{"as_of":"2026-08-10T12:07:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:c3f59b383f4f66632f067aba1c0c6d02a2acee0575c3158bd15520ae8b3328d6","coverage":[{"denominator":44,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":44,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T15:46:44.877182Z","state":"measured"},{"denominator":44,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":44,"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/2507.15067/citation-record","integrity":"/paper/2507.15067/integrity","json":"/paper/2507.15067/citation-record.json","paper":"/paper/2507.15067"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T15:46:44.727522Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.15067","last_updated":"2025-07-20T18:03:44Z","snapshot_observed_at":"2026-08-09T09:52:59.156741Z","submitted_at":"2025-07-20T18:03:44Z","title":"ROBAD: Robust Adversary-aware Local-Global Attended Bad Actor Detection Sequential Model","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T15:46:44.727522Z"},"links":{"citing_paper":"/paper/2507.15067"},"observation_digest":"sha256:083ba31e762d7f11bbfd0e6fad929c2147a6853818dd6b8e002ca6d780f181d7","observation_id":"35185e9e-0e71-431a-9d7e-836f79740a70","resolution":{"observed_at":"2026-08-06T15:46:44.727522Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2004.05150","last_updated":"2020-12-02T17:52:35Z","snapshot_observed_at":"2026-07-31T17:17:17.205582Z","submitted_at":"2020-04-10T17:54:09Z","title":"Longformer: The Long-Document Transformer","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2004.05150","snapshot_observed_at":"2026-08-06T15:46:44.731416Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2507.15067","last_updated":"2025-07-20T18:03:44Z","snapshot_observed_at":"2026-08-09T09:52:59.156741Z","submitted_at":"2025-07-20T18:03:44Z","title":"ROBAD: Robust Adversary-aware Local-Global Attended Bad Actor Detection Sequential Model","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T15:46:44.731416Z"},"links":{"cited_paper":"/paper/2004.05150","citing_paper":"/paper/2507.15067"},"observation_digest":"sha256:29350610cd70c308e63eac954b8707fef8c9e2aab74e1927c485998f47a91a04","observation_id":"de70bba0-7faa-4c0d-ab1f-9896a53a69d3","resolution":{"observed_at":"2026-08-06T15:46:44.731416Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1901.03407","last_updated":"2019-01-23T06:26:15Z","snapshot_observed_at":"2026-08-02T04:09:49.783205Z","submitted_at":"2019-01-10T21:36:57Z","title":"Deep Learning for Anomaly Detection: A Survey","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1901.03407","snapshot_observed_at":"2026-08-06T15:46:44.735248Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2507.15067","last_updated":"2025-07-20T18:03:44Z","snapshot_observed_at":"2026-08-09T09:52:59.156741Z","submitted_at":"2025-07-20T18:03:44Z","title":"ROBAD: Robust Adversary-aware Local-Global Attended Bad Actor Detection Sequential Model","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T15:46:44.735248Z"},"links":{"cited_paper":"/paper/1901.03407","citing_paper":"/paper/2507.15067"},"observation_digest":"sha256:20b8d9754df5bffe8d61bd6f2feda41757d2e1e16d0bee822ac6be2e062f94f1","observation_id":"777c48cb-d981-472c-a07e-c4a5e5f13f96","resolution":{"observed_at":"2026-08-06T15:46:44.735248Z","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":"2026-08-06T15:46:44.739012Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2507.15067","last_updated":"2025-07-20T18:03:44Z","snapshot_observed_at":"2026-08-09T09:52:59.156741Z","submitted_at":"2025-07-20T18:03:44Z","title":"ROBAD: Robust Adversary-aware Local-Global Attended Bad Actor Detection Sequential Model","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T15:46:44.739012Z"},"links":{"citing_paper":"/paper/2507.15067"},"observation_digest":"sha256:2900dc28dda810588777bd56de24e826ba2364601c07be89521a7d2d0eaba32e","observation_id":"13b4f792-57d4-407f-9664-fbd51bd212db","resolution":{"observed_at":"2026-08-06T15:46:44.739012Z","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":"2026-08-06T15:46:45.282611Z","title":null,"venue":null,"work_id":"4731d35d-58e9-4c66-b513-c965feae3d16","year":2019},"citing_paper":{"arxiv_id":"2507.15067","last_updated":"2025-07-20T18:03:44Z","snapshot_observed_at":"2026-08-09T09:52:59.156741Z","submitted_at":"2025-07-20T18:03:44Z","title":"ROBAD: Robust Adversary-aware Local-Global Attended Bad Actor Detection Sequential Model","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T15:46:44.742723Z"},"links":{"citing_paper":"/paper/2507.15067"},"observation_digest":"sha256:e912230eae26ac24a47af6e045dbf5538be8b73a046b1ff4ca085d64b7bf3144","observation_id":"93936f2d-b3b8-49fd-a13e-0823a49b7bd4","resolution":{"observed_at":"2026-08-06T15:46:45.286539Z","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":"2026-08-06T15:46:45.272774Z","title":null,"venue":null,"work_id":"ba475d7d-7e61-4088-9e31-eb39a7eb4675","year":2023},"citing_paper":{"arxiv_id":"2507.15067","last_updated":"2025-07-20T18:03:44Z","snapshot_observed_at":"2026-08-09T09:52:59.156741Z","submitted_at":"2025-07-20T18:03:44Z","title":"ROBAD: Robust Adversary-aware Local-Global Attended Bad Actor Detection Sequential Model","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T15:46:44.746138Z"},"links":{"citing_paper":"/paper/2507.15067"},"observation_digest":"sha256:6013983585b68f638cf41dc0073fa43752cff8c8885393eedfd8b984a4b95a70","observation_id":"54d234a0-3bf2-425a-9c00-079bca629b71","resolution":{"observed_at":"2026-08-06T15:46:45.276173Z","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":"2026-08-06T15:46:45.263342Z","title":null,"venue":null,"work_id":"1d71d0ca-fb27-41bf-b0ef-176aee69fe46","year":2022},"citing_paper":{"arxiv_id":"2507.15067","last_updated":"2025-07-20T18:03:44Z","snapshot_observed_at":"2026-08-09T09:52:59.156741Z","submitted_at":"2025-07-20T18:03:44Z","title":"ROBAD: Robust Adversary-aware Local-Global Attended Bad Actor Detection Sequential Model","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T15:46:44.750151Z"},"links":{"citing_paper":"/paper/2507.15067"},"observation_digest":"sha256:3b2a5cedf43827fade5773571daa538f8bb1eefb9ce9c4396c446d6af046efce","observation_id":"92f5aa6c-5c9d-4778-a5e5-6a7035c17160","resolution":{"observed_at":"2026-08-06T15:46:45.266460Z","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":{"arxiv_id":"1810.04805","last_updated":"2019-05-24T20:37:26Z","snapshot_observed_at":"2026-07-30T09:12:38.100527Z","submitted_at":"2018-10-11T00:50:01Z","title":"BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1810.04805","snapshot_observed_at":"2026-08-06T15:46:44.754284Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.15067","last_updated":"2025-07-20T18:03:44Z","snapshot_observed_at":"2026-08-09T09:52:59.156741Z","submitted_at":"2025-07-20T18:03:44Z","title":"ROBAD: Robust Adversary-aware Local-Global Attended Bad Actor Detection Sequential Model","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T15:46:44.754284Z"},"links":{"cited_paper":"/paper/1810.04805","citing_paper":"/paper/2507.15067"},"observation_digest":"sha256:e8eb9bb9b5c4ad703bfc37a9827d08a53e68e81849f95d79485d2394f605fb29","observation_id":"bd1b4697-80fd-4975-8d79-25817059ba8f","resolution":{"observed_at":"2026-08-06T15:46:44.754284Z","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":"2026-08-06T15:46:45.254335Z","title":null,"venue":null,"work_id":"db99b369-902e-4388-9d8f-63de5abfddf3","year":2020},"citing_paper":{"arxiv_id":"2507.15067","last_updated":"2025-07-20T18:03:44Z","snapshot_observed_at":"2026-08-09T09:52:59.156741Z","submitted_at":"2025-07-20T18:03:44Z","title":"ROBAD: Robust Adversary-aware Local-Global Attended Bad Actor Detection Sequential Model","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T15:46:44.758009Z"},"links":{"citing_paper":"/paper/2507.15067"},"observation_digest":"sha256:1f894e2208984457b34340b3818344325fa2b74ca38c324ca58cad25c4ff12ce","observation_id":"e21c752e-3e48-4f1b-8a8a-08a7a41395e4","resolution":{"observed_at":"2026-08-06T15:46:45.257378Z","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":"2026-08-06T15:46:45.245635Z","title":null,"venue":null,"work_id":"8ced86e3-5dab-4562-a00c-a3d9edcdb387","year":2020},"citing_paper":{"arxiv_id":"2507.15067","last_updated":"2025-07-20T18:03:44Z","snapshot_observed_at":"2026-08-09T09:52:59.156741Z","submitted_at":"2025-07-20T18:03:44Z","title":"ROBAD: Robust Adversary-aware Local-Global Attended Bad Actor Detection Sequential Model","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T15:46:44.762216Z"},"links":{"citing_paper":"/paper/2507.15067"},"observation_digest":"sha256:c57c93068b70cb3183a11757193ffafd22bfebda4b13f8f8d0bdb43c71f3985a","observation_id":"709c8b59-be63-44be-94fb-08d771d53325","resolution":{"observed_at":"2026-08-06T15:46:45.248526Z","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":"2026-08-06T15:46:45.236535Z","title":null,"venue":null,"work_id":"fb1573e8-8b1e-4d2e-94d6-3d6e9ad214c0","year":2017},"citing_paper":{"arxiv_id":"2507.15067","last_updated":"2025-07-20T18:03:44Z","snapshot_observed_at":"2026-08-09T09:52:59.156741Z","submitted_at":"2025-07-20T18:03:44Z","title":"ROBAD: Robust Adversary-aware Local-Global Attended Bad Actor Detection Sequential Model","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T15:46:44.766232Z"},"links":{"citing_paper":"/paper/2507.15067"},"observation_digest":"sha256:4761aca9c734a90366270e5467d98f408aafd7b8b08483073d5696d6b615c958","observation_id":"345c5ee6-03a1-4722-94c6-b528d8a56721","resolution":{"observed_at":"2026-08-06T15:46:45.239419Z","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":"2026-08-06T15:46:45.227641Z","title":null,"venue":null,"work_id":"35e82949-5743-4b5c-ace5-49ba84a904db","year":2023},"citing_paper":{"arxiv_id":"2507.15067","last_updated":"2025-07-20T18:03:44Z","snapshot_observed_at":"2026-08-09T09:52:59.156741Z","submitted_at":"2025-07-20T18:03:44Z","title":"ROBAD: Robust Adversary-aware Local-Global Attended Bad Actor Detection Sequential Model","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T15:46:44.769494Z"},"links":{"citing_paper":"/paper/2507.15067"},"observation_digest":"sha256:74fe3a33e0c727dbb896196b7b6ed85748fb1d52ce6209307a4a5793eaa97e00","observation_id":"2ac9f41c-3696-4826-8f38-19e7cefb3a63","resolution":{"observed_at":"2026-08-06T15:46:45.230692Z","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":{"arxiv_id":"1412.6572","last_updated":"2015-03-20T20:19:16Z","snapshot_observed_at":"2026-07-06T04:04:16.777653Z","submitted_at":"2014-12-20T01:17:12Z","title":"Explaining and Harnessing Adversarial Examples","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1412.6572","snapshot_observed_at":"2026-08-06T15:46:44.772834Z","title":null,"venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2507.15067","last_updated":"2025-07-20T18:03:44Z","snapshot_observed_at":"2026-08-09T09:52:59.156741Z","submitted_at":"2025-07-20T18:03:44Z","title":"ROBAD: Robust Adversary-aware Local-Global Attended Bad Actor Detection Sequential Model","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T15:46:44.772834Z"},"links":{"cited_paper":"/paper/1412.6572","citing_paper":"/paper/2507.15067"},"observation_digest":"sha256:f1300d501406fca8c1eef26defb7eb9ebb140faecf8f7f3462ba79ef853b9c29","observation_id":"d7919f2a-4bbd-4b20-86e1-cd925c601ed4","resolution":{"observed_at":"2026-08-06T15:46:44.772834Z","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":"2026-08-06T15:46:45.219003Z","title":null,"venue":null,"work_id":"4ba98ddc-e9f7-4ed5-b0b6-924ebb26b2dc","year":2021},"citing_paper":{"arxiv_id":"2507.15067","last_updated":"2025-07-20T18:03:44Z","snapshot_observed_at":"2026-08-09T09:52:59.156741Z","submitted_at":"2025-07-20T18:03:44Z","title":"ROBAD: Robust Adversary-aware Local-Global Attended Bad Actor Detection Sequential Model","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T15:46:44.776362Z"},"links":{"citing_paper":"/paper/2507.15067"},"observation_digest":"sha256:229510c16c7c7ffa4c30cee4cd63a40f8e78740001cb610e15db0caef2d845a4","observation_id":"58669ca3-02a5-45f2-a5ed-8f8a7e53035a","resolution":{"observed_at":"2026-08-06T15:46:45.221936Z","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":"2026-08-06T15:46:45.209908Z","title":null,"venue":null,"work_id":"ed6038b4-0621-478b-91e8-46ce86ceecb2","year":2020},"citing_paper":{"arxiv_id":"2507.15067","last_updated":"2025-07-20T18:03:44Z","snapshot_observed_at":"2026-08-09T09:52:59.156741Z","submitted_at":"2025-07-20T18:03:44Z","title":"ROBAD: Robust Adversary-aware Local-Global Attended Bad Actor Detection Sequential Model","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T15:46:44.779308Z"},"links":{"citing_paper":"/paper/2507.15067"},"observation_digest":"sha256:467d67b6ce584e60be7861bf48fba30cdea3b93c4437a2b436bb2597d3fb15f4","observation_id":"95290f96-3ea7-4c9c-9880-fea2a4bd53f7","resolution":{"observed_at":"2026-08-06T15:46:45.213406Z","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":"2026-08-06T15:46:45.200336Z","title":null,"venue":null,"work_id":"3a6a737f-4b8c-4d66-bf7a-5bcde2d5f2ac","year":2017},"citing_paper":{"arxiv_id":"2507.15067","last_updated":"2025-07-20T18:03:44Z","snapshot_observed_at":"2026-08-09T09:52:59.156741Z","submitted_at":"2025-07-20T18:03:44Z","title":"ROBAD: Robust Adversary-aware Local-Global Attended Bad Actor Detection Sequential Model","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T15:46:44.782560Z"},"links":{"citing_paper":"/paper/2507.15067"},"observation_digest":"sha256:d451c4ab39e2544bd94c3b486527fb1edb64691dda7b5222c581b4dd48a821cb","observation_id":"bdf19dad-703c-46ba-ad78-a2c75bda8640","resolution":{"observed_at":"2026-08-06T15:46:45.204038Z","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":"2026-08-06T15:46:45.190649Z","title":null,"venue":null,"work_id":"4eafce81-ce8f-4c42-b4bb-d5efd82025e5","year":2019},"citing_paper":{"arxiv_id":"2507.15067","last_updated":"2025-07-20T18:03:44Z","snapshot_observed_at":"2026-08-09T09:52:59.156741Z","submitted_at":"2025-07-20T18:03:44Z","title":"ROBAD: Robust Adversary-aware Local-Global Attended Bad Actor Detection Sequential Model","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T15:46:44.785622Z"},"links":{"citing_paper":"/paper/2507.15067"},"observation_digest":"sha256:d011c0546897650f4aa2a7b67dda3d550fdabe56062d36f3ee96c50c5263f1d0","observation_id":"293dd3fc-3332-4500-89f4-219c26b8388a","resolution":{"observed_at":"2026-08-06T15:46:45.194365Z","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":{"arxiv_id":"1412.6980","last_updated":"2017-01-30T01:27:54Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2014-12-22T13:54:29Z","title":"Adam: A Method for Stochastic Optimization","version":9},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1412.6980","snapshot_observed_at":"2026-08-06T15:46:44.788921Z","title":null,"venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2507.15067","last_updated":"2025-07-20T18:03:44Z","snapshot_observed_at":"2026-08-09T09:52:59.156741Z","submitted_at":"2025-07-20T18:03:44Z","title":"ROBAD: Robust Adversary-aware Local-Global Attended Bad Actor Detection Sequential Model","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T15:46:44.788921Z"},"links":{"cited_paper":"/paper/1412.6980","citing_paper":"/paper/2507.15067"},"observation_digest":"sha256:b2454d9309109f0f00b813ef42a76fdfd1a57f0d38a3671d3449b3ef096747d6","observation_id":"c3fb9fe9-4fb5-429d-a967-8a90468b814d","resolution":{"observed_at":"2026-08-06T15:46:44.788921Z","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":"2026-08-06T15:46:45.180573Z","title":null,"venue":null,"work_id":"e38bec3e-475b-4cea-b094-92d38fec419e","year":2017},"citing_paper":{"arxiv_id":"2507.15067","last_updated":"2025-07-20T18:03:44Z","snapshot_observed_at":"2026-08-09T09:52:59.156741Z","submitted_at":"2025-07-20T18:03:44Z","title":"ROBAD: Robust Adversary-aware Local-Global Attended Bad Actor Detection Sequential Model","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T15:46:44.792275Z"},"links":{"citing_paper":"/paper/2507.15067"},"observation_digest":"sha256:0464e5dd6ee8ae335759617e89b63cb470b247ec01e549d578f104823d399f0f","observation_id":"795cb226-b3f6-4deb-96d2-255dc30b8598","resolution":{"observed_at":"2026-08-06T15:46:45.183984Z","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":"2026-08-06T15:46:45.170912Z","title":null,"venue":null,"work_id":"448aef39-5121-41fd-acec-ca05fbfeebfe","year":2018},"citing_paper":{"arxiv_id":"2507.15067","last_updated":"2025-07-20T18:03:44Z","snapshot_observed_at":"2026-08-09T09:52:59.156741Z","submitted_at":"2025-07-20T18:03:44Z","title":"ROBAD: Robust Adversary-aware Local-Global Attended Bad Actor Detection Sequential Model","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T15:46:44.795423Z"},"links":{"citing_paper":"/paper/2507.15067"},"observation_digest":"sha256:56da97750042fd90ccc24defb39b5c2a5420c93356edb754570aa4c9307a6574","observation_id":"3b90adae-8621-457a-ae4b-1d39b7db7b0c","resolution":{"observed_at":"2026-08-06T15:46:45.174145Z","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":"2026-08-06T15:46:45.160932Z","title":"Subrahmanian","venue":null,"work_id":"d2794630-7aa5-45c3-b945-98cd0cd26e21","year":2015},"citing_paper":{"arxiv_id":"2507.15067","last_updated":"2025-07-20T18:03:44Z","snapshot_observed_at":"2026-08-09T09:52:59.156741Z","submitted_at":"2025-07-20T18:03:44Z","title":"ROBAD: Robust Adversary-aware Local-Global Attended Bad Actor Detection Sequential Model","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T15:46:44.798936Z"},"links":{"citing_paper":"/paper/2507.15067"},"observation_digest":"sha256:db849a7abe4b7b40264470c61830d617d17a53d5545a95080b3c93698402a285","observation_id":"bd0509ca-23a7-4c6c-8235-a51b85501515","resolution":{"observed_at":"2026-08-06T15:46:45.164405Z","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":"2026-08-06T15:46:45.150231Z","title":"Leskovec","venue":null,"work_id":"56503863-21f1-4352-94f4-4b4d231f8eee","year":2019},"citing_paper":{"arxiv_id":"2507.15067","last_updated":"2025-07-20T18:03:44Z","snapshot_observed_at":"2026-08-09T09:52:59.156741Z","submitted_at":"2025-07-20T18:03:44Z","title":"ROBAD: Robust Adversary-aware Local-Global Attended Bad Actor Detection Sequential Model","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T15:46:44.802383Z"},"links":{"citing_paper":"/paper/2507.15067"},"observation_digest":"sha256:d6bc50e547fa6368957000dce36cb0133f1145f2d543b88294d59aae170009eb","observation_id":"36fc08ed-edd4-40eb-a700-8fe0c64b567a","resolution":{"observed_at":"2026-08-06T15:46:45.153894Z","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":"2026-08-06T15:46:45.140060Z","title":null,"venue":null,"work_id":"88cb962b-511e-4a35-aedd-2c1aedd574bc","year":2020},"citing_paper":{"arxiv_id":"2507.15067","last_updated":"2025-07-20T18:03:44Z","snapshot_observed_at":"2026-08-09T09:52:59.156741Z","submitted_at":"2025-07-20T18:03:44Z","title":"ROBAD: Robust Adversary-aware Local-Global Attended Bad Actor Detection Sequential Model","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T15:46:44.805740Z"},"links":{"citing_paper":"/paper/2507.15067"},"observation_digest":"sha256:8e334676a35a8325d09b9effdd2ef232abfa5b761b560d2800e23dd1199231e0","observation_id":"62ad895a-edf6-478e-a4a2-c7dddd220908","resolution":{"observed_at":"2026-08-06T15:46:45.143534Z","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":"2026-08-06T15:46:45.129685Z","title":null,"venue":null,"work_id":"7d34fa9c-0b26-4ac0-99d4-9e2f394d7acc","year":2016},"citing_paper":{"arxiv_id":"2507.15067","last_updated":"2025-07-20T18:03:44Z","snapshot_observed_at":"2026-08-09T09:52:59.156741Z","submitted_at":"2025-07-20T18:03:44Z","title":"ROBAD: Robust Adversary-aware Local-Global Attended Bad Actor Detection Sequential Model","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T15:46:44.809065Z"},"links":{"citing_paper":"/paper/2507.15067"},"observation_digest":"sha256:143343b1078832e1006fb43eb02edfeef248961e9fffe385a4626518048dee58","observation_id":"00a4ee17-d27b-492c-a827-3363d22ff399","resolution":{"observed_at":"2026-08-06T15:46:45.133346Z","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":"2026-08-06T15:46:45.118478Z","title":null,"venue":null,"work_id":"dacae71d-5faf-4217-be09-987c77c81049","year":2018},"citing_paper":{"arxiv_id":"2507.15067","last_updated":"2025-07-20T18:03:44Z","snapshot_observed_at":"2026-08-09T09:52:59.156741Z","submitted_at":"2025-07-20T18:03:44Z","title":"ROBAD: Robust Adversary-aware Local-Global Attended Bad Actor Detection Sequential Model","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T15:46:44.812250Z"},"links":{"citing_paper":"/paper/2507.15067"},"observation_digest":"sha256:e06eada4652e9ec548fbfff0f0d1dbab407d6991ef303f4f64108253dbcb01c7","observation_id":"bd8a9f8d-77bb-40b8-84cd-c769cb33e5b2","resolution":{"observed_at":"2026-08-06T15:46:45.122102Z","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":{"arxiv_id":"1901.11504","last_updated":"2019-05-30T00:01:20Z","snapshot_observed_at":"2026-07-06T07:30:20.997518Z","submitted_at":"2019-01-31T18:07:25Z","title":"Multi-Task Deep Neural Networks for Natural Language Understanding","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1901.11504","snapshot_observed_at":"2026-08-06T15:46:44.815620Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2507.15067","last_updated":"2025-07-20T18:03:44Z","snapshot_observed_at":"2026-08-09T09:52:59.156741Z","submitted_at":"2025-07-20T18:03:44Z","title":"ROBAD: Robust Adversary-aware Local-Global Attended Bad Actor Detection Sequential Model","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T15:46:44.815620Z"},"links":{"cited_paper":"/paper/1901.11504","citing_paper":"/paper/2507.15067"},"observation_digest":"sha256:f6ee01f6c42b337e2acf12f1b2dbbe913010692b807e9c0314bfa3d62f816aaa","observation_id":"6f08d134-1994-4838-a5ac-68bccb243035","resolution":{"observed_at":"2026-08-06T15:46:44.815620Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1605.07725","last_updated":"2021-11-16T07:16:21Z","snapshot_observed_at":"2026-08-03T15:04:24.910065Z","submitted_at":"2016-05-25T04:25:45Z","title":"Adversarial Training Methods for Semi-Supervised Text Classification","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1605.07725","snapshot_observed_at":"2026-08-06T15:46:44.819791Z","title":null,"venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2507.15067","last_updated":"2025-07-20T18:03:44Z","snapshot_observed_at":"2026-08-09T09:52:59.156741Z","submitted_at":"2025-07-20T18:03:44Z","title":"ROBAD: Robust Adversary-aware Local-Global Attended Bad Actor Detection Sequential Model","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T15:46:44.819791Z"},"links":{"cited_paper":"/paper/1605.07725","citing_paper":"/paper/2507.15067"},"observation_digest":"sha256:13bffc38c719ba285a2537ff3ec6d27e90b46e91247cba9df9b706ce3a0dc672","observation_id":"03dd8a4f-ba1a-4827-9836-65fce42644f9","resolution":{"observed_at":"2026-08-06T15:46:44.819791Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2005.05909","last_updated":"2020-10-05T00:10:24Z","snapshot_observed_at":"2026-08-05T07:11:54.244493Z","submitted_at":"2020-04-29T21:33:35Z","title":"TextAttack: A Framework for Adversarial Attacks, Data Augmentation, and Adversarial Training in NLP","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2005.05909","snapshot_observed_at":"2026-08-06T15:46:44.823362Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2507.15067","last_updated":"2025-07-20T18:03:44Z","snapshot_observed_at":"2026-08-09T09:52:59.156741Z","submitted_at":"2025-07-20T18:03:44Z","title":"ROBAD: Robust Adversary-aware Local-Global Attended Bad Actor Detection Sequential Model","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T15:46:44.823362Z"},"links":{"cited_paper":"/paper/2005.05909","citing_paper":"/paper/2507.15067"},"observation_digest":"sha256:22023d826f145ea2e75587b337c0230a6dd2583acb03c4ee3c057f0d6d4a201b","observation_id":"90d3897a-c5a1-4268-b98c-e8fea1bffea5","resolution":{"observed_at":"2026-08-06T15:46:44.823362Z","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":"2026-08-06T15:46:45.107151Z","title":null,"venue":null,"work_id":"e296095c-7382-4889-9f29-cfb0221e7654","year":2018},"citing_paper":{"arxiv_id":"2507.15067","last_updated":"2025-07-20T18:03:44Z","snapshot_observed_at":"2026-08-09T09:52:59.156741Z","submitted_at":"2025-07-20T18:03:44Z","title":"ROBAD: Robust Adversary-aware Local-Global Attended Bad Actor Detection Sequential Model","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T15:46:44.827611Z"},"links":{"citing_paper":"/paper/2507.15067"},"observation_digest":"sha256:db0e1093f1c8006b92be6b2b899738106fdf90877a36b4ac2df99e2aaa1e0012","observation_id":"4dbc47fe-f2e9-464c-b6de-fa16d6eb9c7d","resolution":{"observed_at":"2026-08-06T15:46:45.110563Z","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":"2026-08-06T15:46:45.097260Z","title":null,"venue":null,"work_id":"927c39fb-e41b-4a3d-ba13-8a38b3678b63","year":2020},"citing_paper":{"arxiv_id":"2507.15067","last_updated":"2025-07-20T18:03:44Z","snapshot_observed_at":"2026-08-09T09:52:59.156741Z","submitted_at":"2025-07-20T18:03:44Z","title":"ROBAD: Robust Adversary-aware Local-Global Attended Bad Actor Detection Sequential Model","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T15:46:44.830870Z"},"links":{"citing_paper":"/paper/2507.15067"},"observation_digest":"sha256:08abee17e282a8e836906b77f85e0226affbde18bdf5e48c431f9edc34e86643","observation_id":"ec3a9002-804a-4b1c-9c4b-916a3ec54de6","resolution":{"observed_at":"2026-08-06T15:46:45.100641Z","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":{"arxiv_id":"1807.03748","last_updated":"2019-01-22T18:47:12Z","snapshot_observed_at":"2026-07-06T06:49:24.960992Z","submitted_at":"2018-07-10T16:52:11Z","title":"Representation Learning with Contrastive Predictive Coding","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1807.03748","snapshot_observed_at":"2026-08-06T15:46:44.834153Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.15067","last_updated":"2025-07-20T18:03:44Z","snapshot_observed_at":"2026-08-09T09:52:59.156741Z","submitted_at":"2025-07-20T18:03:44Z","title":"ROBAD: Robust Adversary-aware Local-Global Attended Bad Actor Detection Sequential Model","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T15:46:44.834153Z"},"links":{"cited_paper":"/paper/1807.03748","citing_paper":"/paper/2507.15067"},"observation_digest":"sha256:ab6d003faa028126de5ceff40618fec9ba1dc4c2efa731f22c6b275022ebb8fe","observation_id":"754de7d1-4d05-4a70-860a-70fdd496030f","resolution":{"observed_at":"2026-08-06T15:46:44.834153Z","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":"2026-08-06T15:46:45.087438Z","title":null,"venue":null,"work_id":"66d69045-a5b3-46c5-8d88-773afb9578a6","year":2019},"citing_paper":{"arxiv_id":"2507.15067","last_updated":"2025-07-20T18:03:44Z","snapshot_observed_at":"2026-08-09T09:52:59.156741Z","submitted_at":"2025-07-20T18:03:44Z","title":"ROBAD: Robust Adversary-aware Local-Global Attended Bad Actor Detection Sequential Model","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T15:46:44.837681Z"},"links":{"citing_paper":"/paper/2507.15067"},"observation_digest":"sha256:0fec46ba5d49d9f978ea1a97b52d1d53d4ec542c069ef509ba5b1741a4abaa98","observation_id":"414b6077-7683-44d9-852a-bb05705bf362","resolution":{"observed_at":"2026-08-06T15:46:45.090936Z","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":"2026-08-06T15:46:45.077709Z","title":null,"venue":null,"work_id":"51264db3-30ff-4581-829f-4ae6a5595b3a","year":2015},"citing_paper":{"arxiv_id":"2507.15067","last_updated":"2025-07-20T18:03:44Z","snapshot_observed_at":"2026-08-09T09:52:59.156741Z","submitted_at":"2025-07-20T18:03:44Z","title":"ROBAD: Robust Adversary-aware Local-Global Attended Bad Actor Detection Sequential Model","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T15:46:44.840957Z"},"links":{"citing_paper":"/paper/2507.15067"},"observation_digest":"sha256:f7b2bbaefa4be7cb55ec9f89d6210d78c045bf7809e439216452d52695b77824","observation_id":"d4fab460-704c-4a0b-8a7d-b539f171a1fb","resolution":{"observed_at":"2026-08-06T15:46:45.081172Z","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":{"arxiv_id":"1805.06605","last_updated":"2018-05-18T00:20:52Z","snapshot_observed_at":"2026-08-02T06:44:56.184651Z","submitted_at":"2018-05-17T05:38:55Z","title":"Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using Generative Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1805.06605","snapshot_observed_at":"2026-08-06T15:46:44.845052Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.15067","last_updated":"2025-07-20T18:03:44Z","snapshot_observed_at":"2026-08-09T09:52:59.156741Z","submitted_at":"2025-07-20T18:03:44Z","title":"ROBAD: Robust Adversary-aware Local-Global Attended Bad Actor Detection Sequential Model","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-06T15:46:44.845052Z"},"links":{"cited_paper":"/paper/1805.06605","citing_paper":"/paper/2507.15067"},"observation_digest":"sha256:f49ca3b4d9c087ce285cfe3a05aaa1f9afff19b6cf54e0c9dcb73742df17f1fc","observation_id":"b0d444f1-3e91-4ebc-b483-556f5b3ab042","resolution":{"observed_at":"2026-08-06T15:46:44.845052Z","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":"2026-08-06T15:46:45.067379Z","title":null,"venue":null,"work_id":"05391964-4637-4b4b-b0db-905594499439","year":2017},"citing_paper":{"arxiv_id":"2507.15067","last_updated":"2025-07-20T18:03:44Z","snapshot_observed_at":"2026-08-09T09:52:59.156741Z","submitted_at":"2025-07-20T18:03:44Z","title":"ROBAD: Robust Adversary-aware Local-Global Attended Bad Actor Detection Sequential Model","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-06T15:46:44.848513Z"},"links":{"citing_paper":"/paper/2507.15067"},"observation_digest":"sha256:4f97214d86f06d93f1ea8edf04c37d8723b00a933bc3bd391fa638c619b2bf59","observation_id":"c0e24c91-9e87-407e-b045-7c93ac1828c0","resolution":{"observed_at":"2026-08-06T15:46:45.070803Z","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":{"arxiv_id":"2307.09288","last_updated":"2023-07-19T17:08:59Z","snapshot_observed_at":"2026-08-07T12:56:43.323460Z","submitted_at":"2023-07-18T14:31:57Z","title":"Llama 2: Open Foundation and Fine-Tuned Chat Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.09288","snapshot_observed_at":"2026-08-06T15:46:44.851458Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.15067","last_updated":"2025-07-20T18:03:44Z","snapshot_observed_at":"2026-08-09T09:52:59.156741Z","submitted_at":"2025-07-20T18:03:44Z","title":"ROBAD: Robust Adversary-aware Local-Global Attended Bad Actor Detection Sequential Model","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-06T15:46:44.851458Z"},"links":{"cited_paper":"/paper/2307.09288","citing_paper":"/paper/2507.15067"},"observation_digest":"sha256:f992c72e82d453e1be8f1b2fa095d7a67f1beb450ff6d9e027eb9f2d75062c1f","observation_id":"9832bbed-c821-4fdb-991f-dfd167274f06","resolution":{"observed_at":"2026-08-06T15:46:44.851458Z","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":"2026-08-06T15:46:44.854906Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.15067","last_updated":"2025-07-20T18:03:44Z","snapshot_observed_at":"2026-08-09T09:52:59.156741Z","submitted_at":"2025-07-20T18:03:44Z","title":"ROBAD: Robust Adversary-aware Local-Global Attended Bad Actor Detection Sequential Model","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-06T15:46:44.854906Z"},"links":{"citing_paper":"/paper/2507.15067"},"observation_digest":"sha256:8404c9fab5fb097d38140bb64256b3ed7303721362524e49c2fe01c437677ec8","observation_id":"b29721d7-479b-4462-9d08-0a7b886d9f01","resolution":{"observed_at":"2026-08-06T15:46:44.854906Z","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":"2026-08-06T15:46:45.051373Z","title":null,"venue":null,"work_id":"e6818d35-62c8-40d7-993a-6dea0405ec1f","year":2019},"citing_paper":{"arxiv_id":"2507.15067","last_updated":"2025-07-20T18:03:44Z","snapshot_observed_at":"2026-08-09T09:52:59.156741Z","submitted_at":"2025-07-20T18:03:44Z","title":"ROBAD: Robust Adversary-aware Local-Global Attended Bad Actor Detection Sequential Model","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-06T15:46:44.857973Z"},"links":{"citing_paper":"/paper/2507.15067"},"observation_digest":"sha256:2eb8ab308aed0a5d62eae9b334fe6aea1ea2db659d6d5eb049dfde5cfe584052","observation_id":"ef8e0153-1eaf-458a-8089-d37cf3ab9c99","resolution":{"observed_at":"2026-08-06T15:46:45.054699Z","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":"2026-08-06T15:46:45.041915Z","title":null,"venue":null,"work_id":"b684fc3c-f101-4ecb-9523-bf84c4a7dc50","year":2021},"citing_paper":{"arxiv_id":"2507.15067","last_updated":"2025-07-20T18:03:44Z","snapshot_observed_at":"2026-08-09T09:52:59.156741Z","submitted_at":"2025-07-20T18:03:44Z","title":"ROBAD: Robust Adversary-aware Local-Global Attended Bad Actor Detection Sequential Model","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-06T15:46:44.861076Z"},"links":{"citing_paper":"/paper/2507.15067"},"observation_digest":"sha256:c472b4bb1f54966fdfb1609cf8db57d1b65821627992834d8e5379159ed2836a","observation_id":"286544c5-6d47-490a-9d3b-65f8b1686fad","resolution":{"observed_at":"2026-08-06T15:46:45.045161Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T15:46:44.864252Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.15067","last_updated":"2025-07-20T18:03:44Z","snapshot_observed_at":"2026-08-09T09:52:59.156741Z","submitted_at":"2025-07-20T18:03:44Z","title":"ROBAD: Robust Adversary-aware Local-Global Attended Bad Actor Detection Sequential Model","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-06T15:46:44.864252Z"},"links":{"citing_paper":"/paper/2507.15067"},"observation_digest":"sha256:5297ad50e55b9ab05af39941b5e1d139d8b8defb396ec8534762ddddece4989b","observation_id":"b1ccbc00-6d62-4d94-9ea8-c253bfa1ffd9","resolution":{"observed_at":"2026-08-06T15:46:44.864252Z","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":"2026-08-06T15:46:45.026263Z","title":null,"venue":null,"work_id":"254c720a-8c8f-4907-9082-3cd6f5333669","year":2016},"citing_paper":{"arxiv_id":"2507.15067","last_updated":"2025-07-20T18:03:44Z","snapshot_observed_at":"2026-08-09T09:52:59.156741Z","submitted_at":"2025-07-20T18:03:44Z","title":"ROBAD: Robust Adversary-aware Local-Global Attended Bad Actor Detection Sequential Model","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-06T15:46:44.867215Z"},"links":{"citing_paper":"/paper/2507.15067"},"observation_digest":"sha256:1c5abbc53a80cf5109ceb33571c0e2760b67589c6a27ee50fd8011770f80d04d","observation_id":"0b7d44b2-b10b-473e-aa84-0f7864296137","resolution":{"observed_at":"2026-08-06T15:46:45.029654Z","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":{"arxiv_id":"1710.09412","last_updated":"2018-04-27T21:39:25Z","snapshot_observed_at":"2026-08-08T10:28:19.597631Z","submitted_at":"2017-10-25T18:30:49Z","title":"mixup: Beyond Empirical Risk Minimization","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1710.09412","snapshot_observed_at":"2026-08-06T15:46:44.870370Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.15067","last_updated":"2025-07-20T18:03:44Z","snapshot_observed_at":"2026-08-09T09:52:59.156741Z","submitted_at":"2025-07-20T18:03:44Z","title":"ROBAD: Robust Adversary-aware Local-Global Attended Bad Actor Detection Sequential Model","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-06T15:46:44.870370Z"},"links":{"cited_paper":"/paper/1710.09412","citing_paper":"/paper/2507.15067"},"observation_digest":"sha256:f110884d37dd0fd2152f0a27a43c07076c082118a525f227fe5392626dd6e7df","observation_id":"4adff9a7-abb2-4601-be3a-3439f40df015","resolution":{"observed_at":"2026-08-06T15:46:44.870370Z","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":"2026-08-06T15:46:45.016670Z","title":null,"venue":null,"work_id":"ed7bb6bc-e48b-4f6d-8c64-9faf91e72756","year":2020},"citing_paper":{"arxiv_id":"2507.15067","last_updated":"2025-07-20T18:03:44Z","snapshot_observed_at":"2026-08-09T09:52:59.156741Z","submitted_at":"2025-07-20T18:03:44Z","title":"ROBAD: Robust Adversary-aware Local-Global Attended Bad Actor Detection Sequential Model","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-06T15:46:44.874064Z"},"links":{"citing_paper":"/paper/2507.15067"},"observation_digest":"sha256:ffb730391c60ce1292a622cc1a86c1404f94661b5266b3c85f589fd485b2e094","observation_id":"4f27ca59-a163-44de-8376-55e4c26900c0","resolution":{"observed_at":"2026-08-06T15:46:45.020084Z","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":"2026-08-06T15:46:45.006275Z","title":null,"venue":null,"work_id":"4b63da50-55f8-471d-b7e0-9235af7c25da","year":2019},"citing_paper":{"arxiv_id":"2507.15067","last_updated":"2025-07-20T18:03:44Z","snapshot_observed_at":"2026-08-09T09:52:59.156741Z","submitted_at":"2025-07-20T18:03:44Z","title":"ROBAD: Robust Adversary-aware Local-Global Attended Bad Actor Detection Sequential Model","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-06T15:46:44.877182Z"},"links":{"citing_paper":"/paper/2507.15067"},"observation_digest":"sha256:0f8e4a9c4eddf53f9149dd857eb45307bdae6dd7dd8d8ed16755a73f15a15e9f","observation_id":"d6c0bb70-9c7f-453d-b84c-d2b0743d40af","resolution":{"observed_at":"2026-08-06T15:46:45.010211Z","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"}}],"paper":{"arxiv_id":"2507.15067","last_updated":"2025-07-20T18:03:44Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-09T09:52:59.156741Z","submitted_at":"2025-07-20T18:03:44Z","title":"ROBAD: Robust Adversary-aware Local-Global Attended Bad Actor Detection Sequential Model"},"reference_resolution":{"displayed":44,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":42,"verified_exact":0,"verified_fuzzy":2},"total_outbound_references":44},"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 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2507.15067."}