{"as_of":"2026-08-13T06:43:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:dee2f0f395c8fb1d9c2f91618cec8cf51bfa0cbc572251ac1ef200682190bf77","coverage":[{"denominator":48,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":48,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-11T23:32:37.500348Z","state":"measured"},{"denominator":48,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":48,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-13T06:32:02.005865+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/2412.02454/citation-record","integrity":"/paper/2412.02454/integrity","json":"/paper/2412.02454/citation-record.json","paper":"/paper/2412.02454"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:32:37.200536Z","title":null,"venue":null,"work_id":null,"year":1974},"citing_paper":{"arxiv_id":"2412.02454","last_updated":"2024-12-03T13:43:36Z","snapshot_observed_at":"2026-08-12T09:38:28.587555Z","submitted_at":"2024-12-03T13:43:36Z","title":"Gracefully Filtering Backdoor Samples for Generative Large Language Models without Retraining","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-11T23:32:37.200536Z"},"links":{"citing_paper":"/paper/2412.02454"},"observation_digest":"sha256:c226b94c14fcab5b9e9c1f8b4aa2e5124c91a5a05b12354cdab128e14fdb32e1","observation_id":"c64c3ff6-063c-486b-b079-47d3102e06d2","resolution":{"observed_at":"2026-08-11T23:32:37.200536Z","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":"2026-08-11T23:32:39.018379Z","title":null,"venue":null,"work_id":"1ff8892d-61b2-49b8-a3fe-32522a220b83","year":2024},"citing_paper":{"arxiv_id":"2412.02454","last_updated":"2024-12-03T13:43:36Z","snapshot_observed_at":"2026-08-12T09:38:28.587555Z","submitted_at":"2024-12-03T13:43:36Z","title":"Gracefully Filtering Backdoor Samples for Generative Large Language Models without Retraining","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-11T23:32:37.208019Z"},"links":{"citing_paper":"/paper/2412.02454"},"observation_digest":"sha256:9a3c24f930068505bb79de912e1188e1fb76e53ef15d9ca38f79443b95630bbc","observation_id":"f88305e7-1bfc-42c7-9062-90101f43e943","resolution":{"observed_at":"2026-08-11T23:32:39.023444Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-11T23:32:39.000919Z","title":null,"venue":null,"work_id":"db77f87d-dd3e-4d19-88de-24e1cdae4f8e","year":2013},"citing_paper":{"arxiv_id":"2412.02454","last_updated":"2024-12-03T13:43:36Z","snapshot_observed_at":"2026-08-12T09:38:28.587555Z","submitted_at":"2024-12-03T13:43:36Z","title":"Gracefully Filtering Backdoor Samples for Generative Large Language Models without Retraining","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-11T23:32:37.214359Z"},"links":{"citing_paper":"/paper/2412.02454"},"observation_digest":"sha256:bf99557707b20f0384872b5f10540f2fe2b1fb1ccc948f41699955e2442cb1b7","observation_id":"9a12e4bf-1b98-4ffb-b398-d45585505fc0","resolution":{"observed_at":"2026-08-11T23:32:39.005999Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1016/j.neucom.2021.04.105","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:32:38.013107Z","title":null,"venue":null,"work_id":"5144f7b6-eb16-47fd-92bd-a9ac0383185a","year":2021},"citing_paper":{"arxiv_id":"2412.02454","last_updated":"2024-12-03T13:43:36Z","snapshot_observed_at":"2026-08-12T09:38:28.587555Z","submitted_at":"2024-12-03T13:43:36Z","title":"Gracefully Filtering Backdoor Samples for Generative Large Language Models without Retraining","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-11T23:32:37.221315Z"},"links":{"citing_paper":"/paper/2412.02454"},"observation_digest":"sha256:63bf55a74e2c80feebb96189b59acd0f047b8948cf31c169d906748ffacdaaf5","observation_id":"ebf84415-fc11-48a1-9bd6-47b87ee6be24","resolution":{"observed_at":"2026-08-11T23:32:38.017774Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2405.13401","last_updated":"2024-07-07T05:03:53Z","snapshot_observed_at":"2026-08-13T00:02:27.152550Z","submitted_at":"2024-05-22T07:21:32Z","title":"TrojanRAG: Retrieval-Augmented Generation Can Be Backdoor Driver in Large Language Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.13401","snapshot_observed_at":"2026-08-11T23:32:37.230867Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.02454","last_updated":"2024-12-03T13:43:36Z","snapshot_observed_at":"2026-08-12T09:38:28.587555Z","submitted_at":"2024-12-03T13:43:36Z","title":"Gracefully Filtering Backdoor Samples for Generative Large Language Models without Retraining","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-11T23:32:37.230867Z"},"links":{"cited_paper":"/paper/2405.13401","citing_paper":"/paper/2412.02454"},"observation_digest":"sha256:cb7561c906d969261ab0796b1d462503ddde79ce52fb0a4073082af867710ae0","observation_id":"deecf3e3-388b-44ef-a699-41ffdf2dd286","resolution":{"observed_at":"2026-08-11T23:32:37.230867Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.06055","last_updated":"2024-12-04T05:04:46Z","snapshot_observed_at":"2026-07-06T16:17:19.255200Z","submitted_at":"2023-09-12T08:48:38Z","title":"Backdoor Attacks and Countermeasures in Natural Language Processing Models: A Comprehensive Security Review","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.06055","snapshot_observed_at":"2026-08-11T23:32:37.237102Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.02454","last_updated":"2024-12-03T13:43:36Z","snapshot_observed_at":"2026-08-12T09:38:28.587555Z","submitted_at":"2024-12-03T13:43:36Z","title":"Gracefully Filtering Backdoor Samples for Generative Large Language Models without Retraining","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-11T23:32:37.237102Z"},"links":{"cited_paper":"/paper/2309.06055","citing_paper":"/paper/2412.02454"},"observation_digest":"sha256:5093bab59782bc90e8f48d093e74928ad3b3cbfe7b9de91f3680f06c850c894a","observation_id":"754c9af4-6068-4a41-9f61-391a5439dfbe","resolution":{"observed_at":"2026-08-11T23:32:37.237102Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.09878","last_updated":"2024-08-19T10:39:45Z","snapshot_observed_at":"2026-08-12T23:01:33.855923Z","submitted_at":"2024-08-19T10:39:45Z","title":"Transferring Backdoors between Large Language Models by Knowledge Distillation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.09878","snapshot_observed_at":"2026-08-11T23:32:37.244331Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.02454","last_updated":"2024-12-03T13:43:36Z","snapshot_observed_at":"2026-08-12T09:38:28.587555Z","submitted_at":"2024-12-03T13:43:36Z","title":"Gracefully Filtering Backdoor Samples for Generative Large Language Models without Retraining","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-11T23:32:37.244331Z"},"links":{"cited_paper":"/paper/2408.09878","citing_paper":"/paper/2412.02454"},"observation_digest":"sha256:25108ea709bd135716038d2f16b54eaff1211bc96b95f2399a8742fb2cd637ba","observation_id":"a000e2f9-15df-476d-be6b-35e952881d40","resolution":{"observed_at":"2026-08-11T23:32:37.244331Z","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":"2026-08-11T23:32:37.249474Z","title":"Gonzalez, Ion Stoica, and Eric P","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.02454","last_updated":"2024-12-03T13:43:36Z","snapshot_observed_at":"2026-08-12T09:38:28.587555Z","submitted_at":"2024-12-03T13:43:36Z","title":"Gracefully Filtering Backdoor Samples for Generative Large Language Models without Retraining","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-11T23:32:37.249474Z"},"links":{"citing_paper":"/paper/2412.02454"},"observation_digest":"sha256:e40166f58a9a2856a9011fc1d6323b748e767d37d653d2b30d7a38e8ce518289","observation_id":"4a15e468-ea28-4ab3-9535-bccd12c8d06b","resolution":{"observed_at":"2026-08-11T23:32:37.249474Z","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":"2026-08-11T23:32:38.973172Z","title":null,"venue":null,"work_id":"64589ac1-6b3b-410a-abcd-1de7a67c6a95","year":2022},"citing_paper":{"arxiv_id":"2412.02454","last_updated":"2024-12-03T13:43:36Z","snapshot_observed_at":"2026-08-12T09:38:28.587555Z","submitted_at":"2024-12-03T13:43:36Z","title":"Gracefully Filtering Backdoor Samples for Generative Large Language Models without Retraining","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-11T23:32:37.254583Z"},"links":{"citing_paper":"/paper/2412.02454"},"observation_digest":"sha256:9f695c76e2404eb335f1d59b32801d1f33796f19c9b56fe4c7bcb802ecf4a7ff","observation_id":"fb5b4151-c4df-4dc2-83fd-a099976f5127","resolution":{"observed_at":"2026-08-11T23:32:38.978760Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2019.29413","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:32:38.705872Z","title":null,"venue":null,"work_id":"278d8b52-29f3-4863-b9d3-9e23e4f2f74f","year":2019},"citing_paper":{"arxiv_id":"2412.02454","last_updated":"2024-12-03T13:43:36Z","snapshot_observed_at":"2026-08-12T09:38:28.587555Z","submitted_at":"2024-12-03T13:43:36Z","title":"Gracefully Filtering Backdoor Samples for Generative Large Language Models without Retraining","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-11T23:32:37.259340Z"},"links":{"citing_paper":"/paper/2412.02454"},"observation_digest":"sha256:254cf024e77a8bde561e2d1d9009e7b71cc105eaa7b9fb634bbeca650d22c586","observation_id":"15a478c6-ea12-43ca-9966-34f6a79b73e3","resolution":{"observed_at":"2026-08-11T23:32:38.715057Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2301.00234","last_updated":"2024-10-05T11:47:02Z","snapshot_observed_at":"2026-07-06T14:36:25.690733Z","submitted_at":"2022-12-31T15:57:09Z","title":"A Survey on In-context Learning","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2301.00234","snapshot_observed_at":"2026-08-11T23:32:37.265187Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.02454","last_updated":"2024-12-03T13:43:36Z","snapshot_observed_at":"2026-08-12T09:38:28.587555Z","submitted_at":"2024-12-03T13:43:36Z","title":"Gracefully Filtering Backdoor Samples for Generative Large Language Models without Retraining","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-11T23:32:37.265187Z"},"links":{"cited_paper":"/paper/2301.00234","citing_paper":"/paper/2412.02454"},"observation_digest":"sha256:ac9f2d5891e778b55c20695e2f67ac456351e0a73436186e61aa66669944f723","observation_id":"4b593247-63a0-4b75-86c1-ef8659396043","resolution":{"observed_at":"2026-08-11T23:32:37.265187Z","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":"2024.24620","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:32:38.602223Z","title":null,"venue":null,"work_id":"df991e0b-225a-44a8-97a2-1521a7e895ae","year":2024},"citing_paper":{"arxiv_id":"2412.02454","last_updated":"2024-12-03T13:43:36Z","snapshot_observed_at":"2026-08-12T09:38:28.587555Z","submitted_at":"2024-12-03T13:43:36Z","title":"Gracefully Filtering Backdoor Samples for Generative Large Language Models without Retraining","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-11T23:32:37.272286Z"},"links":{"citing_paper":"/paper/2412.02454"},"observation_digest":"sha256:ad3d408f6e3875f172a0d7531f1435fa65ea20da4648656d3c578dd3645f7a18","observation_id":"86d27401-a7fd-440d-93ea-e85fa78e5599","resolution":{"observed_at":"2026-08-11T23:32:38.615629Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2021.30558","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:32:38.495111Z","title":null,"venue":null,"work_id":"c7b380e0-a039-474c-9ad9-ed3450dda083","year":2021},"citing_paper":{"arxiv_id":"2412.02454","last_updated":"2024-12-03T13:43:36Z","snapshot_observed_at":"2026-08-12T09:38:28.587555Z","submitted_at":"2024-12-03T13:43:36Z","title":"Gracefully Filtering Backdoor Samples for Generative Large Language Models without Retraining","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-11T23:32:37.278088Z"},"links":{"citing_paper":"/paper/2412.02454"},"observation_digest":"sha256:9e3e40446fbc6435104a4a0c3f9291668e69e07ea78d46d4a208bedf2ca2e949","observation_id":"a7e615f6-868f-4247-bd06-f45099798eba","resolution":{"observed_at":"2026-08-11T23:32:38.503604Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-11T23:32:37.284046Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.02454","last_updated":"2024-12-03T13:43:36Z","snapshot_observed_at":"2026-08-12T09:38:28.587555Z","submitted_at":"2024-12-03T13:43:36Z","title":"Gracefully Filtering Backdoor Samples for Generative Large Language Models without Retraining","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-11T23:32:37.284046Z"},"links":{"citing_paper":"/paper/2412.02454"},"observation_digest":"sha256:573c93fae2b6556155514e02c93b5557d4a2224437ed7f4bf66dcdf8f1103714","observation_id":"4dc32a14-d77e-4d35-9142-93ef47a0df41","resolution":{"observed_at":"2026-08-11T23:32:37.284046Z","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":"2026-08-11T23:32:38.954586Z","title":null,"venue":null,"work_id":"cec93679-9eed-4fec-a5b1-90b127ec26c6","year":2022},"citing_paper":{"arxiv_id":"2412.02454","last_updated":"2024-12-03T13:43:36Z","snapshot_observed_at":"2026-08-12T09:38:28.587555Z","submitted_at":"2024-12-03T13:43:36Z","title":"Gracefully Filtering Backdoor Samples for Generative Large Language Models without Retraining","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-11T23:32:37.289579Z"},"links":{"citing_paper":"/paper/2412.02454"},"observation_digest":"sha256:1fe663e8a89b2c92743f18c7a7e1437fa0922931c2ce7c9023fbcfd85b343dd2","observation_id":"23ab2011-2e9e-4a13-ac7d-a015ef32708a","resolution":{"observed_at":"2026-08-11T23:32:38.960905Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.18653/v1/2024.findings-naacl.94","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:32:37.898645Z","title":null,"venue":null,"work_id":"aa0666e8-5b64-46d9-803e-7942fc7ee797","year":2024},"citing_paper":{"arxiv_id":"2412.02454","last_updated":"2024-12-03T13:43:36Z","snapshot_observed_at":"2026-08-12T09:38:28.587555Z","submitted_at":"2024-12-03T13:43:36Z","title":"Gracefully Filtering Backdoor Samples for Generative Large Language Models without Retraining","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-11T23:32:37.296226Z"},"links":{"citing_paper":"/paper/2412.02454"},"observation_digest":"sha256:611e51208d64396eccec766fd0f530d21aad1f78d653dda0147bb040b93a98ca","observation_id":"9a3b08d2-9bf1-4909-983b-732c6403b678","resolution":{"observed_at":"2026-08-11T23:32:37.904043Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-11T23:32:37.301727Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2412.02454","last_updated":"2024-12-03T13:43:36Z","snapshot_observed_at":"2026-08-12T09:38:28.587555Z","submitted_at":"2024-12-03T13:43:36Z","title":"Gracefully Filtering Backdoor Samples for Generative Large Language Models without Retraining","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-11T23:32:37.301727Z"},"links":{"citing_paper":"/paper/2412.02454"},"observation_digest":"sha256:de16d37dc26d096a32fedbac979692453b061624d4565445ffdb4ff3a7cf8228","observation_id":"6671e1c8-abed-452b-a34e-5dfba2a11738","resolution":{"observed_at":"2026-08-11T23:32:37.301727Z","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":"10.18653/v1/2022.emnlp-main.798","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:32:37.868339Z","title":null,"venue":null,"work_id":"03ca3e65-418d-42f8-8ff1-3aa6e6c6afb0","year":2022},"citing_paper":{"arxiv_id":"2412.02454","last_updated":"2024-12-03T13:43:36Z","snapshot_observed_at":"2026-08-12T09:38:28.587555Z","submitted_at":"2024-12-03T13:43:36Z","title":"Gracefully Filtering Backdoor Samples for Generative Large Language Models without Retraining","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-11T23:32:37.308299Z"},"links":{"citing_paper":"/paper/2412.02454"},"observation_digest":"sha256:75373c542fb3b5b57c0eae3af399793f7051d1ab11393950afd2a5f7984af2c9","observation_id":"a7e8c155-c8ac-453b-b30e-c5994bcee16d","resolution":{"observed_at":"2026-08-11T23:32:37.873653Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-11T23:32:37.313366Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2412.02454","last_updated":"2024-12-03T13:43:36Z","snapshot_observed_at":"2026-08-12T09:38:28.587555Z","submitted_at":"2024-12-03T13:43:36Z","title":"Gracefully Filtering Backdoor Samples for Generative Large Language Models without Retraining","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-11T23:32:37.313366Z"},"links":{"citing_paper":"/paper/2412.02454"},"observation_digest":"sha256:9cd6e9522be77ea3a617303458e9692caa67d43c99f7b0ca2bf1dd8f346ef172","observation_id":"14f7a712-1e36-4ac8-a528-466dfdecb814","resolution":{"observed_at":"2026-08-11T23:32:37.313366Z","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":"2026-08-11T23:32:37.319268Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2412.02454","last_updated":"2024-12-03T13:43:36Z","snapshot_observed_at":"2026-08-12T09:38:28.587555Z","submitted_at":"2024-12-03T13:43:36Z","title":"Gracefully Filtering Backdoor Samples for Generative Large Language Models without Retraining","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-11T23:32:37.319268Z"},"links":{"citing_paper":"/paper/2412.02454"},"observation_digest":"sha256:7afb3c342cc159cf3ee0ba94c1f71c7a61b56f2d202f10f684ea0fc9010355a9","observation_id":"25072cef-32a2-4403-8790-13d233528b51","resolution":{"observed_at":"2026-08-11T23:32:37.319268Z","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":"2026-08-11T23:32:38.932838Z","title":null,"venue":null,"work_id":"2eb841bd-a517-4d52-9fb9-5998b5428a63","year":2024},"citing_paper":{"arxiv_id":"2412.02454","last_updated":"2024-12-03T13:43:36Z","snapshot_observed_at":"2026-08-12T09:38:28.587555Z","submitted_at":"2024-12-03T13:43:36Z","title":"Gracefully Filtering Backdoor Samples for Generative Large Language Models without Retraining","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-11T23:32:37.324601Z"},"links":{"citing_paper":"/paper/2412.02454"},"observation_digest":"sha256:1989094db57fd1875b4ee1c0a2ac5d937c85730eee78bbc368a8a74fd0a4b298","observation_id":"61938a10-3970-4596-a5f0-8c3bf5a0ada4","resolution":{"observed_at":"2026-08-11T23:32:38.939762Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.12257","last_updated":"2025-03-27T16:21:02Z","snapshot_observed_at":"2026-08-12T23:40:27.733082Z","submitted_at":"2024-06-18T04:10:38Z","title":"CleanGen: Mitigating Backdoor Attacks for Generation Tasks in Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.12257","snapshot_observed_at":"2026-08-11T23:32:37.329637Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.02454","last_updated":"2024-12-03T13:43:36Z","snapshot_observed_at":"2026-08-12T09:38:28.587555Z","submitted_at":"2024-12-03T13:43:36Z","title":"Gracefully Filtering Backdoor Samples for Generative Large Language Models without Retraining","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-11T23:32:37.329637Z"},"links":{"cited_paper":"/paper/2406.12257","citing_paper":"/paper/2412.02454"},"observation_digest":"sha256:bd33d9c691e2987c067667ce234977e06e55402ffa64d669a39e642e438dcc85","observation_id":"390881ca-a5c1-4688-89ed-3a7b41887d4d","resolution":{"observed_at":"2026-08-11T23:32:37.329637Z","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":"10.18653/v1/2021.findings-emnlp.40","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:32:37.803060Z","title":null,"venue":null,"work_id":"c51b639c-a8c1-4db2-a573-1b9912e8621c","year":2021},"citing_paper":{"arxiv_id":"2412.02454","last_updated":"2024-12-03T13:43:36Z","snapshot_observed_at":"2026-08-12T09:38:28.587555Z","submitted_at":"2024-12-03T13:43:36Z","title":"Gracefully Filtering Backdoor Samples for Generative Large Language Models without Retraining","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-11T23:32:37.336619Z"},"links":{"citing_paper":"/paper/2412.02454"},"observation_digest":"sha256:920879afb8dd259ee44f6fda9f6a567d3bd99f6f985a1ca99b4ea4ec586b3657","observation_id":"b10b3e87-ae4e-43d0-b46f-3bd09a4b9406","resolution":{"observed_at":"2026-08-11T23:32:37.808751Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-11T23:32:37.342853Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2412.02454","last_updated":"2024-12-03T13:43:36Z","snapshot_observed_at":"2026-08-12T09:38:28.587555Z","submitted_at":"2024-12-03T13:43:36Z","title":"Gracefully Filtering Backdoor Samples for Generative Large Language Models without Retraining","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-11T23:32:37.342853Z"},"links":{"citing_paper":"/paper/2412.02454"},"observation_digest":"sha256:98538a7dd3a806fcad2d8f4b57ba86d22f15783e72d8202a6a5487fc4bf44e92","observation_id":"46adc126-a5cd-403f-a3b5-879d5fd31c9e","resolution":{"observed_at":"2026-08-11T23:32:37.342853Z","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":"2026-08-11T23:32:37.349849Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.02454","last_updated":"2024-12-03T13:43:36Z","snapshot_observed_at":"2026-08-12T09:38:28.587555Z","submitted_at":"2024-12-03T13:43:36Z","title":"Gracefully Filtering Backdoor Samples for Generative Large Language Models without Retraining","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-11T23:32:37.349849Z"},"links":{"citing_paper":"/paper/2412.02454"},"observation_digest":"sha256:c60b8e0dc46c007f44ed970dc2c50d40d48b92a7c98d74cc8141822a4dfbd427","observation_id":"4d9946b9-a580-4a09-b7f8-2323ef1be9de","resolution":{"observed_at":"2026-08-11T23:32:37.349849Z","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":"2026-08-11T23:32:37.356666Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.02454","last_updated":"2024-12-03T13:43:36Z","snapshot_observed_at":"2026-08-12T09:38:28.587555Z","submitted_at":"2024-12-03T13:43:36Z","title":"Gracefully Filtering Backdoor Samples for Generative Large Language Models without Retraining","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-11T23:32:37.356666Z"},"links":{"citing_paper":"/paper/2412.02454"},"observation_digest":"sha256:51cf080fada7d3f84bbc25744d03e03037b9ff69657d055b5afe1987ee60f54b","observation_id":"56c0dc03-e7fd-48b4-97f5-55588028e627","resolution":{"observed_at":"2026-08-11T23:32:37.356666Z","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":"2026-08-11T23:32:37.362476Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2412.02454","last_updated":"2024-12-03T13:43:36Z","snapshot_observed_at":"2026-08-12T09:38:28.587555Z","submitted_at":"2024-12-03T13:43:36Z","title":"Gracefully Filtering Backdoor Samples for Generative Large Language Models without Retraining","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-11T23:32:37.362476Z"},"links":{"citing_paper":"/paper/2412.02454"},"observation_digest":"sha256:c2856858151e8004b0a1c42d8a2e056bce6aeb0ef280ab81fe888590e94c62d7","observation_id":"5e38000d-059b-4b32-8e9e-e986f95de913","resolution":{"observed_at":"2026-08-11T23:32:37.362476Z","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":"2026-08-11T23:32:38.900503Z","title":null,"venue":null,"work_id":"94c42a97-8d3f-4d90-afa1-144ce5de1375","year":2019},"citing_paper":{"arxiv_id":"2412.02454","last_updated":"2024-12-03T13:43:36Z","snapshot_observed_at":"2026-08-12T09:38:28.587555Z","submitted_at":"2024-12-03T13:43:36Z","title":"Gracefully Filtering Backdoor Samples for Generative Large Language Models without Retraining","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-11T23:32:37.370255Z"},"links":{"citing_paper":"/paper/2412.02454"},"observation_digest":"sha256:94b6ffcf4eba01799ab9646dd7ebca6e87231217773b0f35a3c9d06a183e6f68","observation_id":"9c2e80f3-29c7-4288-840e-d268197d2576","resolution":{"observed_at":"2026-08-11T23:32:38.906133Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-11T23:32:37.376110Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2412.02454","last_updated":"2024-12-03T13:43:36Z","snapshot_observed_at":"2026-08-12T09:38:28.587555Z","submitted_at":"2024-12-03T13:43:36Z","title":"Gracefully Filtering Backdoor Samples for Generative Large Language Models without Retraining","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-11T23:32:37.376110Z"},"links":{"citing_paper":"/paper/2412.02454"},"observation_digest":"sha256:fc4ae64b0588c344547ff2d3c2e9fe01a4377eb0072a5f38aa5b26fbdd114d5e","observation_id":"a01db7ab-8aa0-4d48-bb42-0c3029cd3eb1","resolution":{"observed_at":"2026-08-11T23:32:37.376110Z","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":"2026-08-11T23:32:37.384232Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2412.02454","last_updated":"2024-12-03T13:43:36Z","snapshot_observed_at":"2026-08-12T09:38:28.587555Z","submitted_at":"2024-12-03T13:43:36Z","title":"Gracefully Filtering Backdoor Samples for Generative Large Language Models without Retraining","version":1},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-11T23:32:37.384232Z"},"links":{"citing_paper":"/paper/2412.02454"},"observation_digest":"sha256:097e56ae67e20dcc00eccf68afca73144e2f975e571f509cbdee8620c12d0bfc","observation_id":"2b1d49f6-193c-4740-bab4-cd027f25a356","resolution":{"observed_at":"2026-08-11T23:32:37.384232Z","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":"2026-08-11T23:32:37.393639Z","title":null,"venue":null,"work_id":null,"year":1987},"citing_paper":{"arxiv_id":"2412.02454","last_updated":"2024-12-03T13:43:36Z","snapshot_observed_at":"2026-08-12T09:38:28.587555Z","submitted_at":"2024-12-03T13:43:36Z","title":"Gracefully Filtering Backdoor Samples for Generative Large Language Models without Retraining","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-11T23:32:37.393639Z"},"links":{"citing_paper":"/paper/2412.02454"},"observation_digest":"sha256:71708c0eebfeffd447a4178ec32907901f49a41aa3812eeae17d7fc2451c1623","observation_id":"1a1497ec-8e04-46e5-afbc-19bda374e608","resolution":{"observed_at":"2026-08-11T23:32:37.393639Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"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":"2026-08-11T23:32:37.400217Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.02454","last_updated":"2024-12-03T13:43:36Z","snapshot_observed_at":"2026-08-12T09:38:28.587555Z","submitted_at":"2024-12-03T13:43:36Z","title":"Gracefully Filtering Backdoor Samples for Generative Large Language Models without Retraining","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-11T23:32:37.400217Z"},"links":{"cited_paper":"/paper/2307.09288","citing_paper":"/paper/2412.02454"},"observation_digest":"sha256:26453b480a60f4bd59684833589fa8879c542c0fc6e8e26edc0c578f15924e3a","observation_id":"274187f0-9f35-426c-ad79-ff075489d293","resolution":{"observed_at":"2026-08-11T23:32:37.400217Z","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":"2026-08-11T23:32:38.881908Z","title":null,"venue":null,"work_id":"0f80c385-f4b4-40ac-ae4b-a19366144d42","year":2022},"citing_paper":{"arxiv_id":"2412.02454","last_updated":"2024-12-03T13:43:36Z","snapshot_observed_at":"2026-08-12T09:38:28.587555Z","submitted_at":"2024-12-03T13:43:36Z","title":"Gracefully Filtering Backdoor Samples for Generative Large Language Models without Retraining","version":1},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-11T23:32:37.406219Z"},"links":{"citing_paper":"/paper/2412.02454"},"observation_digest":"sha256:79dc2dc0a9db91a775238f73148633a6b45f1f030ecaa87437839b2ebe35825e","observation_id":"e0b8efec-0049-4e53-a737-45305bf6b6d3","resolution":{"observed_at":"2026-08-11T23:32:38.887023Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-11T23:32:38.864619Z","title":null,"venue":null,"work_id":"04cbae23-7ffc-4246-9be5-9468aba92c31","year":2024},"citing_paper":{"arxiv_id":"2412.02454","last_updated":"2024-12-03T13:43:36Z","snapshot_observed_at":"2026-08-12T09:38:28.587555Z","submitted_at":"2024-12-03T13:43:36Z","title":"Gracefully Filtering Backdoor Samples for Generative Large Language Models without Retraining","version":1},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-11T23:32:37.412283Z"},"links":{"citing_paper":"/paper/2412.02454"},"observation_digest":"sha256:ff24ea3ba4caa35942598ad4fd576df708fe7558ec5d6715587a6b9a025bf357","observation_id":"07eae30e-fdc2-45fd-918b-0be06f409853","resolution":{"observed_at":"2026-08-11T23:32:38.869497Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-11T23:32:38.845851Z","title":null,"venue":null,"work_id":"fef93570-9636-4d45-8210-f2cfb6b97869","year":2024},"citing_paper":{"arxiv_id":"2412.02454","last_updated":"2024-12-03T13:43:36Z","snapshot_observed_at":"2026-08-12T09:38:28.587555Z","submitted_at":"2024-12-03T13:43:36Z","title":"Gracefully Filtering Backdoor Samples for Generative Large Language Models without Retraining","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-11T23:32:37.418347Z"},"links":{"citing_paper":"/paper/2412.02454"},"observation_digest":"sha256:8db3274537d903e37e98a8f501cb6f6146ec1f51839fab6c9ac6d487102d6d42","observation_id":"a63c6828-0628-460f-82e4-ac21951398e7","resolution":{"observed_at":"2026-08-11T23:32:38.851884Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-11T23:32:38.827025Z","title":null,"venue":null,"work_id":"38122d40-faae-42fd-bfa6-fa951ed4e11a","year":2020},"citing_paper":{"arxiv_id":"2412.02454","last_updated":"2024-12-03T13:43:36Z","snapshot_observed_at":"2026-08-12T09:38:28.587555Z","submitted_at":"2024-12-03T13:43:36Z","title":"Gracefully Filtering Backdoor Samples for Generative Large Language Models without Retraining","version":1},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-11T23:32:37.425493Z"},"links":{"citing_paper":"/paper/2412.02454"},"observation_digest":"sha256:6806c8cb1f2cb3bfe34a8a4145e6dba27fcd541f95a6815c420bdd11d86a16cd","observation_id":"182733a8-c8c1-4654-8afc-b110191cbc69","resolution":{"observed_at":"2026-08-11T23:32:38.832405Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-11T23:32:37.431697Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2412.02454","last_updated":"2024-12-03T13:43:36Z","snapshot_observed_at":"2026-08-12T09:38:28.587555Z","submitted_at":"2024-12-03T13:43:36Z","title":"Gracefully Filtering Backdoor Samples for Generative Large Language Models without Retraining","version":1},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-11T23:32:37.431697Z"},"links":{"citing_paper":"/paper/2412.02454"},"observation_digest":"sha256:182cd8fe17095af2261fca58b377da30a652c87c9dcae3797e0bed1c1aef60a3","observation_id":"b36879eb-59d1-48b9-814a-01dd22ffb6e2","resolution":{"observed_at":"2026-08-11T23:32:37.431697Z","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":"10.1609/aaai.v35i12.17261","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:32:37.695060Z","title":null,"venue":null,"work_id":"b4a8cdf3-c79c-4089-9b88-6707d75ea24f","year":2021},"citing_paper":{"arxiv_id":"2412.02454","last_updated":"2024-12-03T13:43:36Z","snapshot_observed_at":"2026-08-12T09:38:28.587555Z","submitted_at":"2024-12-03T13:43:36Z","title":"Gracefully Filtering Backdoor Samples for Generative Large Language Models without Retraining","version":1},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-11T23:32:37.438111Z"},"links":{"citing_paper":"/paper/2412.02454"},"observation_digest":"sha256:2f0771606e0f10e7c1084f7bcd4bf93a830e7ca29da79c88a93cb4d3e94a7dbc","observation_id":"b7c8e2e3-7697-4128-850c-f39712c0185a","resolution":{"observed_at":"2026-08-11T23:32:37.701173Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.08956","last_updated":"2025-05-17T01:19:58Z","snapshot_observed_at":"2026-08-12T23:23:47.179346Z","submitted_at":"2024-07-12T03:18:38Z","title":"Defending Code Language Models against Backdoor Attacks with Deceptive Cross-Entropy Loss","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.08956","snapshot_observed_at":"2026-08-11T23:32:37.445016Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.02454","last_updated":"2024-12-03T13:43:36Z","snapshot_observed_at":"2026-08-12T09:38:28.587555Z","submitted_at":"2024-12-03T13:43:36Z","title":"Gracefully Filtering Backdoor Samples for Generative Large Language Models without Retraining","version":1},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-11T23:32:37.445016Z"},"links":{"cited_paper":"/paper/2407.08956","citing_paper":"/paper/2412.02454"},"observation_digest":"sha256:7e95f56499dc2e9f4d44a8774be8a83a50223fba29e8189e5626872cb0907b7a","observation_id":"696f4206-7a95-4508-b2bc-4e9eecfa2fbb","resolution":{"observed_at":"2026-08-11T23:32:37.445016Z","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":"10.18653/v1/2021.emnlp-main.659","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:32:37.654251Z","title":null,"venue":null,"work_id":"45db02af-b477-437d-b76e-019da91bc34d","year":2021},"citing_paper":{"arxiv_id":"2412.02454","last_updated":"2024-12-03T13:43:36Z","snapshot_observed_at":"2026-08-12T09:38:28.587555Z","submitted_at":"2024-12-03T13:43:36Z","title":"Gracefully Filtering Backdoor Samples for Generative Large Language Models without Retraining","version":1},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-11T23:32:37.451589Z"},"links":{"citing_paper":"/paper/2412.02454"},"observation_digest":"sha256:646910eb779454342dbb77978a46eb37e20ca7d2af03fab9ef5d0ca37cbdc219","observation_id":"f0e61ef8-530f-4573-8736-e62dc2524116","resolution":{"observed_at":"2026-08-11T23:32:37.659506Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.18653/v1/2023.findings-acl.157","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:32:37.635598Z","title":null,"venue":null,"work_id":"666c3fbb-b216-4e05-ad29-c8a7dd582d5b","year":2023},"citing_paper":{"arxiv_id":"2412.02454","last_updated":"2024-12-03T13:43:36Z","snapshot_observed_at":"2026-08-12T09:38:28.587555Z","submitted_at":"2024-12-03T13:43:36Z","title":"Gracefully Filtering Backdoor Samples for Generative Large Language Models without Retraining","version":1},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-11T23:32:37.457199Z"},"links":{"citing_paper":"/paper/2412.02454"},"observation_digest":"sha256:4f30cab08c43b4ff79d8a2c9f0ae477e9e99a8b908797c1300710e159d8dd2e3","observation_id":"eb098fbf-d3a4-4ba4-b665-f60848de28a6","resolution":{"observed_at":"2026-08-11T23:32:37.640772Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.18653/v1/2024.findings-naacl.217","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:32:37.615547Z","title":null,"venue":null,"work_id":"ec1647a8-b21c-4d58-9c17-b58ac77b3df1","year":2024},"citing_paper":{"arxiv_id":"2412.02454","last_updated":"2024-12-03T13:43:36Z","snapshot_observed_at":"2026-08-12T09:38:28.587555Z","submitted_at":"2024-12-03T13:43:36Z","title":"Gracefully Filtering Backdoor Samples for Generative Large Language Models without Retraining","version":1},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-11T23:32:37.463095Z"},"links":{"citing_paper":"/paper/2412.02454"},"observation_digest":"sha256:b6faffc232bd948a965343aa747137707433694abe5c1f0f21fad2444bb440fa","observation_id":"e6ce9416-b30b-458b-be7b-1376fd7ce3ab","resolution":{"observed_at":"2026-08-11T23:32:37.621372Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2401.05949","last_updated":"2024-10-09T11:46:24Z","snapshot_observed_at":"2026-08-13T04:44:33.587123Z","submitted_at":"2024-01-11T14:38:19Z","title":"Universal Vulnerabilities in Large Language Models: Backdoor Attacks for In-context Learning","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.05949","snapshot_observed_at":"2026-08-11T23:32:37.469049Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.02454","last_updated":"2024-12-03T13:43:36Z","snapshot_observed_at":"2026-08-12T09:38:28.587555Z","submitted_at":"2024-12-03T13:43:36Z","title":"Gracefully Filtering Backdoor Samples for Generative Large Language Models without Retraining","version":1},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-08-11T23:32:37.469049Z"},"links":{"cited_paper":"/paper/2401.05949","citing_paper":"/paper/2412.02454"},"observation_digest":"sha256:02e29e2cc27a265f3a5d55d60b5471667f23d6666a0476cc9844234a8679c255","observation_id":"2cd724ee-f883-41a9-a562-0bcea2c9680d","resolution":{"observed_at":"2026-08-11T23:32:37.469049Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.18223","last_updated":"2026-03-18T05:34:39Z","snapshot_observed_at":"2026-08-06T23:27:24.356320Z","submitted_at":"2023-03-31T17:28:46Z","title":"A Survey of Large Language Models","version":19},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.18223","snapshot_observed_at":"2026-08-11T23:32:37.476652Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.02454","last_updated":"2024-12-03T13:43:36Z","snapshot_observed_at":"2026-08-12T09:38:28.587555Z","submitted_at":"2024-12-03T13:43:36Z","title":"Gracefully Filtering Backdoor Samples for Generative Large Language Models without Retraining","version":1},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-08-11T23:32:37.476652Z"},"links":{"cited_paper":"/paper/2303.18223","citing_paper":"/paper/2412.02454"},"observation_digest":"sha256:417d024b8247a3686efc2b08490e8d4cb39d385e1bc47a7c01e9455206810aac","observation_id":"e573e9cf-9b6b-46db-8e73-1634cf6e7aeb","resolution":{"observed_at":"2026-08-11T23:32:37.476652Z","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":"10.1162/tacl_a_00622","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:32:37.542252Z","title":null,"venue":null,"work_id":"d1c30849-aae8-4b3d-8a9e-b584591c4798","year":2023},"citing_paper":{"arxiv_id":"2412.02454","last_updated":"2024-12-03T13:43:36Z","snapshot_observed_at":"2026-08-12T09:38:28.587555Z","submitted_at":"2024-12-03T13:43:36Z","title":"Gracefully Filtering Backdoor Samples for Generative Large Language Models without Retraining","version":1},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-11T23:32:37.482334Z"},"links":{"citing_paper":"/paper/2412.02454"},"observation_digest":"sha256:761ec6e7beb1bde4270d547bc9b4568e90b939678be7c5a9b4e398cce8569c74","observation_id":"8bc7f476-c9ca-41e4-bb60-047d7fcdc94e","resolution":{"observed_at":"2026-08-11T23:32:37.550278Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"file/0799492","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:32:38.147840Z","title":null,"venue":null,"work_id":"aa36c9b5-0931-4524-8690-9f28d02dc711","year":2022},"citing_paper":{"arxiv_id":"2412.02454","last_updated":"2024-12-03T13:43:36Z","snapshot_observed_at":"2026-08-12T09:38:28.587555Z","submitted_at":"2024-12-03T13:43:36Z","title":"Gracefully Filtering Backdoor Samples for Generative Large Language Models without Retraining","version":1},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-08-11T23:32:37.488900Z"},"links":{"citing_paper":"/paper/2412.02454"},"observation_digest":"sha256:8416fc7b92f8454627d042735ae35547405c6840814cea328e6150e07ba34509","observation_id":"583b1d8f-8b8e-4ab6-8e4f-82cc092ebc7b","resolution":{"observed_at":"2026-08-11T23:32:38.158082Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-11T23:32:37.494065Z","title":"online\" 'onlinestring :=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2412.02454","last_updated":"2024-12-03T13:43:36Z","snapshot_observed_at":"2026-08-12T09:38:28.587555Z","submitted_at":"2024-12-03T13:43:36Z","title":"Gracefully Filtering Backdoor Samples for Generative Large Language Models without Retraining","version":1},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-08-11T23:32:37.494065Z"},"links":{"citing_paper":"/paper/2412.02454"},"observation_digest":"sha256:51261c5fb5590a22faa93f6a95a50e608cd0f370226da3b486117fa987f922e3","observation_id":"5f353f2a-135a-4c01-a725-db7c1bc50c11","resolution":{"observed_at":"2026-08-11T23:32:37.494065Z","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":"2026-08-11T23:32:37.500348Z","title":"write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2412.02454","last_updated":"2024-12-03T13:43:36Z","snapshot_observed_at":"2026-08-12T09:38:28.587555Z","submitted_at":"2024-12-03T13:43:36Z","title":"Gracefully Filtering Backdoor Samples for Generative Large Language Models without Retraining","version":1},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-08-11T23:32:37.500348Z"},"links":{"citing_paper":"/paper/2412.02454"},"observation_digest":"sha256:35d20a6be3114b5d93e1a409d418b7b0105c0fff10319ee36a92172dcb4af417","observation_id":"141b8cfb-f82a-4faa-904c-6a2e14128db4","resolution":{"observed_at":"2026-08-11T23:32:37.500348Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2412.02454","last_updated":"2024-12-03T13:43:36Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-12T09:38:28.587555Z","submitted_at":"2024-12-03T13:43:36Z","title":"Gracefully Filtering Backdoor Samples for Generative Large Language Models without Retraining"},"reference_resolution":{"displayed":48,"state_counts":{"malformed_identifier":0,"metadata_mismatch":2,"parse_uncertain":0,"unresolved":35,"verified_exact":11,"verified_fuzzy":0},"total_outbound_references":48},"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":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"thesis":"As of 13 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 0 inbound Pith citation observations for arXiv:2412.02454."}