{"as_of":"2026-08-15T11:04:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:7efd621829d8633f76ebd0a252ecb38308880d3704d09311ae85557b8782f0cb","coverage":[{"denominator":68,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":68,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-14T14:26:39.775562Z","state":"measured"},{"denominator":70,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":70,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-15T06:32:42.880941+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T04:08:37.186446Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-07-02T16:27:08.926506Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1908.03173","snapshot_observed_at":"2026-08-07T04:08:37.186446Z","title":"arXiv preprint arXiv:1908.03173 (2019)","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2506.11521","last_updated":"2025-06-13T07:22:36Z","snapshot_observed_at":"2026-08-14T07:45:07.248965Z","submitted_at":"2025-06-13T07:22:36Z","title":"Investigating Vulnerabilities and Defenses Against Audio-Visual Attacks: A Comprehensive Survey Emphasizing Multimodal Models","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-07T04:08:37.186446Z"},"links":{"cited_paper":"/paper/1908.03173","citing_paper":"/paper/2506.11521"},"observation_digest":"sha256:99933a0eb562f44acf02c22d38c2e02e03dc7ac1827203ebdce9c4d1c46929cd","observation_id":"5e952512-06f4-49e2-9de6-ac5ce587f6f9","resolution":{"observed_at":"2026-08-07T04:08:37.186446Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"cited_work":{"arxiv_id":"1908.03173","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1908.03173","snapshot_observed_at":"2026-07-02T16:27:08.926506Z","title":"Hafemann, Jerome Rony, Ismail Ben Ayed, Patrick Cardinal, and Alessan- dro L","venue":null,"work_id":"639d963e-41e0-460f-be85-2a47d59bc4e4","year":1908},"citing_paper":{"arxiv_id":"2606.06833","last_updated":"2026-06-05T02:18:23Z","snapshot_observed_at":"2026-07-06T23:46:33.376471Z","submitted_at":"2026-06-05T02:18:23Z","title":"Hearing the Unspoken: Language Model Priors for Acoustic Adversarial Attacks","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-06-27T22:45:50.928636Z"},"links":{"cited_paper":"/paper/1908.03173","citing_paper":"/paper/2606.06833"},"observation_digest":"sha256:b37667d68a62f24ffa0c85eef0e35ad700b38350622f1cb5dbe8c8a88c2a1bb4","observation_id":"ce8cfe29-59a7-463f-963b-2f1a5a251d02","resolution":{"observed_at":"2026-07-02T16:27:08.927938Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/1908.03173/citation-record","integrity":"/paper/1908.03173/integrity","json":"/paper/1908.03173/citation-record.json","paper":"/paper/1908.03173"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:26:40.690949Z","title":"Object detection with deep learning: A review,","venue":null,"work_id":"e755c500-15a2-4d45-83e6-4987de26fd96","year":2019},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.564746Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:08d341ba6944e5d9490c2922f6e1229999798cdeabf59f167b28baca22fcb6ee","observation_id":"42affafc-3f1b-45de-be83-f6cae8e78cdf","resolution":{"observed_at":"2026-08-14T14:26:40.694977Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T14:26:40.682243Z","title":"Multilingual anchoring: Interactive topic modeling and alignment across languages,","venue":null,"work_id":"63afc111-b1ea-4342-8ead-3aae47b365b6","year":2018},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.568964Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:012e409dfcab3f5594641d4e2c3a91f1f25c8db6650ab1369ee2c70901949a5a","observation_id":"8e584608-52ed-4976-9d63-7b9e7e53146a","resolution":{"observed_at":"2026-08-14T14:26:40.685711Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T14:26:40.673412Z","title":"Unsupervised text style transfer using language models as dis- criminators,","venue":null,"work_id":"daef78c1-2263-4b79-b1de-ee477af57fc3","year":2018},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.572382Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:4d186f362dea33f0cfa7edf5a8dc9a4674e9c9f7ddcfb03618b635fc3bcbcedd","observation_id":"15e9fba5-9ed7-4113-acf4-ccf33899fd1d","resolution":{"observed_at":"2026-08-14T14:26:40.677088Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T14:26:40.663922Z","title":"Transfer learning from speaker verification to multispeaker text-to-speech synthesis,","venue":null,"work_id":"92261106-7ca9-422e-a9ad-18486dfef626","year":2018},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.576033Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:740f145299973b518a648448c28babe93baa78b69e80dcf3099e7ab040fc3222","observation_id":"bf4eec48-6a9c-42af-8983-344fed27184c","resolution":{"observed_at":"2026-08-14T14:26:40.667333Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T14:26:40.655493Z","title":"Unsupervised cross-modal alignment of speech and text embedding spaces,","venue":null,"work_id":"ebd8a584-416e-4523-9940-bf6a5811b513","year":2018},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.579360Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:6634d65fad8ee04a08aaac748285ab5ce50f55bb946d656ca55207d4d18100bf","observation_id":"cdac56bf-9ec1-4ec5-9a0e-476fd70f3b2e","resolution":{"observed_at":"2026-08-14T14:26:40.658645Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T14:26:40.646393Z","title":"Intriguing properties of neural networks,","venue":null,"work_id":"c990d92c-bd15-4d7f-9816-061b6522dd71","year":2014},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.582583Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:8799912e486580f578b4a144417ec663e87e5a836719b8e3fc9c7e101f7832cd","observation_id":"45880274-897e-4bcd-972c-fd6c09e1f3a2","resolution":{"observed_at":"2026-08-14T14:26:40.649513Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T14:26:40.637548Z","title":"Explaining and Har- nessing Adversarial Examples,","venue":null,"work_id":"4b48663b-d121-4ef0-80be-b03fbf6f4b62","year":2015},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.585948Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:acd61a53b0d573feb5687dba47edd73aa03987b97130e95d6ce172ea51f43edd","observation_id":"cfe11c97-b3ac-4f6d-8445-d8c4701d46c2","resolution":{"observed_at":"2026-08-14T14:26:40.640880Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T14:26:40.628838Z","title":"Towards evaluating the robustness of neural networks,","venue":null,"work_id":"2d08aae0-542d-4753-9af4-3c0b3bbff6d4","year":2017},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.588877Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:080c154b7c940769f17bd0d7e3aa550daa1a03669583116cc78061942ef785ac","observation_id":"e8b23386-af0f-4649-92f8-bf6dc3058b48","resolution":{"observed_at":"2026-08-14T14:26:40.632250Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T14:26:40.619294Z","title":"Threat of adversarial attacks on deep learning in computer vision: A survey,","venue":null,"work_id":"4303d1b1-5207-4354-9701-928f54f2f019","year":2018},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.591753Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:c88aa1e976b214c0230ecef8a89affaedd66c34bff632840492f201ed60f044a","observation_id":"9b474184-c161-4142-9c62-4b6b724a172d","resolution":{"observed_at":"2026-08-14T14:26:40.622759Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1902.03020","last_updated":"2020-11-29T08:38:50Z","snapshot_observed_at":"2026-08-14T17:19:14.214836Z","submitted_at":"2019-02-08T11:14:08Z","title":"On the security relevance of weights in deep learning","version":2},"cited_work":{"arxiv_id":"1902.03020","doi":null,"metadata_source":"pith","pith_arxiv_id":"1902.03020","snapshot_observed_at":"2026-08-14T14:26:40.051232Z","title":"On the security relevance of weights in deep learning","venue":"cs.CR","work_id":"859137f3-bc4c-4687-9163-a4b67e540893","year":2019},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.594561Z"},"links":{"cited_paper":"/paper/1902.03020","citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:94d96bdd177593e4abc823708e486e80ecf8c14b5c55882b3b4c78a01bda2e18","observation_id":"49803a54-5df7-4bea-b4fc-2182b63360d6","resolution":{"observed_at":"2026-08-14T14:26:40.055334Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T14:26:40.610266Z","title":"Cross-representation transferability of adversarial attacks: From spectrograms to audio waveforms,","venue":null,"work_id":"2d604276-6871-4ced-a248-4b538537c4a1","year":2020},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.598141Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:9f981cb5cf45f5e94b8727e61afd2e750c618801cd72dc9d6bf428d7e57255a8","observation_id":"97732fec-aaf8-4573-840b-797c3897c86e","resolution":{"observed_at":"2026-08-14T14:26:40.613864Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T14:26:40.601568Z","title":"Wild patterns: Ten years after the rise of adversarial machine learning,","venue":null,"work_id":"0ec3dc53-0239-4dae-bec7-74c76bf7618a","year":2018},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.601407Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:3b23c9c4dd9a6ec54b2bca650fee72e0dd0e87545db34dfba3eeb1166fca1216","observation_id":"5fdbc347-24b7-4f34-a7b9-ff9a2f43a704","resolution":{"observed_at":"2026-08-14T14:26:40.605002Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"8450.8610","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:26:40.035222Z","title":"Knockoff nets: Stealing functionality of black-box models,","venue":null,"work_id":"fe2ce954-74df-4888-a4b0-56e77fd55620","year":2019},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.604496Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:e46172cb50ccdecd26e07868dc2598873977225309966217bd2eba07951c8577","observation_id":"b6c8e03d-0282-43e1-8dcf-02932ddd7e81","resolution":{"observed_at":"2026-08-14T14:26:40.040183Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T14:26:40.592747Z","title":"Universal adversarial perturbations,","venue":null,"work_id":"fa599e36-fde6-461b-bbad-c8559773fe81","year":2017},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.607540Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:cac032e99f3fabaafd7ed9cf7fb960bea9f56c61a063b429d8d3ae3601843bcf","observation_id":"6d8fe745-a81a-4b4f-9242-e859d5f41cdb","resolution":{"observed_at":"2026-08-14T14:26:40.596091Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1412.5567","last_updated":"2014-12-19T21:36:13Z","snapshot_observed_at":"2026-08-14T23:07:07.038301Z","submitted_at":"2014-12-17T20:39:45Z","title":"Deep Speech: Scaling up end-to-end speech recognition","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1412.5567","snapshot_observed_at":"2026-08-14T14:26:39.610366Z","title":"Deep speech: Scaling up end-to-end speech recognition,","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.610366Z"},"links":{"cited_paper":"/paper/1412.5567","citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:890b76d44880ae823a529d0fab99180c07144a984dc80c186cf6e9c2c9bad971","observation_id":"bbb72529-0580-4065-a687-141580d91046","resolution":{"observed_at":"2026-08-14T14:26:39.610366Z","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":"2026-08-14T14:26:40.582983Z","title":"Speech acoustic mod- eling from raw multichannel waveforms,","venue":null,"work_id":"dffe55f6-b92a-4698-a15b-354592ec7f1e","year":2015},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.613908Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:4d977bafa7ec5d14e35cad308e6b9c477837034a5262e5e62c901ad4663e1848","observation_id":"8efc910b-fadf-4885-97d4-965ec5e8f0bf","resolution":{"observed_at":"2026-08-14T14:26:40.586185Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T14:26:40.573943Z","title":"Wavenet: A generative model for raw audio,","venue":null,"work_id":"2de0ce0c-4920-4962-b8da-e7d80bbf3b7e","year":2016},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.616912Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:731b2b1160f09a4ef7011383f4f3412d121c3d633617a02c30b88a5970b82f28","observation_id":"954ac846-7841-4bfa-a88a-73becbfc30dc","resolution":{"observed_at":"2026-08-14T14:26:40.577153Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T14:26:40.565103Z","title":"Learning the speech front-end with raw waveform CLDNNs,","venue":null,"work_id":"f88dee44-e236-4acd-b89f-b83c59d892d8","year":2015},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.620072Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:ab0855ff604d3b79f448d28da3f60ac990d6fbf4bbd2cda5205b9f0fb9f8cbf4","observation_id":"135b5eb2-13cf-4a20-8e49-5d7279078da5","resolution":{"observed_at":"2026-08-14T14:26:40.568466Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T14:26:40.555893Z","title":"Speaker recognition from raw wave- form with SincNet,","venue":null,"work_id":"64b285a2-43cb-483c-8f1f-d15172b044b7","year":2018},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.623132Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:425d6d0d377bc3b0022f1994fb2175131af6dba7d14841f77b7fe45bee37abd9","observation_id":"78a20c73-29f5-4c48-ac58-fd208382ab19","resolution":{"observed_at":"2026-08-14T14:26:40.559730Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T14:26:40.546397Z","title":"Learning filterbanks from raw speech for phone recognition,","venue":null,"work_id":"857aaab7-293d-448b-b906-519fc3fb3a9f","year":2018},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.626386Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:55d634fc65f18a37a8052b6b2a5ce0cdb6a4272ec7772b15911406fedff25399","observation_id":"105d7d10-5cee-4d40-aba1-4ba47dfa0375","resolution":{"observed_at":"2026-08-14T14:26:40.550349Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T14:26:40.537087Z","title":"End-to-end speech recognition from the raw wave- form,","venue":null,"work_id":"05fc0fd1-dc1c-4f2f-af1b-db14942e70d1","year":2018},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.629305Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:ee88546beaf4eb629c5f2e7723723d62b99fed43dbb9cef7eb7fda30d5b13b4b","observation_id":"44784f24-c6fd-47a2-956a-33d1963de28e","resolution":{"observed_at":"2026-08-14T14:26:40.540336Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T14:26:40.528023Z","title":"Audio adversarial examples: Targeted attacks on speech-to-text,","venue":null,"work_id":"c5a4398b-e330-4952-9015-a396227a4ee5","year":2018},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.632364Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:8a67dced4eb4c8c4e24ad73ca25e667e3658a428ab888092d78c7f4417c897d5","observation_id":"a2c8d722-3485-4784-8d5a-4d0a80b51d87","resolution":{"observed_at":"2026-08-14T14:26:40.531937Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2007.06622","last_updated":"2020-07-21T17:42:56Z","snapshot_observed_at":"2026-07-06T09:37:50.874824Z","submitted_at":"2020-07-13T18:52:25Z","title":"SoK: The Faults in our ASRs: An Overview of Attacks against Automatic Speech Recognition and Speaker Identification Systems","version":3},"cited_work":{"arxiv_id":"2007.06622","doi":null,"metadata_source":"pith","pith_arxiv_id":"2007.06622","snapshot_observed_at":"2026-08-14T14:26:39.891378Z","title":"SoK: The Faults in our ASRs: An Overview of Attacks against Automatic Speech Recognition and Speaker Identification Systems","venue":"cs.CR","work_id":"ed671ad9-586d-480e-b4de-3eaed7160089","year":2020},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.635289Z"},"links":{"cited_paper":"/paper/2007.06622","citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:5866a565b61b2db859b959d057ccf4c2e6cc273c2af607a529086064ded8372c","observation_id":"323bcdd8-741a-4f46-bf8f-06325285da28","resolution":{"observed_at":"2026-08-14T14:26:39.895355Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T14:26:40.519592Z","title":"Lower bounds on the robustness to adversarial perturbations,","venue":null,"work_id":"cf54ae84-48b8-4548-b60c-84032904c625","year":2017},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.638524Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:b3c34d79d8badf7cf90bab4c39608dbdd392116c91fc4251e051547458d651dc","observation_id":"b2ad5500-aa7e-48bb-9aef-10574e39cce6","resolution":{"observed_at":"2026-08-14T14:26:40.522781Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T14:26:40.510228Z","title":"Are adversarial examples inevitable?","venue":null,"work_id":"2cac594c-84e4-4ef5-870f-fb2360ea6b02","year":2019},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.641674Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:9b730e05c95cc7568dd543f72ce6ac359820d56e7c1d8f95b4c7d23653e84f5c","observation_id":"8034af43-e44d-4029-a88b-51367a4c17f8","resolution":{"observed_at":"2026-08-14T14:26:40.513512Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T14:26:40.500290Z","title":"Adversarial vulnerability for any classifier,","venue":null,"work_id":"9dd29f32-083a-4b4e-80eb-3e1e826f17a3","year":2018},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.644769Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:87d58a0c37003733ae095a2b8c0dc0dc1ec482aa2ff8ceba7b9a57d3460e2fc1","observation_id":"66f95460-66fc-427e-96ab-38a8f5534f0b","resolution":{"observed_at":"2026-08-14T14:26:40.503522Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T14:26:40.489742Z","title":"Adversarial examples in the physical world,","venue":null,"work_id":"55bca587-be51-428d-b5b9-ced6fd5b8ed0","year":2017},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.647677Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:e5cd8a1a867c50585918bea1bc34d1393add82dfa9b2d4fe106e5019331aa18b","observation_id":"f4c2f481-c3af-4cdc-866a-509cdd98222a","resolution":{"observed_at":"2026-08-14T14:26:40.493713Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T14:26:40.480196Z","title":"Synthesizing Robust Adversarial Examples,","venue":null,"work_id":"7774adc1-12ba-4044-b02c-a59350314cf2","year":2018},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.650912Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:03cf359b1bed21950ab7b83450c0262459d19b700138a868843d259f3b22daac","observation_id":"15ad8e5f-1627-4904-8b5e-3dc031889165","resolution":{"observed_at":"2026-08-14T14:26:40.484362Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T14:26:40.471787Z","title":"Hidden voice commands,","venue":null,"work_id":"6607a933-9fcd-496c-8bb6-1cb18cc864ea","year":2016},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.653811Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:d19a6bd923858d13aa4486f8a1a7b967685e783f739941875a0a77ce09dff819","observation_id":"fcabd10b-f127-4c67-a556-08695b2c9f79","resolution":{"observed_at":"2026-08-14T14:26:40.474925Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T14:26:40.462780Z","title":"Dolphi- nattack: Inaudible voice commands,","venue":null,"work_id":"a7c122b1-8662-4728-84e1-b44d5394c713","year":2017},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.657032Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:539defbafa0376dba7d503729a64ee0c02796ba6dccba340f0512fa45451bd7a","observation_id":"d54ba917-c0c4-40d1-804b-9b9c1f1b073d","resolution":{"observed_at":"2026-08-14T14:26:40.466509Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1711.03280","last_updated":"2019-01-11T06:57:33Z","snapshot_observed_at":"2026-08-14T20:15:24.831311Z","submitted_at":"2017-11-09T07:41:53Z","title":"Crafting Adversarial Examples For Speech Paralinguistics Applications","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1711.03280","snapshot_observed_at":"2026-08-14T14:26:39.660243Z","title":"Crafting adversarial examples for speech paralinguistics applications,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.660243Z"},"links":{"cited_paper":"/paper/1711.03280","citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:0299d622746f165dadf3b6ba131c8d4cebe584b855af2113c4f7016945b2bb76","observation_id":"e3e1e333-1935-4ab1-a3b8-821d84bffa72","resolution":{"observed_at":"2026-08-14T14:26:39.660243Z","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":"2026-08-14T14:26:40.453030Z","title":"Deep learning and music adversaries,","venue":null,"work_id":"4bed0730-1c67-4c9b-910c-2f34718ad43d","year":2015},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.663545Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:57f807f5aebffbed44d3611f914945ff0c5dfee045820214d6abaa78b56a49f1","observation_id":"16f1c541-ca18-47c4-82ca-159f3f1616e2","resolution":{"observed_at":"2026-08-14T14:26:40.457279Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T14:26:40.443788Z","title":"Sirenattack: Generating adversarial audio for end-to-end acoustic systems,","venue":null,"work_id":"4ac6a6dd-829b-4e8b-abb4-dd5a102866a8","year":2020},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.666498Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:56d0467c1af3c96c0110a618b1587ab62d6133444be6224758f73568b22bd844","observation_id":"34614abb-c535-49ae-a226-868fc3d8307e","resolution":{"observed_at":"2026-08-14T14:26:40.447170Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1801.00554","last_updated":"2018-01-02T05:24:30Z","snapshot_observed_at":"2026-08-14T19:58:41.864726Z","submitted_at":"2018-01-02T05:24:30Z","title":"Did you hear that? Adversarial Examples Against Automatic Speech Recognition","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1801.00554","snapshot_observed_at":"2026-08-14T14:26:39.669574Z","title":"Did you hear that? adversarial examples against automatic speech recognition,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.669574Z"},"links":{"cited_paper":"/paper/1801.00554","citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:b42409839da4024f50eacb182f018ad5fb35e4016be0cd8aa6fa36deedf0d561","observation_id":"1a05e8c4-5634-4152-a420-fb978dd3dbe7","resolution":{"observed_at":"2026-08-14T14:26:39.669574Z","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":"2026-08-14T14:26:40.434286Z","title":"Convolutional neural networks for small-footprint keyword spotting,","venue":null,"work_id":"bafa6e94-e196-4815-a8cc-5ae6a27e96cb","year":2015},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.673163Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:0efe913e295af8836a59d6369f26d777ab85657b9af33a6e99d6d45fce7068ba","observation_id":"0a92d1c5-747d-4441-8aa9-5550ab69645f","resolution":{"observed_at":"2026-08-14T14:26:40.437966Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T14:26:40.422808Z","title":"Robust audio adversarial example for a physical attack,","venue":null,"work_id":"4e928e15-a479-4d93-96f6-ff4151b48509","year":2019},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.676332Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:d8297cd005953dc028c67fc28cab164aac96c9990c2da28670a9ce1238c409e1","observation_id":"ebf6f359-758b-400c-b2c2-417770de79ff","resolution":{"observed_at":"2026-08-14T14:26:40.427289Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T14:26:40.413289Z","title":"Imperceptible, robust, and targeted adversarial examples for automatic speech recognition,","venue":null,"work_id":"df679419-791a-4a81-8794-dc2641606c29","year":2019},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.679433Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:5d19ca03699a05d8c81f6475791dc40eeca11d9da048c3e5686f2f5f3d39752c","observation_id":"cb21d528-591c-4012-bc04-223f864c972f","resolution":{"observed_at":"2026-08-14T14:26:40.417063Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T14:26:40.403119Z","title":"Robustness of classifiers to universal perturbations: A geometric perspective,","venue":null,"work_id":"13e7ef1a-ee52-4860-8cca-ba8c7133a388","year":2018},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.682460Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:6217ff7f5f8efd169f85ae866fc12d7a467b22c609527f2446c2137d99a53546","observation_id":"ee63ff93-ac58-44a3-96d3-dae12be3537d","resolution":{"observed_at":"2026-08-14T14:26:40.407349Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T14:26:40.393768Z","title":"Universal adversarial perturbations against semantic image segmentation,","venue":null,"work_id":"9b36e247-85f5-4e47-ac64-09e976d445e5","year":2017},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.685441Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:b3001912729916424079135e0661e988ca9d922e7d7a5c6d5b2d7f2a32f9f514","observation_id":"63b4db87-53cf-4ef2-b233-be8bea49fc7e","resolution":{"observed_at":"2026-08-14T14:26:40.397134Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T14:26:40.384551Z","title":"Universal adversarial attacks on text classifiers,","venue":null,"work_id":"ef84df79-2206-44cd-bf71-46507c166682","year":2019},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.688362Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:59249d73329afe0d2e007640fd8f761346a988b7396b84275cedc8a07eb55aa7","observation_id":"cb6b653c-83e1-4bbc-b5b9-2278a19a0a75","resolution":{"observed_at":"2026-08-14T14:26:40.388015Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T14:26:40.374528Z","title":"Learning universal adversarial pertur- bations with generative models,","venue":null,"work_id":"7cc4d420-1e29-4386-8d02-a92a2888073c","year":2018},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.691270Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:c096bca8ec459de821e5b81ce09f981904d0bec83438034ac8b2762773723121","observation_id":"dedc29ff-b631-4808-840d-58ffc40323c4","resolution":{"observed_at":"2026-08-14T14:26:40.378409Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T14:26:40.364475Z","title":"Universal adversarial perturbations for speech recognition systems,","venue":null,"work_id":"18c60743-5436-4659-bbf9-80f188f3d20b","year":2019},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.694224Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:ad1518dfd3b0fce618fd801ad72dcde5a22ed3f01ac0cc050c276921f3afda5c","observation_id":"89096cad-2639-480a-989e-e3c6b93c160a","resolution":{"observed_at":"2026-08-14T14:26:40.368140Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T14:26:40.353842Z","title":"Decoupling direction and norm for efficient gradient- based L2 adversarial attacks and defenses,","venue":null,"work_id":"e779ff0a-6634-461c-b8f5-730ea566c069","year":2019},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.697111Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:9e87db1bda6402f4df9abd78aa917e1f600a255cdd9693a6863ad1099f67cd91","observation_id":"c1df5d28-4a55-4c90-8a1b-ea7e58b6f6d9","resolution":{"observed_at":"2026-08-14T14:26:40.357602Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T14:26:40.244603Z","title":"Deepfool: a simple and accurate method to fool deep neural networks,","venue":null,"work_id":"7747179a-1b4f-433e-8ee8-1e074486d99d","year":2016},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.700402Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:6ebeeb56f8bd51080a089bc5c34530c10d65a5ddbd2c6081bd53e20e1b71a22b","observation_id":"dead9185-d458-4954-9ef7-3cb648382ac1","resolution":{"observed_at":"2026-08-14T14:26:40.248405Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1412.6980","last_updated":"2017-01-30T01:27:54Z","snapshot_observed_at":"2026-08-14T18:51:16.666127Z","submitted_at":"2014-12-22T13:54:29Z","title":"Adam: A Method for Stochastic Optimization","version":9},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1412.6980","snapshot_observed_at":"2026-08-14T14:26:39.703322Z","title":"Adam: A method for stochastic optimiza- tion,","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.703322Z"},"links":{"cited_paper":"/paper/1412.6980","citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:15c84a8fe40badea9af412365caf5bd5a6aead547de17e6c6dbc1656c31ec762","observation_id":"2975e393-6132-433a-ab80-c93c0d8c37ef","resolution":{"observed_at":"2026-08-14T14:26:39.703322Z","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":"2026-08-14T14:26:40.235330Z","title":"Adaptive subgradient methods for online learning and stochastic optimization,","venue":null,"work_id":"e43e5799-267b-43da-854a-af506db4e394","year":2011},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.706218Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:da6699a31590c790757cecc8b441f66ef695cb3670d9b4bc3bfc4967a257263c","observation_id":"52481fa0-ae4e-48bc-a248-2a9683ee71bf","resolution":{"observed_at":"2026-08-14T14:26:40.238751Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T14:26:40.225543Z","title":"On the impor- tance of initialization and momentum in deep learning,","venue":null,"work_id":"ce2b83c5-769b-4118-873b-dcf2f2149ef3","year":2013},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.709045Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:d1e4fe3126b64e424c29e2f6d432549a18990870913e1f92011a1e1fe145b2bc","observation_id":"e64047fa-72b7-47b8-b4af-a7b92da9c8e3","resolution":{"observed_at":"2026-08-14T14:26:40.229597Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T14:26:39.712173Z","title":"Goodfellow, Y","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.712173Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:b21ce4273b1093d7c9c67b399b76629161c41ff1ccbb4d5fe6872b30d2b72c43","observation_id":"fa63ceb4-c385-40a3-9960-4fc7465ee548","resolution":{"observed_at":"2026-08-14T14:26:39.712173Z","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":"2026-08-14T14:26:40.210606Z","title":"A dataset and taxonomy for urban sound research,","venue":null,"work_id":"eaf53777-9aa9-4c45-ae19-f11251d24dde","year":2014},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.715252Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:be764b194d3af29385ca5b5dc1c317631d9543ed6bf4495a7926bdce27e1a85c","observation_id":"1b73967f-0522-4f8a-b448-0bfebbc10a58","resolution":{"observed_at":"2026-08-14T14:26:40.214434Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1804.03209","last_updated":"2018-04-09T19:58:17Z","snapshot_observed_at":"2026-08-14T19:27:43.149965Z","submitted_at":"2018-04-09T19:58:17Z","title":"Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1804.03209","snapshot_observed_at":"2026-08-14T14:26:39.718332Z","title":"Speech commands: A dataset for limited-vocabulary speech recognition,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.718332Z"},"links":{"cited_paper":"/paper/1804.03209","citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:72c0d2d6dbc1ca5a143d68ebc95f052ce18c2135cb9495310cbcb97e07d156cb","observation_id":"467f1c4f-0d6e-4e35-b38b-bce0909e3de8","resolution":{"observed_at":"2026-08-14T14:26:39.718332Z","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":"2026-08-14T14:26:40.201595Z","title":"Learning from between- class examples for deep sound recognition,","venue":null,"work_id":"bf0d72a5-09d3-4895-8ede-70ed406426d9","year":2018},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.721666Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:0c19edbab9592b56a03c4e779f5d20ea0a62124364471258f0f0196f0c819045","observation_id":"8a216384-e919-4e98-ae52-8b31240ad1b6","resolution":{"observed_at":"2026-08-14T14:26:40.204861Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T14:26:40.192365Z","title":"End-to-end envi- ronmental sound classification using a 1D convolutional neural network,","venue":null,"work_id":"03594c8d-89d9-4541-9863-5abf0e501f18","year":2019},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.724782Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:8a8a3402273b61b133c464e273f4ab6d4b44ab98f042bbb43e510463cb2e6099","observation_id":"03e26e2c-ec90-4dc6-9c75-5060d1d5763e","resolution":{"observed_at":"2026-08-14T14:26:40.195746Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T14:26:40.183144Z","title":"Characterizing audio adversarial examples using temporal dependency,","venue":null,"work_id":"d18df33d-5569-4c4c-b0c0-b9d661c081f8","year":2019},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.727778Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:ddf341e52b80996e8a7e510b35e073c4c478f4be6269a19f77f40121ffacacd5","observation_id":"86debf37-1c96-4110-bb48-e503c88102b5","resolution":{"observed_at":"2026-08-14T14:26:40.186511Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T14:26:40.174024Z","title":"Very deep convolutional net- works for large-scale image recognition,","venue":null,"work_id":"6f93ef5b-fa64-4e01-804d-20230f7f1c9d","year":2015},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.730773Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:c78fb669591a6f0fcaaf01f311b80a36ff08d356d6382da24d3ff1ce1950d8c2","observation_id":"fc7ea7e5-8e56-489f-b089-d9fb464312b2","resolution":{"observed_at":"2026-08-14T14:26:40.177390Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1907.02477","last_updated":"2019-08-15T16:49:16Z","snapshot_observed_at":"2026-08-15T08:11:51.779864Z","submitted_at":"2019-07-04T16:15:35Z","title":"Adversarial Attacks in Sound Event Classification","version":2},"cited_work":{"arxiv_id":"1907.02477","doi":null,"metadata_source":"pith","pith_arxiv_id":"1907.02477","snapshot_observed_at":"2026-08-14T14:26:39.834216Z","title":"Adversarial Attacks in Sound Event Classification","venue":"cs.LG","work_id":"eb49cb71-bee3-4299-91e7-fd6b3549806b","year":2019},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.734038Z"},"links":{"cited_paper":"/paper/1907.02477","citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:a658684ec32cbb08e16f06f0c28c101c5180cfb601fec3ae296005e8aec8b1a6","observation_id":"0938e1b0-10bb-42dd-9075-2d73e0fe8565","resolution":{"observed_at":"2026-08-14T14:26:39.838210Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T14:26:40.163102Z","title":"Delving into transferable adversarial examples and black-box attacks,","venue":null,"work_id":"f8984c6a-6d0a-4030-ac30-4afb2d1789b6","year":2017},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.737451Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:75f56f66b9258f555a36b4afc145058eea24482ae40b61efdd29822075c6b0ee","observation_id":"431ca266-96ae-4570-af87-7ccc4d852b12","resolution":{"observed_at":"2026-08-14T14:26:40.167487Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2010.11352","last_updated":"2021-02-20T02:51:55Z","snapshot_observed_at":"2026-08-12T04:38:24.889960Z","submitted_at":"2020-10-22T00:02:02Z","title":"Class-Conditional Defense GAN Against End-to-End Speech Attacks","version":2},"cited_work":{"arxiv_id":"2010.11352","doi":null,"metadata_source":"pith","pith_arxiv_id":"2010.11352","snapshot_observed_at":"2026-08-14T14:26:39.817203Z","title":"Class-Conditional Defense GAN Against End-to-End Speech Attacks","venue":"cs.SD","work_id":"02daf995-a83b-4735-8132-c785a858d441","year":2020},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.741497Z"},"links":{"cited_paper":"/paper/2010.11352","citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:7c40affebd2839208ac106c23f056046fec58c0a52d301c4c2fa3d95d0722c95","observation_id":"dc53fe92-4009-4de4-897e-114b5d49520a","resolution":{"observed_at":"2026-08-14T14:26:39.823446Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T14:26:40.152408Z","title":"A multiversion programming inspired approach to detecting audio adversarial examples,","venue":null,"work_id":"aff78bfa-4610-4146-8bb5-e5400703386f","year":2019},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.744940Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:c716ea45c51abc1940faa3d404cb6f7c03d75c6e69c6555f79860dce0c8ea599","observation_id":"f0fa0b65-eae5-4577-90c5-e6f6d5f2789e","resolution":{"observed_at":"2026-08-14T14:26:40.156290Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T14:26:40.141875Z","title":"A robust ap- proach for securing audio classification against adversarial at- tacks,","venue":null,"work_id":"4ad73ccf-4ec8-4250-b816-2100dad1bf09","year":2019},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.748048Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:b6b83bce039cbde246e5620bdee6b6cff0a998f84b7373bb4a2a7b171a6b24df","observation_id":"fe1c0f19-c27e-4331-81c7-d38bf20feb93","resolution":{"observed_at":"2026-08-14T14:26:40.145528Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T14:26:40.131690Z","title":"Towards deep learning models resistant to adversarial attacks,","venue":null,"work_id":"124f7943-715f-4055-8241-2a1615833578","year":2018},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.751357Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:41f3731961a8d89b7e896b7c5040a4190b63aa00b0d5259da0604bcf1bfd4300","observation_id":"65039262-af2d-4f9b-bb96-397157d453c9","resolution":{"observed_at":"2026-08-14T14:26:40.135024Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T14:26:40.121306Z","title":"Train- ing augmentation with adversarial examples for robust speech recognition,","venue":null,"work_id":"881ffd35-3d9e-4775-8b24-46d55f5f7354","year":2018},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.754401Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:334f7bd0570b7df3f14cf08e5d85d3da8164d81e97d8c68c58bddb6a5dfb8029","observation_id":"1d17373f-47ca-43f2-a4b8-61c9c5e48df7","resolution":{"observed_at":"2026-08-14T14:26:40.124983Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T14:26:40.111125Z","title":"Johnson, I","venue":null,"work_id":"29f571f5-78d0-433a-ae9b-9893b6fa1d65","year":2017},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.757357Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:908619b6ffaefe13e2455cf231a57533755e555c40df6fdeb9c43edd67399bd3","observation_id":"596c166c-16cd-4ecc-90b5-1938ecadfa63","resolution":{"observed_at":"2026-08-14T14:26:40.114648Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T14:26:39.760493Z","title":"Adadelta: An adaptive learning rate method,","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.760493Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:f288ad89f9287806f143a460d8f2b6a8877da44ee4587d2db72454a8b28c0891","observation_id":"3f70b13c-b62c-48db-b207-5b586823bb26","resolution":{"observed_at":"2026-08-14T14:26:39.760493Z","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":"2026-08-14T14:26:40.094269Z","title":"Dropout: a simple way to prevent neural networks from overfitting","venue":null,"work_id":"dbe3370b-da2a-4991-a342-d960f521d45b","year":1929},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.763467Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:922eed03c4c6edd3fd9fe0230632dae19b46fd52149bc4bcf6d1d4aa43f1c565","observation_id":"1a173858-2e5a-4353-a8bc-9e86aa7f63ae","resolution":{"observed_at":"2026-08-14T14:26:40.098221Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T14:26:40.083889Z","title":"Batch normalization: Accelerating deep network training by reducing internal covariate shift,","venue":null,"work_id":"fa996159-b425-420f-99bb-56a789c7c730","year":2015},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.766476Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:dc6e9943dd74e9c026125b6f9a0a5cd213cb88257f7c1437876eafc82aacbd3b","observation_id":"bb176dd3-7dfb-44eb-8a05-08a6d552f723","resolution":{"observed_at":"2026-08-14T14:26:40.087590Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1607.06450","last_updated":"2016-07-21T19:57:52Z","snapshot_observed_at":"2026-08-15T04:53:45.483331Z","submitted_at":"2016-07-21T19:57:52Z","title":"Layer Normalization","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1607.06450","snapshot_observed_at":"2026-08-14T14:26:39.769376Z","title":"Layer normalization,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.769376Z"},"links":{"cited_paper":"/paper/1607.06450","citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:8ba44533455ce832f6f41475721532527e97a8db56cf4ca44147ccc08cde8349","observation_id":"08d8fd87-e8b3-4b85-b92f-abc2c93d2079","resolution":{"observed_at":"2026-08-14T14:26:39.769376Z","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":"2026-08-14T14:26:40.072862Z","title":"Rectifier nonlinearities improve neural network acoustic models,","venue":null,"work_id":"e062b478-b96b-4950-bca0-a5bd2bb3ac5a","year":2013},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.772584Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:f79f2cee406832a53025f10ba7e84cb450f9b91fab27d9f080ca4c6c4c62119c","observation_id":"38382769-0c61-4f3c-b853-6bce2e2a7c90","resolution":{"observed_at":"2026-08-14T14:26:40.076877Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T14:26:40.062242Z","title":"His research interests include audio and speech processing, music information retrieval and developing ad- versarial attacks on machine learning systems","venue":null,"work_id":"cd73f48c-d353-42db-9e6b-bcb2289e0d29","year":2008},"citing_paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations","version":5},"reference_index":2017,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:39.775562Z"},"links":{"citing_paper":"/paper/1908.03173"},"observation_digest":"sha256:438af15c91c93f544e0a1809d56ba16a85558e641a40a9e7ca6d823337af8ca7","observation_id":"063f0196-69e1-456b-9f15-838cd18e38b4","resolution":{"observed_at":"2026-08-14T14:26:40.066019Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"1908.03173","last_updated":"2020-11-17T00:42:45Z","latest_version":5,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-14T14:19:16.836832Z","submitted_at":"2019-08-08T17:07:30Z","title":"Universal Adversarial Audio Perturbations"},"reference_resolution":{"displayed":68,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":8,"verified_exact":4,"verified_fuzzy":55},"total_outbound_references":68},"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":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"thesis":"As of 15 August 2026, this Paper Citation Record lists 68 of 68 outbound references and 2 inbound Pith citation observations for arXiv:1908.03173."}