{"as_of":"2026-08-12T19:14:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:5fe1e78766e784b2cb3ad9d007cb10fc9c4d823f33a4a8e32c2bd080e0cfb76e","coverage":[{"denominator":28,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":28,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-11T11:22:20.208006Z","state":"measured"},{"denominator":28,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":28,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-12T06:34:41.77262+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/2412.16254/citation-record","integrity":"/paper/2412.16254/integrity","json":"/paper/2412.16254/citation-record.json","paper":"/paper/2412.16254"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T11:22:20.877741Z","title":"Distillation as a defense to adversarial perturbations against deep neural networks,","venue":null,"work_id":"877e0876-929b-4be4-9617-c1dfe64ba9ab","year":2016},"citing_paper":{"arxiv_id":"2412.16254","last_updated":"2024-12-20T05:36:19Z","snapshot_observed_at":"2026-08-12T16:06:59.253892Z","submitted_at":"2024-12-20T05:36:19Z","title":"Adversarial Robustness through Dynamic Ensemble Learning","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-11T11:22:20.008594Z"},"links":{"citing_paper":"/paper/2412.16254"},"observation_digest":"sha256:5f4285a9cacdf59dc52b69bbdcb51093455ab5ff3426096503895ec5ff40bdf5","observation_id":"6e3a1d99-b417-4a24-880e-e047d12d1f55","resolution":{"observed_at":"2026-08-11T11:22:20.886260Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T11:22:20.856139Z","title":"Word -level textual adversarial attack method based on differential evolution algorithm,","venue":null,"work_id":"de9602da-8cdb-41ff-ac57-eea6ab673889","year":2022},"citing_paper":{"arxiv_id":"2412.16254","last_updated":"2024-12-20T05:36:19Z","snapshot_observed_at":"2026-08-12T16:06:59.253892Z","submitted_at":"2024-12-20T05:36:19Z","title":"Adversarial Robustness through Dynamic Ensemble Learning","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-11T11:22:20.015983Z"},"links":{"citing_paper":"/paper/2412.16254"},"observation_digest":"sha256:302bc11e0fbc2995973ef1194dbf8a0ace8a1df56c93cc1c3fc54bcf737d1018","observation_id":"95c516b7-8f21-466c-9ffe-86152481a7e1","resolution":{"observed_at":"2026-08-11T11:22:20.861792Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T11:22:20.834114Z","title":"A modified word saliency-based adversarial text attack,","venue":null,"work_id":"b5e53ad4-96eb-4021-8051-f0850e5d4778","year":2024},"citing_paper":{"arxiv_id":"2412.16254","last_updated":"2024-12-20T05:36:19Z","snapshot_observed_at":"2026-08-12T16:06:59.253892Z","submitted_at":"2024-12-20T05:36:19Z","title":"Adversarial Robustness through Dynamic Ensemble Learning","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-11T11:22:20.024478Z"},"links":{"citing_paper":"/paper/2412.16254"},"observation_digest":"sha256:33518c462d44d2aad51b9390ca878594a5cd8f3a0f5aab78a737faaaaa4740ac","observation_id":"e630a51f-ccf8-4fab-b2fa-5837fb60f7ad","resolution":{"observed_at":"2026-08-11T11:22:20.839812Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T11:22:20.805778Z","title":"Saliency attention and semantic similarity-driven adversarial perturbation,","venue":null,"work_id":"f0b443a5-e8fb-4c21-80e3-5716e12d1e8a","year":2024},"citing_paper":{"arxiv_id":"2412.16254","last_updated":"2024-12-20T05:36:19Z","snapshot_observed_at":"2026-08-12T16:06:59.253892Z","submitted_at":"2024-12-20T05:36:19Z","title":"Adversarial Robustness through Dynamic Ensemble Learning","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-11T11:22:20.030142Z"},"links":{"citing_paper":"/paper/2412.16254"},"observation_digest":"sha256:3491592b2703dbf32de95469830f534012bae884f2236052515e3726dbd9142c","observation_id":"b9cf6ff6-72f8-44e4-940b-7c4122ebfdb2","resolution":{"observed_at":"2026-08-11T11:22:20.813219Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2405.04346","last_updated":"2024-09-04T15:48:40Z","snapshot_observed_at":"2026-08-12T08:01:33.660468Z","submitted_at":"2024-05-07T14:23:22Z","title":"Revisiting Character-level Adversarial Attacks for Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.04346","snapshot_observed_at":"2026-08-11T11:22:20.038849Z","title":"Revisiting character -level adversarial attacks,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.16254","last_updated":"2024-12-20T05:36:19Z","snapshot_observed_at":"2026-08-12T16:06:59.253892Z","submitted_at":"2024-12-20T05:36:19Z","title":"Adversarial Robustness through Dynamic Ensemble Learning","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-11T11:22:20.038849Z"},"links":{"cited_paper":"/paper/2405.04346","citing_paper":"/paper/2412.16254"},"observation_digest":"sha256:8fabaa599132df5bb95eb85a9e6003800d4128f685d4386255b484fa7d359b0c","observation_id":"93922730-0d17-49cc-bde0-ba0e0b515c17","resolution":{"observed_at":"2026-08-11T11:22:20.038849Z","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":"2026-08-11T11:22:20.784777Z","title":"Character-level white -box adversarial attacks against transformers via attachable subwords substitution,","venue":null,"work_id":"54724aa1-4afa-4909-a290-7511d8f4dfb4","year":2022},"citing_paper":{"arxiv_id":"2412.16254","last_updated":"2024-12-20T05:36:19Z","snapshot_observed_at":"2026-08-12T16:06:59.253892Z","submitted_at":"2024-12-20T05:36:19Z","title":"Adversarial Robustness through Dynamic Ensemble Learning","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-11T11:22:20.045717Z"},"links":{"citing_paper":"/paper/2412.16254"},"observation_digest":"sha256:883dd7431144fe01a7a9ba73cb5fb599acf97b8b80bf31258457f5f8e276e1a7","observation_id":"177d4af8-05f1-4053-81da-2b7fbee3cbb2","resolution":{"observed_at":"2026-08-11T11:22:20.790574Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T11:22:20.759074Z","title":"Defense against adversarial attacks via textual embeddings based on semantic associative field,","venue":null,"work_id":"6a7d0a41-37de-4797-a182-f014ac894aaa","year":2024},"citing_paper":{"arxiv_id":"2412.16254","last_updated":"2024-12-20T05:36:19Z","snapshot_observed_at":"2026-08-12T16:06:59.253892Z","submitted_at":"2024-12-20T05:36:19Z","title":"Adversarial Robustness through Dynamic Ensemble Learning","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-11T11:22:20.052240Z"},"links":{"citing_paper":"/paper/2412.16254"},"observation_digest":"sha256:3bd3e85fd41ec2bfde42f8cce605268fbd56d11bc7429b8f8a66056db76992b4","observation_id":"00055ddb-cbd6-41ae-97d6-eede3c283899","resolution":{"observed_at":"2026-08-11T11:22:20.764977Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T11:22:20.733980Z","title":"Phrase-level textual adversarial attack with label preservationn,","venue":null,"work_id":"077955c8-3dbd-4686-ab16-490921dfd703","year":2022},"citing_paper":{"arxiv_id":"2412.16254","last_updated":"2024-12-20T05:36:19Z","snapshot_observed_at":"2026-08-12T16:06:59.253892Z","submitted_at":"2024-12-20T05:36:19Z","title":"Adversarial Robustness through Dynamic Ensemble Learning","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-11T11:22:20.059944Z"},"links":{"citing_paper":"/paper/2412.16254"},"observation_digest":"sha256:e2000c6ee74e36dd212d0579c3a48ab7b7415e0615820a31000174552eae0e56","observation_id":"235d9f90-eb17-4661-a6da-42983d007c4b","resolution":{"observed_at":"2026-08-11T11:22:20.743165Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T11:22:20.713286Z","title":"Explaining and harnessing adversarial examples","venue":null,"work_id":"a3d1dd03-9eb6-4753-b71a-5e01b2a0e50f","year":2015},"citing_paper":{"arxiv_id":"2412.16254","last_updated":"2024-12-20T05:36:19Z","snapshot_observed_at":"2026-08-12T16:06:59.253892Z","submitted_at":"2024-12-20T05:36:19Z","title":"Adversarial Robustness through Dynamic Ensemble Learning","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-11T11:22:20.071042Z"},"links":{"citing_paper":"/paper/2412.16254"},"observation_digest":"sha256:3985274282d8d3d555bef64cfe4726ec2b30719de5e7354aaf3eb56055fcad64","observation_id":"c15beb32-aa4f-4023-bf82-0252cdca68aa","resolution":{"observed_at":"2026-08-11T11:22:20.720814Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T11:22:20.685024Z","title":"Estimating raining data influence by tracing gradient descent","venue":null,"work_id":"ba05a081-6ad7-44b5-b26e-6019b192939a","year":2020},"citing_paper":{"arxiv_id":"2412.16254","last_updated":"2024-12-20T05:36:19Z","snapshot_observed_at":"2026-08-12T16:06:59.253892Z","submitted_at":"2024-12-20T05:36:19Z","title":"Adversarial Robustness through Dynamic Ensemble Learning","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-11T11:22:20.077928Z"},"links":{"citing_paper":"/paper/2412.16254"},"observation_digest":"sha256:6914732ce84e2c9df061e0cffbe0eeaabba2abe79e1ed72310ee19e113748ce5","observation_id":"fed22d08-6f10-4626-84c2-fcdc55cb27c0","resolution":{"observed_at":"2026-08-11T11:22:20.693324Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T11:22:20.661607Z","title":"Interpretable adversarial perturbation in input embedding space for text","venue":null,"work_id":"e01390f3-86a0-4394-8453-a6d8fd954626","year":2018},"citing_paper":{"arxiv_id":"2412.16254","last_updated":"2024-12-20T05:36:19Z","snapshot_observed_at":"2026-08-12T16:06:59.253892Z","submitted_at":"2024-12-20T05:36:19Z","title":"Adversarial Robustness through Dynamic Ensemble Learning","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-11T11:22:20.085426Z"},"links":{"citing_paper":"/paper/2412.16254"},"observation_digest":"sha256:fef4cd95530d4c878f97885ef07df4c29178cf67b73b69cd2239562f73fd7dc2","observation_id":"0b02d5bd-00a6-4471-8261-fe60cca3bd7c","resolution":{"observed_at":"2026-08-11T11:22:20.668488Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T11:22:20.640272Z","title":"Adversarial examples for evaluating reading comprehension systems","venue":null,"work_id":"78d35b04-fdd0-4b53-9c6b-b759eebb0f09","year":2017},"citing_paper":{"arxiv_id":"2412.16254","last_updated":"2024-12-20T05:36:19Z","snapshot_observed_at":"2026-08-12T16:06:59.253892Z","submitted_at":"2024-12-20T05:36:19Z","title":"Adversarial Robustness through Dynamic Ensemble Learning","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-11T11:22:20.093991Z"},"links":{"citing_paper":"/paper/2412.16254"},"observation_digest":"sha256:6fd4d2dd7c5780c1caf6b206d2064914f727c88ded7050f45421d285ecd92f06","observation_id":"08763c27-c44a-421d-ac98-ff03f643da37","resolution":{"observed_at":"2026-08-11T11:22:20.646642Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T11:22:20.601646Z","title":"Distillation as a defense to adversarial perturbations against deep neural networks,","venue":null,"work_id":"55c605bb-481b-4d32-b347-7fd0dd82b304","year":2016},"citing_paper":{"arxiv_id":"2412.16254","last_updated":"2024-12-20T05:36:19Z","snapshot_observed_at":"2026-08-12T16:06:59.253892Z","submitted_at":"2024-12-20T05:36:19Z","title":"Adversarial Robustness through Dynamic Ensemble Learning","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-11T11:22:20.099134Z"},"links":{"citing_paper":"/paper/2412.16254"},"observation_digest":"sha256:67d21ed10dec817b82af6e875378b181423b690942229e35287027540a611c35","observation_id":"bbee5714-8086-4709-9a52-7e4626bb7605","resolution":{"observed_at":"2026-08-11T11:22:20.625715Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.00248","last_updated":"2025-05-17T00:13:59Z","snapshot_observed_at":"2026-08-12T08:00:59.830367Z","submitted_at":"2024-06-28T22:36:17Z","title":"DiffuseDef: Improved Robustness to Adversarial Attacks via Iterative Denoising","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.00248","snapshot_observed_at":"2026-08-11T11:22:20.110938Z","title":"DiffuseDef: Improved robustness to bert adversarial attacks,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.16254","last_updated":"2024-12-20T05:36:19Z","snapshot_observed_at":"2026-08-12T16:06:59.253892Z","submitted_at":"2024-12-20T05:36:19Z","title":"Adversarial Robustness through Dynamic Ensemble Learning","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-11T11:22:20.110938Z"},"links":{"cited_paper":"/paper/2407.00248","citing_paper":"/paper/2412.16254"},"observation_digest":"sha256:24784eb493e7395bfe37fe8aa2ea8d17d79a1053e77273174e3e2c525f820634","observation_id":"eb494b67-74dc-4a10-8e1f-1d3a8b635a67","resolution":{"observed_at":"2026-08-11T11:22:20.110938Z","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":"2026-08-11T11:22:20.577894Z","title":"Randomized smoothing with masked inference for adversarially robust text classifications,","venue":null,"work_id":"f1154421-11b1-4a20-bce8-12f5e407c2f2","year":2023},"citing_paper":{"arxiv_id":"2412.16254","last_updated":"2024-12-20T05:36:19Z","snapshot_observed_at":"2026-08-12T16:06:59.253892Z","submitted_at":"2024-12-20T05:36:19Z","title":"Adversarial Robustness through Dynamic Ensemble Learning","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-11T11:22:20.120775Z"},"links":{"citing_paper":"/paper/2412.16254"},"observation_digest":"sha256:4fec8f9dc1e9a7759e250c012c7bed65c11b0e3c387ecbb9648ae6cbff83805a","observation_id":"dff1dd2d-834d-47f1-ac36-5dec60739d1b","resolution":{"observed_at":"2026-08-11T11:22:20.584764Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T11:22:20.556266Z","title":"Is bert really robust? A strong baseline for natural language attack on text classification and entailment,","venue":null,"work_id":"f14f7283-fde7-494c-8d01-f316aa7f6f4a","year":2020},"citing_paper":{"arxiv_id":"2412.16254","last_updated":"2024-12-20T05:36:19Z","snapshot_observed_at":"2026-08-12T16:06:59.253892Z","submitted_at":"2024-12-20T05:36:19Z","title":"Adversarial Robustness through Dynamic Ensemble Learning","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-11T11:22:20.131132Z"},"links":{"citing_paper":"/paper/2412.16254"},"observation_digest":"sha256:55014b523891c122072e1383c843a476a5f2c696c7ed87c8e5c57ffa42bcde69","observation_id":"cefb25ae-64cf-4ad9-9408-033d3a5e7429","resolution":{"observed_at":"2026-08-11T11:22:20.563261Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T11:22:20.530801Z","title":"TextBugger: Generating adversarial text against real -world applications,","venue":null,"work_id":"fac0acb6-8599-49d4-9c84-b32d0deb5dae","year":2019},"citing_paper":{"arxiv_id":"2412.16254","last_updated":"2024-12-20T05:36:19Z","snapshot_observed_at":"2026-08-12T16:06:59.253892Z","submitted_at":"2024-12-20T05:36:19Z","title":"Adversarial Robustness through Dynamic Ensemble Learning","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-11T11:22:20.138575Z"},"links":{"citing_paper":"/paper/2412.16254"},"observation_digest":"sha256:48764ab79df57b247b554b5f3d16f2ecdb4f85629153301e373f333354a1f457","observation_id":"368a9c64-33f2-4d58-8614-0b11bb8f63b8","resolution":{"observed_at":"2026-08-11T11:22:20.537410Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T11:22:20.505627Z","title":"BERT-Attack: Adversarial attack against BERT using BERT,","venue":null,"work_id":"a429249b-6799-4238-8054-76d1f4a75827","year":2020},"citing_paper":{"arxiv_id":"2412.16254","last_updated":"2024-12-20T05:36:19Z","snapshot_observed_at":"2026-08-12T16:06:59.253892Z","submitted_at":"2024-12-20T05:36:19Z","title":"Adversarial Robustness through Dynamic Ensemble Learning","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-11T11:22:20.145903Z"},"links":{"citing_paper":"/paper/2412.16254"},"observation_digest":"sha256:998f917544c08b07cb2c0b7a677c71b72e17366c49c1404c3dce6a58759d7b32","observation_id":"f4c48e81-97fd-4bbd-a636-ce4c312f4ada","resolution":{"observed_at":"2026-08-11T11:22:20.513581Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T11:22:20.481829Z","title":"Character-level Convolutional Networks for Text Classification,","venue":null,"work_id":"4be3e9a7-7709-48a6-b344-f5043fba26a3","year":2015},"citing_paper":{"arxiv_id":"2412.16254","last_updated":"2024-12-20T05:36:19Z","snapshot_observed_at":"2026-08-12T16:06:59.253892Z","submitted_at":"2024-12-20T05:36:19Z","title":"Adversarial Robustness through Dynamic Ensemble Learning","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-11T11:22:20.152427Z"},"links":{"citing_paper":"/paper/2412.16254"},"observation_digest":"sha256:216ac7baed7f50ab653667d254aaaf9c75345beec2b1f46ba2aa04c665dc0744","observation_id":"665e10be-bbea-46cd-aa03-90aff171e08f","resolution":{"observed_at":"2026-08-11T11:22:20.486801Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T11:22:20.462443Z","title":"Learning word vectors for sentiment analysis,","venue":null,"work_id":"540a297b-5b9c-4ec2-9e5f-196c4ba51857","year":2011},"citing_paper":{"arxiv_id":"2412.16254","last_updated":"2024-12-20T05:36:19Z","snapshot_observed_at":"2026-08-12T16:06:59.253892Z","submitted_at":"2024-12-20T05:36:19Z","title":"Adversarial Robustness through Dynamic Ensemble Learning","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-11T11:22:20.157780Z"},"links":{"citing_paper":"/paper/2412.16254"},"observation_digest":"sha256:da591234eefadca5b58e324f6ba3cad1ae9f31a228d2f846baf22cd7a0b88a41","observation_id":"e6e82ea9-17b2-4bc5-b246-dc681be49df1","resolution":{"observed_at":"2026-08-11T11:22:20.467980Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T11:22:20.441382Z","title":"GLUE: A multi -task benchmark and analysis platform for natural language understanding,","venue":null,"work_id":"836175a8-11c5-4c39-8633-7d9a3bd2df8a","year":2018},"citing_paper":{"arxiv_id":"2412.16254","last_updated":"2024-12-20T05:36:19Z","snapshot_observed_at":"2026-08-12T16:06:59.253892Z","submitted_at":"2024-12-20T05:36:19Z","title":"Adversarial Robustness through Dynamic Ensemble Learning","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-11T11:22:20.163896Z"},"links":{"citing_paper":"/paper/2412.16254"},"observation_digest":"sha256:4b52687fd5d397e007446f76bc057acd763d84ee55571476ea36566d353275a0","observation_id":"0dd8e30a-8aa1-4939-99a1-25b12fcea3b8","resolution":{"observed_at":"2026-08-11T11:22:20.448934Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T11:22:20.417408Z","title":"A broad-coverage challenge corpus for sentence understanding through inference,","venue":null,"work_id":"20a8bfc7-71f0-439e-b184-58dd567306ee","year":2018},"citing_paper":{"arxiv_id":"2412.16254","last_updated":"2024-12-20T05:36:19Z","snapshot_observed_at":"2026-08-12T16:06:59.253892Z","submitted_at":"2024-12-20T05:36:19Z","title":"Adversarial Robustness through Dynamic Ensemble Learning","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-11T11:22:20.170800Z"},"links":{"citing_paper":"/paper/2412.16254"},"observation_digest":"sha256:f975338aa7bbb27bc5c169cf3ef0aa736067cc8e86c35c26f8ab318bf67884ac","observation_id":"0490d4ab-f69c-4c98-a066-ff5df9b9c860","resolution":{"observed_at":"2026-08-11T11:22:20.423420Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T11:22:20.398169Z","title":"BERT: Pre - training of deep bi -directional transformers for language understanding,","venue":null,"work_id":"80879a8c-f61f-4828-a12e-37b531f29cc5","year":2019},"citing_paper":{"arxiv_id":"2412.16254","last_updated":"2024-12-20T05:36:19Z","snapshot_observed_at":"2026-08-12T16:06:59.253892Z","submitted_at":"2024-12-20T05:36:19Z","title":"Adversarial Robustness through Dynamic Ensemble Learning","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-11T11:22:20.176790Z"},"links":{"citing_paper":"/paper/2412.16254"},"observation_digest":"sha256:c065797840a430542b0816e7f4752e57063a264aa1b4bf435fae10c976be36d9","observation_id":"ddc5eebc-42bb-4271-a720-49ca46cd0feb","resolution":{"observed_at":"2026-08-11T11:22:20.404040Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1907.11692","last_updated":"2019-07-26T17:48:29Z","snapshot_observed_at":"2026-07-31T22:31:37.910868Z","submitted_at":"2019-07-26T17:48:29Z","title":"RoBERTa: A Robustly Optimized BERT Pretraining Approach","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1907.11692","snapshot_observed_at":"2026-08-11T11:22:20.182235Z","title":"RoBERTa: A robustly optimized BERT pretraining approach,","venue":null,"work_id":null,"year":1907},"citing_paper":{"arxiv_id":"2412.16254","last_updated":"2024-12-20T05:36:19Z","snapshot_observed_at":"2026-08-12T16:06:59.253892Z","submitted_at":"2024-12-20T05:36:19Z","title":"Adversarial Robustness through Dynamic Ensemble Learning","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-11T11:22:20.182235Z"},"links":{"cited_paper":"/paper/1907.11692","citing_paper":"/paper/2412.16254"},"observation_digest":"sha256:0bdcf5b2871d56e12e0898a87923e542040dd2127f55c81baa3a19becb8d9e9e","observation_id":"a4196b7a-5c54-442b-844c-ae7fc2fa2cb6","resolution":{"observed_at":"2026-08-11T11:22:20.182235Z","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":"2026-08-11T11:22:20.378429Z","title":"ALBERT: A lite BERT for self -supervised learning of language representations,","venue":null,"work_id":"b3c93aff-1c23-4935-b001-c2f5233dd2ec","year":2020},"citing_paper":{"arxiv_id":"2412.16254","last_updated":"2024-12-20T05:36:19Z","snapshot_observed_at":"2026-08-12T16:06:59.253892Z","submitted_at":"2024-12-20T05:36:19Z","title":"Adversarial Robustness through Dynamic Ensemble Learning","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-11T11:22:20.189184Z"},"links":{"citing_paper":"/paper/2412.16254"},"observation_digest":"sha256:d665fd3ac4dc0d30a6c4821cc58c973ad43f0be9e8c989af5076401dde673efe","observation_id":"4c416917-680f-4c4f-8c72-36374807dd9e","resolution":{"observed_at":"2026-08-11T11:22:20.384027Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T11:22:20.360723Z","title":"InfoBERT: Improving robustness of lang uage models from an information theoretic perspective,","venue":null,"work_id":"3dcee0cb-9d16-4356-a86c-9753e17b9434","year":2021},"citing_paper":{"arxiv_id":"2412.16254","last_updated":"2024-12-20T05:36:19Z","snapshot_observed_at":"2026-08-12T16:06:59.253892Z","submitted_at":"2024-12-20T05:36:19Z","title":"Adversarial Robustness through Dynamic Ensemble Learning","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-11T11:22:20.194776Z"},"links":{"citing_paper":"/paper/2412.16254"},"observation_digest":"sha256:68430bfeee8e788588ab9390a71cb49396919c2a97bf9973d28e6738f186c687","observation_id":"b8d44a70-3d74-406f-8e0b-a22a2e4a0853","resolution":{"observed_at":"2026-08-11T11:22:20.365944Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T11:22:20.340201Z","title":"Searching for an effective defender: Benchmarking defense against adversarial word substitution,","venue":null,"work_id":"5d1aa1bc-7ca9-4269-9ae2-77d278dc0eb3","year":2021},"citing_paper":{"arxiv_id":"2412.16254","last_updated":"2024-12-20T05:36:19Z","snapshot_observed_at":"2026-08-12T16:06:59.253892Z","submitted_at":"2024-12-20T05:36:19Z","title":"Adversarial Robustness through Dynamic Ensemble Learning","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-11T11:22:20.200422Z"},"links":{"citing_paper":"/paper/2412.16254"},"observation_digest":"sha256:7b137031d71478284df5618acb1f934e21b720f3f2f17a11b1c76d69b7c5a575","observation_id":"1339ee51-a8c3-406f-a1cb-89ec2ca4bbad","resolution":{"observed_at":"2026-08-11T11:22:20.347969Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1909.11764","last_updated":"2020-04-23T07:19:00Z","snapshot_observed_at":"2026-08-12T16:06:14.773530Z","submitted_at":"2019-09-25T20:50:32Z","title":"FreeLB: Enhanced Adversarial Training for Natural Language Understanding","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1909.11764","snapshot_observed_at":"2026-08-11T11:22:20.208006Z","title":"FreeLB: Enhanced adversarial training for natural language understanding,","venue":null,"work_id":null,"year":1909},"citing_paper":{"arxiv_id":"2412.16254","last_updated":"2024-12-20T05:36:19Z","snapshot_observed_at":"2026-08-12T16:06:59.253892Z","submitted_at":"2024-12-20T05:36:19Z","title":"Adversarial Robustness through Dynamic Ensemble Learning","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-11T11:22:20.208006Z"},"links":{"cited_paper":"/paper/1909.11764","citing_paper":"/paper/2412.16254"},"observation_digest":"sha256:e3f77371c8295e1ff4177cc433cc1808c93146b12d6f82611d75e6bf2793cac5","observation_id":"c5db83b5-bd35-4cb9-b4b7-693fe555ddc7","resolution":{"observed_at":"2026-08-11T11:22:20.208006Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2412.16254","last_updated":"2024-12-20T05:36:19Z","latest_version":1,"primary_category":"cs.CR","snapshot_observed_at":"2026-08-12T16:06:59.253892Z","submitted_at":"2024-12-20T05:36:19Z","title":"Adversarial Robustness through Dynamic Ensemble Learning"},"reference_resolution":{"displayed":28,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":4,"verified_exact":0,"verified_fuzzy":24},"total_outbound_references":28},"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":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"thesis":"As of 12 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 0 inbound Pith citation observations for arXiv:2412.16254."}