poisoning Attacks in Federated Learning: A Sliding Mode Approach","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T15:06:53.735458Z"},"links":{"cited_paper":"/paper/1803.01498","citing_paper":"/paper/2505.16403"},"observation_digest":"sha256:684e72217810d324875d6d9bb82770542f5919968c60650688ade1ea43295050","observation_id":"bfbaa9ad-353c-4011-b02a-0f39d73914a2","resolution":{"observed_at":"2026-08-07T15:06:53.735458Z","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":"2026-08-07T15:06:56.000384Z","title":"En- abling privacy-preserving sharing of genomic data for gwass in decentralized networks","venue":null,"work_id":"30aa48bd-5253-4529-88ab-fe7907301270","year":2019},"citing_paper":{"arxiv_id":"2505.16403","last_updated":"2025-05-29T00:20:42Z","snapshot_observed_at":"2026-08-07T14:59:28.408515Z","submitted_at":"2025-05-22T08:54:17Z","title":"Performance Guaranteed Poisoning Attacks in Federated Learning: A Sliding Mode Approach","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T15:06:53.879418Z"},"links":{"citing_paper":"/paper/2505.16403"},"observation_digest":"sha256:ea57f844705c4f903f2267c15971b11c27be7d9b443f1be9afb2729d023e3d38","observation_id":"da3ccd56-e1fb-464f-a8ef-fd19ae0567ef","resolution":{"observed_at":"2026-08-07T15:06:56.046732Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:06:55.837757Z","title":"Privcoll: Practical privacy-preserving collaborative machine learn- ing","venue":null,"work_id":"4601b7b2-21da-49bb-8654-d63b11aebe7e","year":2020},"citing_paper":{"arxiv_id":"2505.16403","last_updated":"2025-05-29T00:20:42Z","snapshot_observed_at":"2026-08-07T14:59:28.408515Z","submitted_at":"2025-05-22T08:54:17Z","title":"Performance Guaranteed Poisoning Attacks in Federated Learning: A Sliding Mode Approach","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T15:06:53.962870Z"},"links":{"citing_paper":"/paper/2505.16403"},"observation_digest":"sha256:0e81bd68f2f69a16471009329a1fbc0f74309ecde0d03ba2431d142bddb214dc","observation_id":"564e29d1-d00b-4566-aa7f-7e0d920ca5e7","resolution":{"observed_at":"2026-08-07T15:06:55.921464Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:06:55.643918Z","title":"A survey on federated learn- ing","venue":null,"work_id":"fe2501a0-e8ba-41be-b303-796f7aab4ab8","year":2021},"citing_paper":{"arxiv_id":"2505.16403","last_updated":"2025-05-29T00:20:42Z","snapshot_observed_at":"2026-08-07T14:59:28.408515Z","submitted_at":"2025-05-22T08:54:17Z","title":"Performance Guaranteed Poisoning Attacks in Federated Learning: A Sliding Mode Approach","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T15:06:54.019179Z"},"links":{"citing_paper":"/paper/2505.16403"},"observation_digest":"sha256:c6eaa5da6ff0b200bb73a7243afeed1b3618fe61bc9438f004a5245a1b28e058","observation_id":"c903801c-7afe-49df-9ef0-c498b7552ea2","resolution":{"observed_at":"2026-08-07T15:06:55.738556Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:06:55.449665Z","title":"Denial-of-service or fine-grained control: Towards flexible model poisoning attacks on federated learning","venue":null,"work_id":"46c69866-667e-4206-bada-13784127e978","year":2023},"citing_paper":{"arxiv_id":"2505.16403","last_updated":"2025-05-29T00:20:42Z","snapshot_observed_at":"2026-08-07T14:59:28.408515Z","submitted_at":"2025-05-22T08:54:17Z","title":"Performance Guaranteed Poisoning Attacks in Federated Learning: A Sliding Mode Approach","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T15:06:54.123544Z"},"links":{"citing_paper":"/paper/2505.16403"},"observation_digest":"sha256:b81a5dcbf28a5e7d1727498302fe6d79444b9e7fd110baa21919304f3db4e3c6","observation_id":"36daf518-a46f-4173-a08e-28bf91b52acb","resolution":{"observed_at":"2026-08-07T15:06:55.533990Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:06:55.148622Z","title":null,"venue":null,"work_id":"2c481ad8-f5b8-4af5-a549-998c7950a2f4","year":2009},"citing_paper":{"arxiv_id":"2505.16403","last_updated":"2025-05-29T00:20:42Z","snapshot_observed_at":"2026-08-07T14:59:28.408515Z","submitted_at":"2025-05-22T08:54:17Z","title":"Performance Guaranteed Poisoning Attacks in Federated Learning: A Sliding Mode Approach","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T15:06:54.221234Z"},"links":{"citing_paper":"/paper/2505.16403"},"observation_digest":"sha256:b7d643a76c838e924257e68fa5b6162fd0409be9690943df0f9770ab5f8e4034","observation_id":"e0c4b332-0979-492b-a2c3-35feba24aedf","resolution":{"observed_at":"2026-08-07T15:06:55.302646Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:06:54.839721Z","title":"Datasets • CIFAR10 [Krizhevsky, 2009]","venue":null,"work_id":"9aa97c68-51b3-4430-a019-4952047728ac","year":2009},"citing_paper":{"arxiv_id":"2505.16403","last_updated":"2025-05-29T00:20:42Z","snapshot_observed_at":"2026-08-07T14:59:28.408515Z","submitted_at":"2025-05-22T08:54:17Z","title":"Performance Guaranteed Poisoning Attacks in Federated Learning: A Sliding Mode Approach","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T15:06:54.312854Z"},"links":{"citing_paper":"/paper/2505.16403"},"observation_digest":"sha256:de215cf85c5cc4a876994c813d1b83efbd1f882efc8169c0e74112524b632c4c","observation_id":"0813fc18-9bd1-45d4-908a-e1336ebbc4d7","resolution":{"observed_at":"2026-08-07T15:06:54.964124Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:06:56.060386Z","title":"Terminal Sliding Mode Control – An Overview","venue":null,"work_id":"b6c9ba41-5c1b-4731-a73f-8a45a175f389","year":2021},"citing_paper":{"arxiv_id":"2505.16403","last_updated":"2025-05-29T00:20:42Z","snapshot_observed_at":"2026-08-07T14:59:28.408515Z","submitted_at":"2025-05-22T08:54:17Z","title":"Performance Guaranteed Poisoning Attacks in Federated Learning: A Sliding Mode Approach","version":2},"reference_index":1999,"source":"pdf_text","source_observed_at":"2026-08-07T15:06:53.830406Z"},"links":{"citing_paper":"/paper/2505.16403"},"observation_digest":"sha256:23c9bfe4aaf89a062a9635bcb0fa12c9a73d5f538d1285e39c6096bec6e60c76","observation_id":"bdd58db4-6204-42e5-9977-00c4e87f8fec","resolution":{"observed_at":"2026-08-07T15:06:56.063840Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:06:56.273625Z","title":"The MNIST Database of Handwrit- ten Digit Images for Machine Learning Research [Best of the Web]","venue":null,"work_id":"5dfb8b51-f190-45a9-b922-1588aa76b06c","year":2012},"citing_paper":{"arxiv_id":"2505.16403","last_updated":"2025-05-29T00:20:42Z","snapshot_observed_at":"2026-08-07T14:59:28.408515Z","submitted_at":"2025-05-22T08:54:17Z","title":"Performance Guaranteed Poisoning Attacks in Federated Learning: A Sliding Mode Approach","version":2},"reference_index":2009,"source":"pdf_text","source_observed_at":"2026-08-07T15:06:51.718214Z"},"links":{"citing_paper":"/paper/2505.16403"},"observation_digest":"sha256:9612d1781bde083e03ce8144474746d51cc28a50cd736e42da71a42b2c0f4297","observation_id":"97328e67-83f9-4ed4-b6b7-c72ccefa1108","resolution":{"observed_at":"2026-08-07T15:06:56.277056Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:06:56.070626Z","title":"Byzantine-Robust Dis- tributed Learning: Towards Optimal Statistical Rates, February","venue":null,"work_id":"5f79e83a-1232-45e8-b9b7-7c2c063c674e","year":2021},"citing_paper":{"arxiv_id":"2505.16403","last_updated":"2025-05-29T00:20:42Z","snapshot_observed_at":"2026-08-07T14:59:28.408515Z","submitted_at":"2025-05-22T08:54:17Z","title":"Performance Guaranteed Poisoning Attacks in Federated Learning: A Sliding Mode Approach","version":2},"reference_index":2011,"source":"pdf_text","source_observed_at":"2026-08-07T15:06:53.648650Z"},"links":{"citing_paper":"/paper/2505.16403"},"observation_digest":"sha256:d1d9eea7aa6b6699c70b5efe620688edb695c8a619daec9222ddd7fd3ca4248e","observation_id":"dc273268-bcb0-47d6-9a36-e71facf976eb","resolution":{"observed_at":"2026-08-07T15:06:56.073945Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:06:56.263302Z","title":"[Fang et al., 2020] Minghong Fang, Xiaoyu Cao, Jinyuan Jia, and Neil Gong","venue":null,"work_id":"e7eb6d90-3943-4a5a-9197-f7662f22bc79","year":2020},"citing_paper":{"arxiv_id":"2505.16403","last_updated":"2025-05-29T00:20:42Z","snapshot_observed_at":"2026-08-07T14:59:28.408515Z","submitted_at":"2025-05-22T08:54:17Z","title":"Performance Guaranteed Poisoning Attacks in Federated Learning: A Sliding Mode Approach","version":2},"reference_index":2012,"source":"pdf_text","source_observed_at":"2026-08-07T15:06:51.836627Z"},"links":{"citing_paper":"/paper/2505.16403"},"observation_digest":"sha256:80675a1881c67339c7d41d238e613ddf78c43faea7d9cf0bed4ec06f019d1e0e","observation_id":"f45ebb15-2466-4775-a5bd-58c574b53d5b","resolution":{"observed_at":"2026-08-07T15:06:56.266928Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:06:56.176623Z","title":"Krizhevsky","venue":null,"work_id":"e824a096-5285-4b3b-a7b7-4ab9d719591d","year":2009},"citing_paper":{"arxiv_id":"2505.16403","last_updated":"2025-05-29T00:20:42Z","snapshot_observed_at":"2026-08-07T14:59:28.408515Z","submitted_at":"2025-05-22T08:54:17Z","title":"Performance Guaranteed Poisoning Attacks in Federated Learning: A Sliding Mode Approach","version":2},"reference_index":2013,"source":"pdf_text","source_observed_at":"2026-08-07T15:06:52.581958Z"},"links":{"citing_paper":"/paper/2505.16403"},"observation_digest":"sha256:36957adf1f76f6e0fb7f533ae7a6cee21de9c0c938b662e029f349dfb8edfe71","observation_id":"04f49023-e62a-4f73-ab6c-c881bf3cf6fe","resolution":{"observed_at":"2026-08-07T15:06:56.179724Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:06:56.159217Z","title":"DSP-Based Sliding-Mode Control for Electromagnetic-Levitation Precise-Position System","venue":null,"work_id":"a46c02cf-8d2a-44bd-b37f-eaa2b5b2177e","year":2013},"citing_paper":{"arxiv_id":"2505.16403","last_updated":"2025-05-29T00:20:42Z","snapshot_observed_at":"2026-08-07T14:59:28.408515Z","submitted_at":"2025-05-22T08:54:17Z","title":"Performance Guaranteed Poisoning Attacks in Federated Learning: A Sliding Mode Approach","version":2},"reference_index":2015,"source":"pdf_text","source_observed_at":"2026-08-07T15:06:52.751968Z"},"links":{"citing_paper":"/paper/2505.16403"},"observation_digest":"sha256:f01ce0e68d5887fb4bfd69d78474bbffe987a5a44405d05ca592c8d4e14fd9db","observation_id":"0166140a-f691-4264-8d61-35a8dfa2aafd","resolution":{"observed_at":"2026-08-07T15:06:56.162973Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:06:56.283844Z","title":"FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping, April","venue":null,"work_id":"f69350bd-b74f-4a93-ac34-fdf68966381e","year":2022},"citing_paper":{"arxiv_id":"2505.16403","last_updated":"2025-05-29T00:20:42Z","snapshot_observed_at":"2026-08-07T14:59:28.408515Z","submitted_at":"2025-05-22T08:54:17Z","title":"Performance Guaranteed Poisoning Attacks in Federated Learning: A Sliding Mode Approach","version":2},"reference_index":2017,"source":"pdf_text","source_observed_at":"2026-08-07T15:06:51.444806Z"},"links":{"citing_paper":"/paper/2505.16403"},"observation_digest":"sha256:7720c9e794c048c4f5d0eaff34f0eae98815da995aad13fb9899f43e1a77404e","observation_id":"8c7ec271-f6aa-4dca-b713-b6133a083ddb","resolution":{"observed_at":"2026-08-07T15:06:56.287819Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:06:56.209460Z","title":"[Jebreel and Domingo-Ferrer, 2023] Najeeb Moharram Je- breel and Josep Domingo-Ferrer","venue":null,"work_id":"5e5c86b5-2aa4-4fcb-9b02-10c2502a57e1","year":2023},"citing_paper":{"arxiv_id":"2505.16403","last_updated":"2025-05-29T00:20:42Z","snapshot_observed_at":"2026-08-07T14:59:28.408515Z","submitted_at":"2025-05-22T08:54:17Z","title":"Performance Guaranteed Poisoning Attacks in Federated Learning: A Sliding Mode Approach","version":2},"reference_index":2018,"source":"pdf_text","source_observed_at":"2026-08-07T15:06:52.271593Z"},"links":{"citing_paper":"/paper/2505.16403"},"observation_digest":"sha256:ea83b15c85e97b27623cd3a4b1c000cac4452650b1494eb27d54732cafdbe2f7","observation_id":"4f1423ec-6879-4743-bae9-9de79c59be5d","resolution":{"observed_at":"2026-08-07T15:06:56.212731Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:06:56.313589Z","title":"How To Backdoor Federated Learning","venue":null,"work_id":"b3d04c8e-9aee-410c-9c92-32b1de01a8b1","year":2020},"citing_paper":{"arxiv_id":"2505.16403","last_updated":"2025-05-29T00:20:42Z","snapshot_observed_at":"2026-08-07T14:59:28.408515Z","submitted_at":"2025-05-22T08:54:17Z","title":"Performance Guaranteed Poisoning Attacks in Federated Learning: A Sliding Mode Approach","version":2},"reference_index":2019,"source":"pdf_text","source_observed_at":"2026-08-07T15:06:50.700145Z"},"links":{"citing_paper":"/paper/2505.16403"},"observation_digest":"sha256:1219fe8f62b5edc80ee34bdceb6471337dcf07909612db7b5df957d2e4d2c74b","observation_id":"1cf4b5d7-1846-41b4-af8d-b9bf79cde64e","resolution":{"observed_at":"2026-08-07T15:06:56.316528Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:06:56.304085Z","title":"A Little Is Enough: Circumventing De- fenses For Distributed Learning","venue":null,"work_id":"2facb788-6805-4365-9ae9-dde400487ea3","year":2019},"citing_paper":{"arxiv_id":"2505.16403","last_updated":"2025-05-29T00:20:42Z","snapshot_observed_at":"2026-08-07T14:59:28.408515Z","submitted_at":"2025-05-22T08:54:17Z","title":"Performance Guaranteed Poisoning Attacks in Federated Learning: A Sliding Mode Approach","version":2},"reference_index":2020,"source":"pdf_text","source_observed_at":"2026-08-07T15:06:50.871572Z"},"links":{"citing_paper":"/paper/2505.16403"},"observation_digest":"sha256:f01b306ca150b753b3c296414aed9b9453b35ddac3b2c6acdc081d69a14a86e4","observation_id":"45fb1856-5e66-4c11-b1a1-c6d8993c90ad","resolution":{"observed_at":"2026-08-07T15:06:56.307570Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:06:56.243246Z","title":"Agramplifier: Defending federated learning against poisoning attacks through local update amplifica- tion","venue":null,"work_id":"9526882d-5afb-485b-aed9-0e028457100b","year":2024},"citing_paper":{"arxiv_id":"2505.16403","last_updated":"2025-05-29T00:20:42Z","snapshot_observed_at":"2026-08-07T14:59:28.408515Z","submitted_at":"2025-05-22T08:54:17Z","title":"Performance Guaranteed Poisoning Attacks in Federated Learning: A Sliding Mode Approach","version":2},"reference_index":2021,"source":"pdf_text","source_observed_at":"2026-08-07T15:06:52.035802Z"},"links":{"citing_paper":"/paper/2505.16403"},"observation_digest":"sha256:bd69f3bd858813c54b8e4b83d40a283fbc32e7cfe2cac2d0b6e6696ab10540c7","observation_id":"1398e35b-9ded-4839-b6cc-cf470bdc5c35","resolution":{"observed_at":"2026-08-07T15:06:56.246704Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:06:56.198796Z","title":"Learning from History for Byzan- tine Robust Optimization, June","venue":null,"work_id":"f28f082f-e5d7-4658-9709-43bf876d34a4","year":2021},"citing_paper":{"arxiv_id":"2505.16403","last_updated":"2025-05-29T00:20:42Z","snapshot_observed_at":"2026-08-07T14:59:28.408515Z","submitted_at":"2025-05-22T08:54:17Z","title":"Performance Guaranteed Poisoning Attacks in Federated Learning: A Sliding Mode Approach","version":2},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-07T15:06:52.354961Z"},"links":{"citing_paper":"/paper/2505.16403"},"observation_digest":"sha256:638a8b880eb331178548f7dfad533550e1ba55f87d536408f75a07e14d0b7d9e","observation_id":"4b7c71f3-9f62-4dee-aeb9-150bf6d2975f","resolution":{"observed_at":"2026-08-07T15:06:56.202549Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:06:56.232190Z","title":"Not all edges are equally robust: Evaluating the robustness of ranking-based federated learning","venue":null,"work_id":"cfb1e858-9ae9-4101-9d31-dbf444fa5d01","year":2025},"citing_paper":{"arxiv_id":"2505.16403","last_updated":"2025-05-29T00:20:42Z","snapshot_observed_at":"2026-08-07T14:59:28.408515Z","submitted_at":"2025-05-22T08:54:17Z","title":"Performance Guaranteed Poisoning Attacks in Federated Learning: A Sliding Mode Approach","version":2},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-07T15:06:52.119114Z"},"links":{"citing_paper":"/paper/2505.16403"},"observation_digest":"sha256:53a67c271eaf381091f441da6b7bbb861499dbee13def80a150abfd793431795","observation_id":"f8637007-0384-478f-aedb-fbad69060c7b","resolution":{"observed_at":"2026-08-07T15:06:56.235759Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:06:56.220037Z","title":"Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning","venue":null,"work_id":"67f4f756-bd41-47e1-9ca5-3d497eaeb444","year":2018},"citing_paper":{"arxiv_id":"2505.16403","last_updated":"2025-05-29T00:20:42Z","snapshot_observed_at":"2026-08-07T14:59:28.408515Z","submitted_at":"2025-05-22T08:54:17Z","title":"Performance Guaranteed Poisoning Attacks in Federated Learning: A Sliding Mode Approach","version":2},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-07T15:06:52.211847Z"},"links":{"citing_paper":"/paper/2505.16403"},"observation_digest":"sha256:82d2eeb1d7679ae47783a3ff173ef64bb82ae7af0a18480e3e1b53c681694841","observation_id":"1683d867-309a-4383-89b4-e4c548d1f445","resolution":{"observed_at":"2026-08-07T15:06:56.223919Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2505.16403","last_updated":"2025-05-29T00:20:42Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-07T14:59:28.408515Z","submitted_at":"2025-05-22T08:54:17Z","title":"Performance Guaranteed Poisoning Attacks in Federated Learning: A Sliding Mode Approach"},"reference_resolution":{"displayed":39,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":6,"verified_exact":0,"verified_fuzzy":32},"total_outbound_references":39},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2505.16403."}