{"as_of":"2026-08-17T05:53:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:5f40e906babb6774f130b55a47b3ea0abed49567af3b42484e946dfdbec9a986","coverage":[{"denominator":55,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":55,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-15T14:37:33.835218Z","state":"measured"},{"denominator":55,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":55,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-16T06:30:59.297886+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/2608.06520/citation-record","integrity":"/paper/2608.06520/integrity","json":"/paper/2608.06520/citation-record.json","paper":"/paper/2608.06520"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T14:37:34.826065Z","title":"A comprehensive survey on multi-agent reinforcement learning for connected and automated vehicles.Sensors, 23(10):4710, 2023","venue":null,"work_id":"fffc806c-bfae-4150-93f6-9004c8075e85","year":2023},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.591610Z"},"links":{"citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:35445a47148efb234f8883b304c34313b34921c102c1da6422a6c9975e7f02e9","observation_id":"1f95496e-babd-4985-a496-4c097e772e89","resolution":{"observed_at":"2026-08-15T14:37:34.830863Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T14:37:34.812175Z","title":null,"venue":null,"work_id":"df780794-bb8b-4442-a01b-692ba2011ef5","year":2025},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.597390Z"},"links":{"citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:11281d117ef4c170ddb37117a5efe695fdabc1fc6eb5722fd0e3e869a146e5d9","observation_id":"85a810b9-e726-4122-b4b8-8672d8705a18","resolution":{"observed_at":"2026-08-15T14:37:34.816616Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2304.08493","last_updated":"2022-12-23T13:12:17Z","snapshot_observed_at":"2026-08-16T16:06:22.292313Z","submitted_at":"2022-12-23T13:12:17Z","title":"Coordinated Multi-Agent Reinforcement Learning for Unmanned Aerial Vehicle Swarms in Autonomous Mobile Access Applications","version":1},"cited_work":{"arxiv_id":"2304.08493","doi":null,"metadata_source":"pith","pith_arxiv_id":"2304.08493","snapshot_observed_at":"2026-08-15T14:37:34.193451Z","title":"Coordinated Multi-Agent Reinforcement Learning for Unmanned Aerial Vehicle Swarms in Autonomous Mobile Access Applications","venue":"cs.MA","work_id":"6f641325-4e9b-4a4d-84a1-8dbf092ce3d3","year":2022},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.602078Z"},"links":{"cited_paper":"/paper/2304.08493","citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:4f73cd05f46b09e2d845209a7f32745a0ca9040de141bf5c0afabdb8d6f17d05","observation_id":"461e1072-91b7-4ae3-9809-eab63ce303db","resolution":{"observed_at":"2026-08-15T14:37:34.198529Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T14:37:34.797954Z","title":"Cooperative multiagent deep reinforcement learning for reliable surveillance via autonomous multi-uav control.IEEE Transactions on Industrial Informatics, 18(10):7086–7096, 2022","venue":null,"work_id":"5284cd88-a22f-434a-97a1-afafc8d55e50","year":2022},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.607210Z"},"links":{"citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:5212c168979261b4799cc668b837eda07417e4517d5a59be1790c3524a644f62","observation_id":"4d0e2161-1cb5-4e6a-aa0f-d52e77652eea","resolution":{"observed_at":"2026-08-15T14:37:34.802572Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T14:37:34.783719Z","title":null,"venue":null,"work_id":"aecd351c-e4ac-4596-8941-90ac802bfc74","year":2019},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.611681Z"},"links":{"citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:dee1148b812f70afa194b54eb78391bd06a30479cb79642a7a8d2b70f4e49228","observation_id":"45e979f8-8f84-48a8-8f89-2724d0fdf67c","resolution":{"observed_at":"2026-08-15T14:37:34.788165Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.08155","last_updated":"2023-10-03T20:47:10Z","snapshot_observed_at":"2026-08-08T22:28:26.004138Z","submitted_at":"2023-08-16T05:57:52Z","title":"AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.08155","snapshot_observed_at":"2026-08-15T14:37:33.615961Z","title":"Autogen: Enabling next-gen llm applications via multi-agent conversation.arXiv preprint arXiv:2308.08155, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.615961Z"},"links":{"cited_paper":"/paper/2308.08155","citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:ad369243280740b1703478975bdb043e939436b86fa1f6b8632e5df0e6ebcc60","observation_id":"961502ca-0e04-426a-bb91-e0ffb6ea8df0","resolution":{"observed_at":"2026-08-15T14:37:33.615961Z","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":"2026-08-15T14:37:33.621191Z","title":"Camel: Communicative agents for\" mind\" exploration of large language model society.Advances in neural information processing systems, 36:51991–52008, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.621191Z"},"links":{"citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:9248dbb2a538da56d0a1e065b488a7c0672ca522c95804822f4b740205de4e3d","observation_id":"dcb25e8a-32c2-4d2d-8ef3-7e329b39133e","resolution":{"observed_at":"2026-08-15T14:37:33.621191Z","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":"2026-08-15T14:37:34.760019Z","title":"Robust llm-based multi-agent system with action negotiation and sharing redundancy enhancement","venue":null,"work_id":"c7f29bc4-b587-4bb7-849f-c5f4c24d8cbf","year":2026},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.625450Z"},"links":{"citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:00077371e16c6181b0cc53882af8e3830c5669f687fcc28c4d3c25fa9ddab008","observation_id":"1e74cc00-8ae3-449a-b23e-a0266074ef78","resolution":{"observed_at":"2026-08-15T14:37:34.764982Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T14:37:33.629826Z","title":"Not what you’ve signed up for: Compromising real-world llm-integrated applications with indirect prompt injection, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.629826Z"},"links":{"citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:1704898c347f3e79c2e865dd4361954e4893e8e0f0459feb63e6a9d32468e171","observation_id":"e6c18cee-f530-4b2c-b544-dfcc770d8b89","resolution":{"observed_at":"2026-08-15T14:37:33.629826Z","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":"2026-08-15T14:37:34.736234Z","title":"The byzantine generals problem","venue":null,"work_id":"9fd2a122-727b-473a-aea0-8464768da11d","year":2019},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.634252Z"},"links":{"citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:07cf723c4bdb06009e97e7f7b664700b31fca935caab4c1d191f5b95cb05d529","observation_id":"f92feeb6-ae31-4a74-8223-42d50ca99b7b","resolution":{"observed_at":"2026-08-15T14:37:34.740394Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T14:37:34.721752Z","title":"Learning from history for byzantine robust optimization","venue":null,"work_id":"8bc98748-4d54-46bc-b224-304091e46f76","year":2021},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.638673Z"},"links":{"citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:8bf2efe6f4a541e4e8ebbe8605da89cea27c1b8955f61b7f6f4957ad7a62a6bd","observation_id":"3ddb354c-6055-49ce-8b2f-1f52249dd301","resolution":{"observed_at":"2026-08-15T14:37:34.726461Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1905.10615","last_updated":"2021-01-17T19:25:56Z","snapshot_observed_at":"2026-08-14T16:26:39.989221Z","submitted_at":"2019-05-25T15:23:19Z","title":"Adversarial Policies: Attacking Deep Reinforcement Learning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1905.10615","snapshot_observed_at":"2026-08-15T14:37:33.643023Z","title":"Adversarial policies: Attacking deep reinforcement learning.arXiv preprint arXiv:1905.10615, 2019","venue":null,"work_id":null,"year":1905},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.643023Z"},"links":{"cited_paper":"/paper/1905.10615","citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:bf1a216c72b636715af6ca28ed7225fd0477439a780af2d47752e3baed8a4e87","observation_id":"8f7258b4-f119-478e-9c91-1dc5ae02f1ac","resolution":{"observed_at":"2026-08-15T14:37:33.643023Z","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":"2026-08-15T14:37:34.707765Z","title":"On the robustness of cooperative multi-agent reinforcement learning","venue":null,"work_id":"54425aa4-6ab1-4378-aab7-b4ca24796ba9","year":2020},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.648791Z"},"links":{"citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:ed53375472f730fb3e998ceb6c76957f30f7e65cbc5040df3b1ea100d6ceaf65","observation_id":"a717d7e3-c0dd-477b-8dcd-5604582d1fc9","resolution":{"observed_at":"2026-08-15T14:37:34.712190Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T14:37:34.693240Z","title":"Attacking cooperative multi-agent reinforcement learning by adversarial minority influence","venue":null,"work_id":"b75985d2-4b21-4f0d-b50c-212dfcf9f350","year":2025},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.653199Z"},"links":{"citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:ae07a0e39e61713ee6493ee781d43d5312e4de359fe72ccf26e9654ff18fc7af","observation_id":"06209aab-a72b-43b6-a19d-42fd3db4d702","resolution":{"observed_at":"2026-08-15T14:37:34.698024Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T14:37:34.678714Z","title":"Empirical study on robustness and resilience in cooperative multi-agent reinforcement learning.Advances in Neural Information Processing Systems, 38:44009–44052, 2026","venue":null,"work_id":"5cc32798-a494-4cd7-83c2-c7f7a90d7836","year":2026},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.657372Z"},"links":{"citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:2908f33aa302e60a4383336a67a32977617d49b963e746f72972ac9dfb6ea3c7","observation_id":"aad9e6e3-1f10-4a63-a633-1a81e75c3bfa","resolution":{"observed_at":"2026-08-15T14:37:34.683537Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T14:37:33.661753Z","title":"Robust dynamic programming.Mathematics of Operations Research, 30(2):257–280, 2005","venue":null,"work_id":null,"year":2005},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.661753Z"},"links":{"citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:8946d8eca6319cb974d555921893f5a3d207347598a84dc5465765092023763e","observation_id":"4a4d3f07-d084-4409-be8f-dc2f990bb390","resolution":{"observed_at":"2026-08-15T14:37:33.661753Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2112.13487","last_updated":"2023-07-11T16:47:42Z","snapshot_observed_at":"2026-08-16T17:31:55.368873Z","submitted_at":"2021-12-27T02:53:44Z","title":"The Statistical Complexity of Interactive Decision Making","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2112.13487","snapshot_observed_at":"2026-08-15T14:37:33.665958Z","title":"The statistical complexity of interactive decision making.arXiv preprint arXiv:2112.13487, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.665958Z"},"links":{"cited_paper":"/paper/2112.13487","citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:15b44ac77bb8dc1fad134b869341a69e9a432678b3dceb328564f81394ec2f48","observation_id":"5e684cdd-ac2f-4e1d-af5f-8e729dc8bec0","resolution":{"observed_at":"2026-08-15T14:37:33.665958Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.06820","last_updated":"2025-06-26T14:54:55Z","snapshot_observed_at":"2026-08-16T12:42:43.169347Z","submitted_at":"2025-04-09T12:25:00Z","title":"Regret Bounds for Robust Online Decision Making","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.06820","snapshot_observed_at":"2026-08-15T14:37:33.670712Z","title":"Regret bounds for robust online decision making.arXiv preprint arXiv:2504.06820, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.670712Z"},"links":{"cited_paper":"/paper/2504.06820","citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:cacbee6037605a36abf220dccaca3bf105e1dd9f60bf8166c6ff8ce9395c9155","observation_id":"0d36f409-86c1-4d41-9a17-abf66e679a64","resolution":{"observed_at":"2026-08-15T14:37:33.670712Z","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":"2026-08-15T14:37:34.655026Z","title":"Action robust reinforcement learning and applications in continuous control","venue":null,"work_id":"af24fc9f-f26e-4a73-a5ff-5ae867d93c9a","year":2019},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.675288Z"},"links":{"citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:5daefdb40f244bdb10bdaccd967c3f0e9e50585735d9a5b5b18d06f6811ba7a7","observation_id":"4e003576-bcb2-4b98-92e6-bf83689f8a23","resolution":{"observed_at":"2026-08-15T14:37:34.659560Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T14:37:34.640705Z","title":"Resilient multi-agent reinforcement learning with adversarial value decomposition","venue":null,"work_id":"b9ca9bbb-7271-45fe-9197-3440eb047a28","year":2021},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.679416Z"},"links":{"citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:9ade6f815f9dd498c4fe3f93370e511d99778f96f82d4a139821dc88d438d652","observation_id":"3d939808-957e-4d20-8bc3-67b195c333a2","resolution":{"observed_at":"2026-08-15T14:37:34.645362Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T14:37:34.626713Z","title":"Robust multi-agent coordination via evolutionary generation of auxiliary adversarial attackers","venue":null,"work_id":"2eb1ce18-8a5c-4ac9-afdb-9a205b8f8737","year":2023},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.683396Z"},"links":{"citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:8388ea727c8e2a1e77142245392eba814a8459da72f9a9646d4a1a9c7f99fb2f","observation_id":"67efacdf-9c50-4e9f-92d7-1df816d09712","resolution":{"observed_at":"2026-08-15T14:37:34.631367Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T14:37:34.611986Z","title":null,"venue":null,"work_id":"261fd119-3210-4f0d-a80b-963ccef5cf8c","year":2023},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.687827Z"},"links":{"citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:033e392a30f456aaf81c27992600e00d46ae01a1b96833bfff828630d2783a22","observation_id":"9cffc3c5-b9c7-4156-abc3-d47200021b12","resolution":{"observed_at":"2026-08-15T14:37:34.616586Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.02844","last_updated":"2025-06-18T06:49:09Z","snapshot_observed_at":"2026-08-15T13:30:06.376395Z","submitted_at":"2025-02-05T02:59:23Z","title":"Wolfpack Adversarial Attack for Robust Multi-Agent Reinforcement Learning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.02844","snapshot_observed_at":"2026-08-15T14:37:33.691968Z","title":"Wolfpack adversarial attack for robust multi-agent reinforcement learning.arXiv preprint arXiv:2502.02844, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.691968Z"},"links":{"cited_paper":"/paper/2502.02844","citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:d4323f8ca7322c1ffa73eba63775d14a659756c7565086f4942f5e723241d76a","observation_id":"21996f1d-8760-4e0c-bd9c-072e0b6525ce","resolution":{"observed_at":"2026-08-15T14:37:33.691968Z","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":"2026-08-15T14:37:34.597801Z","title":"Roping in uncertainty: Robustness and regularization in markov games","venue":null,"work_id":"6d147a48-eb9f-490c-a267-b7504c533081","year":2024},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.696574Z"},"links":{"citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:e6b71e155c09e2458f2b2f5e76bac60e4d4385fe53ce702de0936385e642c9ef","observation_id":"93925888-ecaa-46f4-8b79-a56b65397ec8","resolution":{"observed_at":"2026-08-15T14:37:34.602288Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T14:37:34.582873Z","title":"Byzantine robust cooperative multi-agent reinforcement learning as a bayesian game","venue":null,"work_id":"28c61738-1f9f-4a6b-b49c-b7007a1f65dc","year":2024},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.700756Z"},"links":{"citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:b9fd72b2b99d3971f8f50b803a279389494d7c1b92f2a6f515c443022140c765","observation_id":"f5e57ce0-8db4-4aea-acdf-3d72e96f9b7e","resolution":{"observed_at":"2026-08-15T14:37:34.587528Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T14:37:34.567446Z","title":"Defending against unknown corrupted agents: Reinforcement learning of adversarially robust nash equilibria.Transactions on Machine Learning Research, 2024","venue":null,"work_id":"cd93ca93-c2a4-496e-82a7-f203c62eb4ef","year":2024},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.705238Z"},"links":{"citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:25ec641d9797e899936becb474ab1e1a0f41208dec72c585e36337b40723c0a4","observation_id":"648cb9d8-113c-4a42-be98-e429180c478f","resolution":{"observed_at":"2026-08-15T14:37:34.572806Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T14:37:34.553706Z","title":"Byzantine-robust online and offline distributed reinforcement learning","venue":null,"work_id":"ef05b858-eb6e-4614-87f4-8082f3b4d60f","year":2023},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.709850Z"},"links":{"citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:51cb44210bceb5ce5f3bbbe1be2c6171ad0a2f34bcdbfd126709220ba5eb9ef3","observation_id":"9bc57015-2331-457b-a3ae-c35fb7db6abb","resolution":{"observed_at":"2026-08-15T14:37:34.557994Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T14:37:34.538441Z","title":"Byzantine tolerant algorithms for federated learning.IEEE Transactions on Network Science and Engineering, 10(6):3172–3183, 2023","venue":null,"work_id":"58c19023-438f-4c73-ae87-d9be329f3146","year":2023},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.715477Z"},"links":{"citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:4202ee7b10d0b29c7cf6bba3fc6cc82f224deca94b11845ed271ddd7c5e876f3","observation_id":"62969dcc-4d3b-45d1-9042-fbdad033233d","resolution":{"observed_at":"2026-08-15T14:37:34.543672Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T14:37:34.523851Z","title":"Provably robust federated reinforcement learning","venue":null,"work_id":"443b0a14-71d3-4ef8-b83a-488d5f4261cf","year":2025},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.720861Z"},"links":{"citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:6424df0489caad8d844fe2287a61225985a1386b3a948ca1ed6a98afba5870b4","observation_id":"9c8a3e77-1c17-43a3-881e-561c084e1f64","resolution":{"observed_at":"2026-08-15T14:37:34.528256Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T14:37:34.509632Z","title":"Br- defedrl: Byzantine-robust decentralized federated reinforcement learning with fast convergence and communication efficiency","venue":null,"work_id":"550c00e0-6fc4-41be-81de-a93fe47d1315","year":2024},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.725632Z"},"links":{"citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:9a3179f09e626503fc037e2bbcd30c4cca9c757c7d62fd8924f35d40825fcb33","observation_id":"6236f046-10e3-4e4e-84ae-2d1bc9d467b6","resolution":{"observed_at":"2026-08-15T14:37:34.514402Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T14:37:34.494958Z","title":"Byzantine-robust federated reinforcement learning via critical parameter analysis.International Journal of Machine Learning and Cybernetics, 16(12):10607–10620, 2025","venue":null,"work_id":"70520d03-1c03-4d8d-a81a-18d16acc2009","year":2025},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.730139Z"},"links":{"citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:9b433fc9eb16b1b93557ed9dc6604db4113b2fde3803465f7dde03d6fd8c5eb9","observation_id":"c2995c4b-eca3-4bc2-bd7b-bd1ccf39a5f2","resolution":{"observed_at":"2026-08-15T14:37:34.500149Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T14:37:34.480026Z","title":"Byzantine-robust federated deep deterministic policy gradient","venue":null,"work_id":"7a75d8c4-b8c0-4341-b8c3-a980ecad9cb6","year":2022},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.734372Z"},"links":{"citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:e56dcfeaa71a91d52d7963c1b5614b9199ba31d4a84da13c8d68521b7adbb72f","observation_id":"387aa618-f968-4346-a80d-12898d9ec9be","resolution":{"observed_at":"2026-08-15T14:37:34.484995Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T14:37:34.465447Z","title":"Byzantine-robust federated learning with optimal statistical rates","venue":null,"work_id":"ed7d2e98-04c8-45c1-856e-fa57ff474db8","year":2023},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.738648Z"},"links":{"citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:32ca0dcbadf40d68f503ff7bff6b6dd7521b3c6ee02827d36e4f0a5d6fd2d085","observation_id":"59d58499-8a4e-4054-8f53-05d3d5a78888","resolution":{"observed_at":"2026-08-15T14:37:34.470381Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T14:37:33.742926Z","title":"Robust control of markov decision processes with uncertain transition matrices.Operations Research, 53(5):780–798, 2005","venue":null,"work_id":null,"year":2005},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.742926Z"},"links":{"citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:2df89308604d26d227a7a4edee2d112943e3b9d5d0401c0f9d97c65e272cfcc7","observation_id":"da584e03-6665-4ee6-940b-4114fc46a1e8","resolution":{"observed_at":"2026-08-15T14:37:33.742926Z","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":"2026-08-15T14:37:34.439654Z","title":"Robust markov decision processes.Mathematics of Operations Research, 38(1):153–183, 2013","venue":null,"work_id":"a4b2ccdc-0a30-4367-913c-3c9ff524f06b","year":2013},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.747083Z"},"links":{"citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:5e512802c67b2831cc363d505734e30979b7d3c5398d2f1972d058f8e9291aca","observation_id":"4c6f2cef-ac8b-4b05-b838-8f87fe9b0088","resolution":{"observed_at":"2026-08-15T14:37:34.444857Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T14:37:34.424625Z","title":"Sample complexity of robust reinforcement learning with a generative model","venue":null,"work_id":"17c0a6cd-a14e-4763-b7f6-5b8d60aefa5e","year":2022},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.751630Z"},"links":{"citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:3fa2695397176faa2c8a9d462e12b437bd74b72b492b7f973cd25953895cfcd5","observation_id":"709eeea1-0e85-4dc5-92c3-7aea72446f56","resolution":{"observed_at":"2026-08-15T14:37:34.429428Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T14:37:34.409853Z","title":"Toward theoretical understandings of robust markov decision processes: Sample complexity and asymptotics.The Annals of Statistics, 50(6):3223–3248, 2022","venue":null,"work_id":"aede19e8-54a8-4364-bd71-844e93e2844a","year":2022},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.755719Z"},"links":{"citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:2962a3eb07ca6e30d981bcdae56960304f8fd0a7760fbd978932919ba0625b2f","observation_id":"bbe48c57-fed7-4482-a51e-35d9f80bc986","resolution":{"observed_at":"2026-08-15T14:37:34.414704Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.16589","last_updated":"2025-09-08T02:57:28Z","snapshot_observed_at":"2026-08-16T15:29:29.662333Z","submitted_at":"2023-05-26T02:32:03Z","title":"The Curious Price of Distributional Robustness in Reinforcement Learning with a Generative Model","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.16589","snapshot_observed_at":"2026-08-15T14:37:33.760273Z","title":"The curious price of distributional robustness in reinforcement learning with a generative model.arXiv preprint arXiv:2305.16589, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.760273Z"},"links":{"cited_paper":"/paper/2305.16589","citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:5e96a8755a0ca9e641521ffe54c3388824655ade49df1f0a4b42d2829ad4d20c","observation_id":"d7c99203-09f1-416d-aeb3-0f61e06a57d4","resolution":{"observed_at":"2026-08-15T14:37:33.760273Z","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":"2026-08-15T14:37:34.394975Z","title":"Online robust reinforcement learning with model uncertainty","venue":null,"work_id":"49a0df5b-407b-43e1-b550-5654b01b92a3","year":2021},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.764956Z"},"links":{"citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:e157055b6f75448939fae47fc8f071a5ac22bbffee1a82727a8dfe325a6bd493","observation_id":"6e740092-c2e7-4b10-a2a7-87f507c45874","resolution":{"observed_at":"2026-08-15T14:37:34.399673Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T14:37:34.380488Z","title":null,"venue":null,"work_id":"0fffa97a-957f-489d-9ab5-4a218a7dea6e","year":2024},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.769478Z"},"links":{"citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:5a03fd3d1d32df79ff6aa4618b18b857d541d1a3d4cb85ec49780db26e52cf22","observation_id":"346c9fc6-348f-4e3f-baea-f28d2b42fcbf","resolution":{"observed_at":"2026-08-15T14:37:34.385084Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T14:37:34.365934Z","title":"Sample complexity of distributionally robust off-dynamics reinforcement learning with online interaction","venue":null,"work_id":"c47509f9-b2ef-4e4e-938e-d4caf6766365","year":2025},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.773972Z"},"links":{"citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:357c3007d595c7c1a45e3d7de89d53c2297016b7decd6c05c2e1d097bfa1ef78","observation_id":"cdaa6028-c9c3-45e7-8420-18404ba351f8","resolution":{"observed_at":"2026-08-15T14:37:34.370460Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T14:37:33.778352Z","title":"Corruption-robust offline reinforcement learning with general function approximation.Advances in Neural Information Processing Systems, 36:36208–36221, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.778352Z"},"links":{"citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:7b571700f7ddfeb314bb90374e380deb1e184cba561c3f135757e58a566160eb","observation_id":"eb84cf09-ff1d-4514-b679-ec889e8c81a6","resolution":{"observed_at":"2026-08-15T14:37:33.778352Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2106.06630","last_updated":"2021-06-11T22:41:53Z","snapshot_observed_at":"2026-08-16T18:17:41.722876Z","submitted_at":"2021-06-11T22:41:53Z","title":"Corruption-Robust Offline Reinforcement Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2106.06630","snapshot_observed_at":"2026-08-15T14:37:33.782694Z","title":"Corruption-robust offline reinforcement learning.arXiv preprint arXiv:2106.06630, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.782694Z"},"links":{"cited_paper":"/paper/2106.06630","citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:16b6a2cb4057e369a73323969e43e1162c252f2a37c4b6dad0804e6ad90f41aa","observation_id":"8357c133-8888-4122-8490-28d98e80e869","resolution":{"observed_at":"2026-08-15T14:37:33.782694Z","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":"2026-08-15T14:37:34.340598Z","title":"Corruption-robust exploration in episodic reinforcement learning","venue":null,"work_id":"4ae807cf-b012-45f8-92a1-db9ed14f49bf","year":2021},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.787584Z"},"links":{"citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:7b539657276f52284e1f0e7c8195152f6d67459bf91f827ab289f69f982b1401","observation_id":"ac97d750-468a-4be0-9da3-b23e5ac4f856","resolution":{"observed_at":"2026-08-15T14:37:34.345537Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T14:37:34.325368Z","title":"Online learning in unknown markov games","venue":null,"work_id":"4141515a-c502-4bec-af17-2bbcfddb92ff","year":2021},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.791927Z"},"links":{"citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:88276bc7fe3205162e4f970d5b9dd1f7b615d7fa5ac8965b426f98387e8f9a79","observation_id":"339d2c7d-9fd0-4023-bcbd-42bdabe2d8c1","resolution":{"observed_at":"2026-08-15T14:37:34.330508Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2602.07205","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T14:37:34.065979Z","title":"Online learning for uninformed markov games: Empirical nash-value regret and non-stationarity adaptation.arXiv preprint arXiv:2602.07205, 2026","venue":null,"work_id":"821c2f4f-6526-42fd-8132-36a85d0e9d13","year":2026},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.796344Z"},"links":{"citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:40c1b4c057d087bb15a9caec9c755359cc7c8927c1f6dc72923bafbd6b3e5e9e","observation_id":"34932280-870d-4464-9bf6-33cdbe34a823","resolution":{"observed_at":"2026-08-15T14:37:34.075438Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T14:37:34.309671Z","title":"Learning markov games with adversarial opponents: Efficient algorithms and fundamental limits","venue":null,"work_id":"a2e7b442-d028-4eae-aad9-e14b5fcead40","year":2022},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.800639Z"},"links":{"citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:b7d0d7727107bce6642e8fbb6105f5815d19f1cbba7b66bdd99575032153d7f1","observation_id":"ee648d7c-6abb-4396-b4f4-aa4e1331f232","resolution":{"observed_at":"2026-08-15T14:37:34.314437Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T14:37:34.295181Z","title":null,"venue":null,"work_id":"4f0ba201-e0b2-4246-8ffa-ee32463701bd","year":2024},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.804983Z"},"links":{"citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:dce9578c4bbd885b844fbeb172decf9a138c682ef2e4a86d0a6e227de7a5df09","observation_id":"d5ca4631-4a1e-48b8-80ee-2821317b84da","resolution":{"observed_at":"2026-08-15T14:37:34.299697Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T14:37:34.280203Z","title":"The maxmin value of stochastic games with imperfect monitoring.International journal of game theory, 32(1):133–150, 2003","venue":null,"work_id":"5ad0488e-3488-4215-bd8a-e63b9db9c848","year":2003},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.809513Z"},"links":{"citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:cf482c223e8721c1a0ee72b53dc832591ebdabc6825881411a2a7f872d0b93fa","observation_id":"26531244-f609-4e84-afd4-487d18fb677a","resolution":{"observed_at":"2026-08-15T14:37:34.284980Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T14:37:34.265262Z","title":"Sample-efficient reinforcement learning of partially observable markov games.Advances in Neural Information Processing Systems, 35:18296–18308, 2022","venue":null,"work_id":"1bfad730-b08c-4f01-8905-c11c1ab35ddd","year":2022},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.813487Z"},"links":{"citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:3a5e0f756c2b23d5ed517e8c2fa5a67d9cde6645832f557df03d87b8d5401730","observation_id":"6c398d7d-2595-482b-b3d2-516e3df4b8e7","resolution":{"observed_at":"2026-08-15T14:37:34.270242Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T14:37:34.249886Z","title":"Fictitious play in markov games with single controller","venue":null,"work_id":"fac23a9c-b461-4018-a7d7-5399dcf28d7a","year":2022},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.817620Z"},"links":{"citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:259f4c836c9ca6184dd3ace9142723f55fb36c45fc74e444fd4f4ef7f16c1ffd","observation_id":"53b36374-2399-49b8-9e26-86f8fc15e028","resolution":{"observed_at":"2026-08-15T14:37:34.254665Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T14:37:33.822070Z","title":"A finite-sample analysis of payoff-based independent learning in zero-sum stochastic games.Advances in Neural Information Processing Systems, 36:75826–75883, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.822070Z"},"links":{"citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:fe13dbd6b47e6552333883ea1a308bdeca4561fbffd0d021ef248e1035166a50","observation_id":"49afd8e0-d1a9-41e5-abfd-697278ab2e82","resolution":{"observed_at":"2026-08-15T14:37:33.822070Z","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":"2026-08-15T14:37:34.224201Z","title":"Learning in zero-sum markov games: Relaxing strong reachability and mixing time assumptions","venue":null,"work_id":"1352b50a-ebf3-420d-8e9a-db1bd11d4e27","year":2026},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.826585Z"},"links":{"citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:22df0a19d5ffbff58a2f09e1b197606d0ca29b5566516f5ce9eb34a050662de3","observation_id":"638e3427-04ea-463a-9a7b-4984e7e39ae6","resolution":{"observed_at":"2026-08-15T14:37:34.229442Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T14:37:34.208812Z","title":"Regret minimization and convergence to equilibria in general-sum markov games","venue":null,"work_id":"bb10b312-5e09-4440-b2bf-7b496cef8f39","year":2023},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.831067Z"},"links":{"citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:c455dc5a6fecba8abd71625bc4c664c808d7d59e6d10b9c569bdc3987a2151a1","observation_id":"8274ad05-902c-4c03-9463-ed4c06fb1009","resolution":{"observed_at":"2026-08-15T14:37:34.213544Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-15T14:37:33.835218Z","title":"HX h=1 Rh # ≤E ϖ,u⋆","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:33.835218Z"},"links":{"citing_paper":"/paper/2608.06520"},"observation_digest":"sha256:41d04e1fb90f0a6d1188e3e3b833bb16243c6e0cb421536d4e29ae5530d21e85","observation_id":"13b784d1-3b32-4a97-a0e1-f4c99bb116c8","resolution":{"observed_at":"2026-08-15T14:37:33.835218Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2608.06520","last_updated":"2026-08-06T19:03:49Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-15T14:29:51.638593Z","submitted_at":"2026-08-06T19:03:49Z","title":"Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks"},"reference_resolution":{"displayed":55,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":19,"verified_exact":2,"verified_fuzzy":34},"total_outbound_references":55},"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":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"thesis":"As of 17 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 0 inbound Pith citation observations for arXiv:2608.06520."}