{"as_of":"2026-08-12T16:18:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:9452ad27b1f821c13c3da2d707f98ce1dde6cfb47895343607f0aeb50be9d2ac","coverage":[{"denominator":49,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":49,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-11T15:52:26.632555Z","state":"measured"},{"denominator":49,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":49,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-12T06:34:41.77262+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2412.10597/citation-record","integrity":"/paper/2412.10597/integrity","json":"/paper/2412.10597/citation-record.json","paper":"/paper/2412.10597"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T15:52:28.317703Z","title":"ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness,","venue":null,"work_id":"9844ad21-53d1-4580-8097-37976bbe8470","year":null},"citing_paper":{"arxiv_id":"2412.10597","last_updated":"2025-02-10T21:53:37Z","snapshot_observed_at":"2026-08-12T04:53:04.483357Z","submitted_at":"2024-12-13T22:53:16Z","title":"Err on the Side of Texture: Texture Bias on Real Data","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-11T15:52:26.337977Z"},"links":{"citing_paper":"/paper/2412.10597"},"observation_digest":"sha256:a2e9dd428f3d54f46f235a7153043519ee1dc273b1a337b281b19c45410a5c8e","observation_id":"5c33b7e7-d82a-460e-92a1-64a3cbb6aaf5","resolution":{"observed_at":"2026-08-11T15:52:28.326829Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T15:52:26.350551Z","title":"On the Performance of GoogLeNet and AlexNet Applied to Sketches,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2412.10597","last_updated":"2025-02-10T21:53:37Z","snapshot_observed_at":"2026-08-12T04:53:04.483357Z","submitted_at":"2024-12-13T22:53:16Z","title":"Err on the Side of Texture: Texture Bias on Real Data","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-11T15:52:26.350551Z"},"links":{"citing_paper":"/paper/2412.10597"},"observation_digest":"sha256:4b6d52c9577dec1389b19993fc9f9b5036874d83501fdc2aa1a605f97dd98c08","observation_id":"5c91dc5e-0eae-4d51-bdb9-e2379e1dc862","resolution":{"observed_at":"2026-08-11T15:52:26.350551Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1904.00760","last_updated":"2019-03-20T16:37:17Z","snapshot_observed_at":"2026-08-10T07:57:23.005504Z","submitted_at":"2019-03-20T16:37:17Z","title":"Approximating CNNs with Bag-of-local-Features models works surprisingly well on ImageNet","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1904.00760","snapshot_observed_at":"2026-08-11T15:52:26.356861Z","title":"Approximating CNNs with Bag-of-local-Features models works surprisingly well on ImageNet,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2412.10597","last_updated":"2025-02-10T21:53:37Z","snapshot_observed_at":"2026-08-12T04:53:04.483357Z","submitted_at":"2024-12-13T22:53:16Z","title":"Err on the Side of Texture: Texture Bias on Real Data","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-11T15:52:26.356861Z"},"links":{"cited_paper":"/paper/1904.00760","citing_paper":"/paper/2412.10597"},"observation_digest":"sha256:6337d103c2d536068b4c9697742186d303f36790ca5d16db83b0322b05611c44","observation_id":"4329f7f8-6543-4384-9c2d-10d9066ad2a6","resolution":{"observed_at":"2026-08-11T15:52:26.356861Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T15:52:26.363560Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.10597","last_updated":"2025-02-10T21:53:37Z","snapshot_observed_at":"2026-08-12T04:53:04.483357Z","submitted_at":"2024-12-13T22:53:16Z","title":"Err on the Side of Texture: Texture Bias on Real Data","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-11T15:52:26.363560Z"},"links":{"citing_paper":"/paper/2412.10597"},"observation_digest":"sha256:5d53f85869cda3dcbf69edcdd02644299b55cd3b27a637f0c3d09b0478b2db68","observation_id":"c59d3b69-846e-4b35-82c4-c3972680ab8d","resolution":{"observed_at":"2026-08-11T15:52:26.363560Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1808.08750","last_updated":"2020-10-23T09:05:30Z","snapshot_observed_at":"2026-07-06T06:57:36.335954Z","submitted_at":"2018-08-27T09:17:57Z","title":"Generalisation in humans and deep neural networks","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1808.08750","snapshot_observed_at":"2026-08-11T15:52:26.370323Z","title":"Generalisation in humans and deep neural networks,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2412.10597","last_updated":"2025-02-10T21:53:37Z","snapshot_observed_at":"2026-08-12T04:53:04.483357Z","submitted_at":"2024-12-13T22:53:16Z","title":"Err on the Side of Texture: Texture Bias on Real Data","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-11T15:52:26.370323Z"},"links":{"cited_paper":"/paper/1808.08750","citing_paper":"/paper/2412.10597"},"observation_digest":"sha256:9028a60717934a505a1cf0a931ad4a1168399012008c55a46f3f98b0ec730d53","observation_id":"e110e125-20c8-43be-9ecc-9a46756518b0","resolution":{"observed_at":"2026-08-11T15:52:26.370323Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1907.07174","last_updated":"2021-03-04T21:56:19Z","snapshot_observed_at":"2026-07-06T08:08:08.790847Z","submitted_at":"2019-07-16T17:56:30Z","title":"Natural Adversarial Examples","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1907.07174","snapshot_observed_at":"2026-08-11T15:52:26.378581Z","title":"Natural Adversarial Examples,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2412.10597","last_updated":"2025-02-10T21:53:37Z","snapshot_observed_at":"2026-08-12T04:53:04.483357Z","submitted_at":"2024-12-13T22:53:16Z","title":"Err on the Side of Texture: Texture Bias on Real Data","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-11T15:52:26.378581Z"},"links":{"cited_paper":"/paper/1907.07174","citing_paper":"/paper/2412.10597"},"observation_digest":"sha256:07f0ff870d32bf82d98098bc0e6901ba4b7d1409496130428b7d6da4320340b7","observation_id":"89a206f6-640a-4b85-ae2a-fb4644bf6ca2","resolution":{"observed_at":"2026-08-11T15:52:26.378581Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.10297","last_updated":"2025-05-09T20:20:31Z","snapshot_observed_at":"2026-08-12T04:53:09.535651Z","submitted_at":"2024-09-16T14:02:18Z","title":"On Synthetic Texture Datasets: Challenges, Creation, and Curation","version":3},"cited_work":{"arxiv_id":"2409.10297","doi":"10.48550/arxiv.2409.10297","metadata_source":"pith","pith_arxiv_id":"2409.10297","snapshot_observed_at":"2026-08-11T18:16:15.004306Z","title":"On Synthetic Texture Datasets: Challenges, Creation, and Curation","venue":"cs.CV","work_id":"7d2dabd8-429d-4fc0-8b1a-2186d8333982","year":2024},"citing_paper":{"arxiv_id":"2412.10597","last_updated":"2025-02-10T21:53:37Z","snapshot_observed_at":"2026-08-12T04:53:04.483357Z","submitted_at":"2024-12-13T22:53:16Z","title":"Err on the Side of Texture: Texture Bias on Real Data","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-11T15:52:26.385689Z"},"links":{"cited_paper":"/paper/2409.10297","citing_paper":"/paper/2412.10597"},"observation_digest":"sha256:2b2f3c6505bde678440fb6fc9c1d4b91ab7121b8b42335d4301b62248e1e06e3","observation_id":"5c0abc14-7441-4b7a-8683-4b0abb2711ea","resolution":{"observed_at":"2026-08-11T15:52:27.068505Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.09543","last_updated":"2024-03-14T16:30:52Z","snapshot_observed_at":"2026-08-12T09:02:21.838339Z","submitted_at":"2024-03-14T16:30:52Z","title":"Explorations in Texture Learning","version":1},"cited_work":{"arxiv_id":"2403.09543","doi":"10.48550/arxiv.2403.09543","metadata_source":"pith","pith_arxiv_id":"2403.09543","snapshot_observed_at":"2026-08-11T18:16:15.004306Z","title":"Explorations in Texture Learning","venue":"cs.CV","work_id":"8aec8130-2f06-4a23-9ce0-b834d4138b8a","year":2024},"citing_paper":{"arxiv_id":"2412.10597","last_updated":"2025-02-10T21:53:37Z","snapshot_observed_at":"2026-08-12T04:53:04.483357Z","submitted_at":"2024-12-13T22:53:16Z","title":"Err on the Side of Texture: Texture Bias on Real Data","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-11T15:52:26.392512Z"},"links":{"cited_paper":"/paper/2403.09543","citing_paper":"/paper/2412.10597"},"observation_digest":"sha256:3a6c1f1f9bc1f5b53a096729aa91105e542e00e90c00a251f008a39d04f9fb2f","observation_id":"af57db43-fdf5-49fb-8191-8055f3d40a4f","resolution":{"observed_at":"2026-08-11T15:52:27.030994Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"document/6909856","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T15:52:28.006820Z","title":"Describing Textures in the Wild,","venue":null,"work_id":"e85084a1-1396-4202-8470-ee39c6c4c42c","year":2014},"citing_paper":{"arxiv_id":"2412.10597","last_updated":"2025-02-10T21:53:37Z","snapshot_observed_at":"2026-08-12T04:53:04.483357Z","submitted_at":"2024-12-13T22:53:16Z","title":"Err on the Side of Texture: Texture Bias on Real Data","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-11T15:52:26.398159Z"},"links":{"citing_paper":"/paper/2412.10597"},"observation_digest":"sha256:753d2bce3764862f3d2abcbb9404a9c1cf1d3e98dc5f01e415262a21f62ec1c2","observation_id":"a40632bb-516b-4a2b-9933-d3bdd13ab210","resolution":{"observed_at":"2026-08-11T15:52:28.023496Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2004.07780","last_updated":"2023-11-21T15:22:43Z","snapshot_observed_at":"2026-08-10T05:55:10.444536Z","submitted_at":"2020-04-16T17:18:49Z","title":"Shortcut Learning in Deep Neural Networks","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2004.07780","snapshot_observed_at":"2026-08-11T15:52:26.405398Z","title":"Shortcut Learning in Deep Neural Networks,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2412.10597","last_updated":"2025-02-10T21:53:37Z","snapshot_observed_at":"2026-08-12T04:53:04.483357Z","submitted_at":"2024-12-13T22:53:16Z","title":"Err on the Side of Texture: Texture Bias on Real Data","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-11T15:52:26.405398Z"},"links":{"cited_paper":"/paper/2004.07780","citing_paper":"/paper/2412.10597"},"observation_digest":"sha256:939fb51f7c73f07f8b4a953d7efc46bcd49063e487b3e57b94ab96ed37781147","observation_id":"d15cb385-ba2f-4188-872f-2b8f00c606e4","resolution":{"observed_at":"2026-08-11T15:52:26.405398Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1312.6199","last_updated":"2014-02-19T16:33:14Z","snapshot_observed_at":"2026-07-06T03:31:33.797310Z","submitted_at":"2013-12-21T03:36:08Z","title":"Intriguing properties of neural networks","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1312.6199","snapshot_observed_at":"2026-08-11T15:52:26.422659Z","title":"Intriguing properties of neural networks,","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2412.10597","last_updated":"2025-02-10T21:53:37Z","snapshot_observed_at":"2026-08-12T04:53:04.483357Z","submitted_at":"2024-12-13T22:53:16Z","title":"Err on the Side of Texture: Texture Bias on Real Data","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-11T15:52:26.422659Z"},"links":{"cited_paper":"/paper/1312.6199","citing_paper":"/paper/2412.10597"},"observation_digest":"sha256:0e8fc7f8c6605833d7a7b0ad6b22921f93a870f22d473ac35853131f8fd09820","observation_id":"75a241e4-7543-4a9d-a02b-e5f8a3ef7987","resolution":{"observed_at":"2026-08-11T15:52:26.422659Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/978-3-642-40994-3_","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T15:52:26.975821Z","title":"Evasion Attacks against Machine Learning at Test Time,","venue":null,"work_id":"3d805446-e32e-4cf2-859e-b7406deeaa1b","year":2013},"citing_paper":{"arxiv_id":"2412.10597","last_updated":"2025-02-10T21:53:37Z","snapshot_observed_at":"2026-08-12T04:53:04.483357Z","submitted_at":"2024-12-13T22:53:16Z","title":"Err on the Side of Texture: Texture Bias on Real Data","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-11T15:52:26.428605Z"},"links":{"citing_paper":"/paper/2412.10597"},"observation_digest":"sha256:a370ad0478353983353e608f8ab663a2c167656ebeeb558a809a3934529b3dfe","observation_id":"b77dbddb-40e6-4a46-a0aa-f9a2d41a481c","resolution":{"observed_at":"2026-08-11T15:52:26.980564Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1412.6572","last_updated":"2015-03-20T20:19:16Z","snapshot_observed_at":"2026-07-06T04:04:16.777653Z","submitted_at":"2014-12-20T01:17:12Z","title":"Explaining and Harnessing Adversarial Examples","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1412.6572","snapshot_observed_at":"2026-08-11T15:52:26.440555Z","title":"Explaining and Harnessing Adversarial Examples,","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2412.10597","last_updated":"2025-02-10T21:53:37Z","snapshot_observed_at":"2026-08-12T04:53:04.483357Z","submitted_at":"2024-12-13T22:53:16Z","title":"Err on the Side of Texture: Texture Bias on Real Data","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-11T15:52:26.440555Z"},"links":{"cited_paper":"/paper/1412.6572","citing_paper":"/paper/2412.10597"},"observation_digest":"sha256:d49baeae048e79033752020dfbee14a7c122ca4f4a7ba062938b030eadedbb65","observation_id":"6a0b02af-5b34-46b3-9b33-d9bdbb39857f","resolution":{"observed_at":"2026-08-11T15:52:26.440555Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1706.06083","last_updated":"2019-09-04T18:53:10Z","snapshot_observed_at":"2026-08-07T14:27:46.872660Z","submitted_at":"2017-06-19T17:53:11Z","title":"Towards Deep Learning Models Resistant to Adversarial Attacks","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1706.06083","snapshot_observed_at":"2026-08-11T15:52:26.444982Z","title":"Towards Deep Learning Models Resistant to Adversarial Attacks,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2412.10597","last_updated":"2025-02-10T21:53:37Z","snapshot_observed_at":"2026-08-12T04:53:04.483357Z","submitted_at":"2024-12-13T22:53:16Z","title":"Err on the Side of Texture: Texture Bias on Real Data","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-11T15:52:26.444982Z"},"links":{"cited_paper":"/paper/1706.06083","citing_paper":"/paper/2412.10597"},"observation_digest":"sha256:7277b2af5d26798d08ac3299ba2cc96fc5c7f878d1ec7f893b611bd40aa2254f","observation_id":"7e5882e6-3728-4095-a42d-5670b0e1ce33","resolution":{"observed_at":"2026-08-11T15:52:26.444982Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1511.04599","last_updated":"2016-07-04T04:49:44Z","snapshot_observed_at":"2026-08-11T03:11:51.392306Z","submitted_at":"2015-11-14T18:50:00Z","title":"DeepFool: a simple and accurate method to fool deep neural networks","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1511.04599","snapshot_observed_at":"2026-08-11T15:52:26.451693Z","title":"DeepFool: A simple and accurate method to fool deep neural networks,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2412.10597","last_updated":"2025-02-10T21:53:37Z","snapshot_observed_at":"2026-08-12T04:53:04.483357Z","submitted_at":"2024-12-13T22:53:16Z","title":"Err on the Side of Texture: Texture Bias on Real Data","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-11T15:52:26.451693Z"},"links":{"cited_paper":"/paper/1511.04599","citing_paper":"/paper/2412.10597"},"observation_digest":"sha256:e137afae246dac7cd832bfd83826c1b63d58e7ba37629bc349290d3767e68cd5","observation_id":"ec6fb53f-f122-4aa4-9edf-d1e5bd5a6a27","resolution":{"observed_at":"2026-08-11T15:52:26.451693Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2209.04521","last_updated":"2023-09-06T19:01:25Z","snapshot_observed_at":"2026-08-12T12:49:20.903612Z","submitted_at":"2022-09-09T20:53:11Z","title":"The Space of Adversarial Strategies","version":2},"cited_work":{"arxiv_id":"2209.04521","doi":null,"metadata_source":"pith","pith_arxiv_id":"2209.04521","snapshot_observed_at":"2026-08-11T15:52:27.844180Z","title":"The Space of Adversarial Strategies","venue":"cs.CR","work_id":"c714dc8f-7f42-4735-a31c-ce59f999b681","year":2022},"citing_paper":{"arxiv_id":"2412.10597","last_updated":"2025-02-10T21:53:37Z","snapshot_observed_at":"2026-08-12T04:53:04.483357Z","submitted_at":"2024-12-13T22:53:16Z","title":"Err on the Side of Texture: Texture Bias on Real Data","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-11T15:52:26.461891Z"},"links":{"cited_paper":"/paper/2209.04521","citing_paper":"/paper/2412.10597"},"observation_digest":"sha256:cbe7278741584949a5dbfcd4bbc04d405cba3a06f379f32e9091c9510226e88b","observation_id":"be6d8316-915d-46b7-abcb-2b544e54077a","resolution":{"observed_at":"2026-08-11T15:52:27.850283Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1608.04644","last_updated":"2017-03-22T17:46:16Z","snapshot_observed_at":"2026-07-06T05:07:10.046451Z","submitted_at":"2016-08-16T15:59:35Z","title":"Towards Evaluating the Robustness of Neural Networks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1608.04644","snapshot_observed_at":"2026-08-11T15:52:26.468603Z","title":"Towards Evaluating the Robustness of Neural Networks,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2412.10597","last_updated":"2025-02-10T21:53:37Z","snapshot_observed_at":"2026-08-12T04:53:04.483357Z","submitted_at":"2024-12-13T22:53:16Z","title":"Err on the Side of Texture: Texture Bias on Real Data","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-11T15:52:26.468603Z"},"links":{"cited_paper":"/paper/1608.04644","citing_paper":"/paper/2412.10597"},"observation_digest":"sha256:ff254009de5e228f98ad9f2d972f624e3fa20a747127ed17ff3db3309a31a9c3","observation_id":"91f74a3d-40f8-47dd-bcf9-5a2b45878f17","resolution":{"observed_at":"2026-08-11T15:52:26.468603Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1511.07528","last_updated":"2015-11-24T01:07:08Z","snapshot_observed_at":"2026-08-04T23:22:01.681405Z","submitted_at":"2015-11-24T01:07:08Z","title":"The Limitations of Deep Learning in Adversarial Settings","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1511.07528","snapshot_observed_at":"2026-08-11T15:52:26.474789Z","title":"The Limitations of Deep Learning in Adversarial Settings,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2412.10597","last_updated":"2025-02-10T21:53:37Z","snapshot_observed_at":"2026-08-12T04:53:04.483357Z","submitted_at":"2024-12-13T22:53:16Z","title":"Err on the Side of Texture: Texture Bias on Real Data","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-11T15:52:26.474789Z"},"links":{"cited_paper":"/paper/1511.07528","citing_paper":"/paper/2412.10597"},"observation_digest":"sha256:1e03d60504c876df2501f9fdeac9d9acaa1568cb8e5c0a4370f25f8e1e2a7c3d","observation_id":"04d96936-4dd1-4f02-aaae-cb3846c96023","resolution":{"observed_at":"2026-08-11T15:52:26.474789Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1409.0575","last_updated":"2015-01-30T01:23:59Z","snapshot_observed_at":"2026-07-06T03:53:12.119259Z","submitted_at":"2014-09-01T22:29:38Z","title":"ImageNet Large Scale Visual Recognition Challenge","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1409.0575","snapshot_observed_at":"2026-08-11T15:52:26.480448Z","title":"ImageNet Large Scale Visual Recognition Challenge,","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2412.10597","last_updated":"2025-02-10T21:53:37Z","snapshot_observed_at":"2026-08-12T04:53:04.483357Z","submitted_at":"2024-12-13T22:53:16Z","title":"Err on the Side of Texture: Texture Bias on Real Data","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-11T15:52:26.480448Z"},"links":{"cited_paper":"/paper/1409.0575","citing_paper":"/paper/2412.10597"},"observation_digest":"sha256:672d1b1a8720724b82d932df88de40e08eed6af731aa7bc8e7e35dc381288e26","observation_id":"94f28d4f-5e3b-40c1-8234-4ac7b5547a08","resolution":{"observed_at":"2026-08-11T15:52:26.480448Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T15:52:26.485651Z","title":"Torchvision the machine- vision package of torch,","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2412.10597","last_updated":"2025-02-10T21:53:37Z","snapshot_observed_at":"2026-08-12T04:53:04.483357Z","submitted_at":"2024-12-13T22:53:16Z","title":"Err on the Side of Texture: Texture Bias on Real Data","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-11T15:52:26.485651Z"},"links":{"citing_paper":"/paper/2412.10597"},"observation_digest":"sha256:fe395559cb109b7c5de894d831a90bd50661dc7af538706669ae8d83c14c1e7a","observation_id":"fefdb380-2ec0-4092-aea6-3e353067d4a2","resolution":{"observed_at":"2026-08-11T15:52:26.485651Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1512.03385","last_updated":"2015-12-10T19:51:55Z","snapshot_observed_at":"2026-07-06T04:39:28.429064Z","submitted_at":"2015-12-10T19:51:55Z","title":"Deep Residual Learning for Image Recognition","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1512.03385","snapshot_observed_at":"2026-08-11T15:52:26.490658Z","title":"Deep Residual Learning for Image Recognition,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2412.10597","last_updated":"2025-02-10T21:53:37Z","snapshot_observed_at":"2026-08-12T04:53:04.483357Z","submitted_at":"2024-12-13T22:53:16Z","title":"Err on the Side of Texture: Texture Bias on Real Data","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-11T15:52:26.490658Z"},"links":{"cited_paper":"/paper/1512.03385","citing_paper":"/paper/2412.10597"},"observation_digest":"sha256:d26f611d427bb9a8767b8bf200568012987d8c79d36b9f2386c7904ef173cff6","observation_id":"9b955127-eb42-441c-8cd4-5daa6ade0ac9","resolution":{"observed_at":"2026-08-11T15:52:26.490658Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1905.11946","last_updated":"2020-09-11T05:08:01Z","snapshot_observed_at":"2026-08-10T19:44:30.311627Z","submitted_at":"2019-05-28T17:05:32Z","title":"EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1905.11946","snapshot_observed_at":"2026-08-11T15:52:26.495913Z","title":"EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2412.10597","last_updated":"2025-02-10T21:53:37Z","snapshot_observed_at":"2026-08-12T04:53:04.483357Z","submitted_at":"2024-12-13T22:53:16Z","title":"Err on the Side of Texture: Texture Bias on Real Data","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-11T15:52:26.495913Z"},"links":{"cited_paper":"/paper/1905.11946","citing_paper":"/paper/2412.10597"},"observation_digest":"sha256:9f005c22e79aca27b7b9719eb82a35b0e37c1f801554996031e53877e4e86590","observation_id":"ed0c1030-afde-479c-a0f6-6a92c6df4463","resolution":{"observed_at":"2026-08-11T15:52:26.495913Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1608.06993","last_updated":"2018-01-28T17:12:02Z","snapshot_observed_at":"2026-08-06T14:53:46.539388Z","submitted_at":"2016-08-25T00:44:55Z","title":"Densely Connected Convolutional Networks","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1608.06993","snapshot_observed_at":"2026-08-11T15:52:26.501289Z","title":"Densely Connected Convolutional Networks,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2412.10597","last_updated":"2025-02-10T21:53:37Z","snapshot_observed_at":"2026-08-12T04:53:04.483357Z","submitted_at":"2024-12-13T22:53:16Z","title":"Err on the Side of Texture: Texture Bias on Real Data","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-11T15:52:26.501289Z"},"links":{"cited_paper":"/paper/1608.06993","citing_paper":"/paper/2412.10597"},"observation_digest":"sha256:dd902164ceda3ac434b71ca11001e8bca1527e0dbd154339df084dce3157c9cb","observation_id":"594306ed-a5be-46fc-8dcb-7b8fa966c688","resolution":{"observed_at":"2026-08-11T15:52:26.501289Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1512.00567","last_updated":"2015-12-11T20:27:50Z","snapshot_observed_at":"2026-08-06T16:02:58.892200Z","submitted_at":"2015-12-02T03:44:38Z","title":"Rethinking the Inception Architecture for Computer Vision","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1512.00567","snapshot_observed_at":"2026-08-11T15:52:26.506203Z","title":"Rethinking the Inception Architecture for Computer Vision,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2412.10597","last_updated":"2025-02-10T21:53:37Z","snapshot_observed_at":"2026-08-12T04:53:04.483357Z","submitted_at":"2024-12-13T22:53:16Z","title":"Err on the Side of Texture: Texture Bias on Real Data","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-11T15:52:26.506203Z"},"links":{"cited_paper":"/paper/1512.00567","citing_paper":"/paper/2412.10597"},"observation_digest":"sha256:23599032a3225cb8c40a6853020d6c027b029242fa307d6e5b0bedc41eac7185","observation_id":"31fe393d-23e2-4d7a-9bfd-689051c54aa5","resolution":{"observed_at":"2026-08-11T15:52:26.506203Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1708.06131","last_updated":"2017-08-21T09:55:37Z","snapshot_observed_at":"2026-07-06T05:56:00.379216Z","submitted_at":"2017-08-21T09:55:37Z","title":"Evasion Attacks against Machine Learning at Test Time","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1708.06131","snapshot_observed_at":"2026-08-11T15:52:26.434511Z","title":"Available: http://arxiv.org/abs/1708.06131","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2412.10597","last_updated":"2025-02-10T21:53:37Z","snapshot_observed_at":"2026-08-12T04:53:04.483357Z","submitted_at":"2024-12-13T22:53:16Z","title":"Err on the Side of Texture: Texture Bias on Real Data","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-11T15:52:26.434511Z"},"links":{"cited_paper":"/paper/1708.06131","citing_paper":"/paper/2412.10597"},"observation_digest":"sha256:156f38c92d5d52b065179ac6b311df2fad1b365112230b69b6313448eedfca57","observation_id":"1185e7bf-2189-4860-8b68-38bc8acd6580","resolution":{"observed_at":"2026-08-11T15:52:26.434511Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1911.09071","last_updated":"2020-11-03T22:51:23Z","snapshot_observed_at":"2026-07-06T08:38:33.799230Z","submitted_at":"2019-11-20T18:16:38Z","title":"The Origins and Prevalence of Texture Bias in Convolutional Neural Networks","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1911.09071","snapshot_observed_at":"2026-08-11T15:52:26.518545Z","title":"The Origins and Prevalence of Texture Bias in Convolutional Neural Networks,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2412.10597","last_updated":"2025-02-10T21:53:37Z","snapshot_observed_at":"2026-08-12T04:53:04.483357Z","submitted_at":"2024-12-13T22:53:16Z","title":"Err on the Side of Texture: Texture Bias on Real Data","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-11T15:52:26.518545Z"},"links":{"cited_paper":"/paper/1911.09071","citing_paper":"/paper/2412.10597"},"observation_digest":"sha256:a8a00e98e08dab9e3eab8b3e9c61e71219463f505b14ab795163e102e89853f2","observation_id":"ddcc4713-9ca9-4e3b-ad48-0b34037a9002","resolution":{"observed_at":"2026-08-11T15:52:26.518545Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2201.03545","last_updated":"2022-03-02T15:08:16Z","snapshot_observed_at":"2026-08-11T00:54:50.912638Z","submitted_at":"2022-01-10T18:59:10Z","title":"A ConvNet for the 2020s","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2201.03545","snapshot_observed_at":"2026-08-11T15:52:26.512752Z","title":"A ConvNet for the 2020s,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.10597","last_updated":"2025-02-10T21:53:37Z","snapshot_observed_at":"2026-08-12T04:53:04.483357Z","submitted_at":"2024-12-13T22:53:16Z","title":"Err on the Side of Texture: Texture Bias on Real Data","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-11T15:52:26.512752Z"},"links":{"cited_paper":"/paper/2201.03545","citing_paper":"/paper/2412.10597"},"observation_digest":"sha256:9d0dcf3198432ae10a6fd58989c9a2d2d5e80d5c8c027fbf39e67219e008f6e4","observation_id":"fe9fa969-caf9-499f-993b-3977a3980de6","resolution":{"observed_at":"2026-08-11T15:52:26.512752Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1505.07376","last_updated":"2015-11-06T13:55:09Z","snapshot_observed_at":"2026-08-03T17:16:14.826647Z","submitted_at":"2015-05-27T15:29:52Z","title":"Texture Synthesis Using Convolutional Neural Networks","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1505.07376","snapshot_observed_at":"2026-08-11T15:52:26.528372Z","title":"Texture Synthesis Using Convolutional Neural Networks,","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2412.10597","last_updated":"2025-02-10T21:53:37Z","snapshot_observed_at":"2026-08-12T04:53:04.483357Z","submitted_at":"2024-12-13T22:53:16Z","title":"Err on the Side of Texture: Texture Bias on Real Data","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-11T15:52:26.528372Z"},"links":{"cited_paper":"/paper/1505.07376","citing_paper":"/paper/2412.10597"},"observation_digest":"sha256:618f2baa40264af732eed1e62430f57b788d457b206b8a3e1c5565c96deddf88","observation_id":"18fd791d-34c7-46b8-b821-54d328646a67","resolution":{"observed_at":"2026-08-11T15:52:26.528372Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T15:52:26.523437Z","title":"Network Dissection: Quantifying Interpretability of Deep Visual Representations,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2412.10597","last_updated":"2025-02-10T21:53:37Z","snapshot_observed_at":"2026-08-12T04:53:04.483357Z","submitted_at":"2024-12-13T22:53:16Z","title":"Err on the Side of Texture: Texture Bias on Real Data","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-11T15:52:26.523437Z"},"links":{"citing_paper":"/paper/2412.10597"},"observation_digest":"sha256:9788990101055854c5a0a8bc634c2bd3d09792648e5bfc671264066fa9e39ccc","observation_id":"6361632f-3217-4de5-b103-5ecf4da375be","resolution":{"observed_at":"2026-08-11T15:52:26.523437Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1903.12261","last_updated":"2019-03-28T20:56:37Z","snapshot_observed_at":"2026-08-09T13:36:49.416146Z","submitted_at":"2019-03-28T20:56:37Z","title":"Benchmarking Neural Network Robustness to Common Corruptions and Perturbations","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1903.12261","snapshot_observed_at":"2026-08-11T15:52:26.537998Z","title":"Benchmarking Neu- ral Network Robustness to Common Corruptions and Perturbations,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2412.10597","last_updated":"2025-02-10T21:53:37Z","snapshot_observed_at":"2026-08-12T04:53:04.483357Z","submitted_at":"2024-12-13T22:53:16Z","title":"Err on the Side of Texture: Texture Bias on Real Data","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-11T15:52:26.537998Z"},"links":{"cited_paper":"/paper/1903.12261","citing_paper":"/paper/2412.10597"},"observation_digest":"sha256:b36a858c119aa79ad2f4aba0ea57293bd03c694150304bf2568ac4784f05656b","observation_id":"0eb8b3b3-1459-4d26-bc10-81e885d4dcfb","resolution":{"observed_at":"2026-08-11T15:52:26.537998Z","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":"document/7780634","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T15:52:27.586112Z","title":"Image Style Transfer Using Convolutional Neural Networks,","venue":null,"work_id":"72035f5c-6d9c-4e7d-a418-62ceeaf107ff","year":2016},"citing_paper":{"arxiv_id":"2412.10597","last_updated":"2025-02-10T21:53:37Z","snapshot_observed_at":"2026-08-12T04:53:04.483357Z","submitted_at":"2024-12-13T22:53:16Z","title":"Err on the Side of Texture: Texture Bias on Real Data","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-11T15:52:26.533581Z"},"links":{"citing_paper":"/paper/2412.10597"},"observation_digest":"sha256:e331704a2b18ecd5770eaffbeda10aa02edabaaa116c5a660ac7eb4c09424bb4","observation_id":"bff59440-2147-4e75-bd1b-259e787c3781","resolution":{"observed_at":"2026-08-11T15:52:27.597673Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T15:52:28.263412Z","title":"Shape-Texture Debiased Neural Network Training,","venue":null,"work_id":"fd38a415-9f10-4aed-a5b1-835d7b4f7719","year":2021},"citing_paper":{"arxiv_id":"2412.10597","last_updated":"2025-02-10T21:53:37Z","snapshot_observed_at":"2026-08-12T04:53:04.483357Z","submitted_at":"2024-12-13T22:53:16Z","title":"Err on the Side of Texture: Texture Bias on Real Data","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-11T15:52:26.551498Z"},"links":{"citing_paper":"/paper/2412.10597"},"observation_digest":"sha256:d5c88cb64ded8762a6ab1292145dc17b610540c27bc71e472d1fc59910bc7e00","observation_id":"2092ba5e-b3fb-4de2-80cf-4b73c318b8d8","resolution":{"observed_at":"2026-08-11T15:52:28.274082Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T15:52:26.542697Z","title":"Shift from Texture-bias to Shape-bias: Edge Deformation-based Augmentation for Robust Object Recognition,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.10597","last_updated":"2025-02-10T21:53:37Z","snapshot_observed_at":"2026-08-12T04:53:04.483357Z","submitted_at":"2024-12-13T22:53:16Z","title":"Err on the Side of Texture: Texture Bias on Real Data","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-11T15:52:26.542697Z"},"links":{"citing_paper":"/paper/2412.10597"},"observation_digest":"sha256:bc50586bb62abba3db28dcc0c7cee9003ea9530aa030033761b4d94a6e8bc76f","observation_id":"8d6b10f3-5998-487b-917d-b21088b19e22","resolution":{"observed_at":"2026-08-11T15:52:26.542697Z","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":"2026-08-11T15:52:28.237607Z","title":"Adversarial Machine Learning at Scale,","venue":null,"work_id":"8179dcc9-c512-4ae3-8412-e486a84267b4","year":2017},"citing_paper":{"arxiv_id":"2412.10597","last_updated":"2025-02-10T21:53:37Z","snapshot_observed_at":"2026-08-12T04:53:04.483357Z","submitted_at":"2024-12-13T22:53:16Z","title":"Err on the Side of Texture: Texture Bias on Real Data","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-11T15:52:26.561532Z"},"links":{"citing_paper":"/paper/2412.10597"},"observation_digest":"sha256:f7a16fd067c8cb103e6f08e275535dc086ea7adc88597869f85190692d955603","observation_id":"9a5dc4ef-778e-4e32-9b48-cfcf18488b35","resolution":{"observed_at":"2026-08-11T15:52:28.245282Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1511.03034","last_updated":"2016-01-16T01:44:18Z","snapshot_observed_at":"2026-07-06T04:35:56.693328Z","submitted_at":"2015-11-10T09:44:33Z","title":"Learning with a Strong Adversary","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1511.03034","snapshot_observed_at":"2026-08-11T15:52:26.556374Z","title":"Huang, B","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2412.10597","last_updated":"2025-02-10T21:53:37Z","snapshot_observed_at":"2026-08-12T04:53:04.483357Z","submitted_at":"2024-12-13T22:53:16Z","title":"Err on the Side of Texture: Texture Bias on Real Data","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-11T15:52:26.556374Z"},"links":{"cited_paper":"/paper/1511.03034","citing_paper":"/paper/2412.10597"},"observation_digest":"sha256:2e173d62c623d1efd190128fa4f474f7c51b8b20a063d8a7db43c51ef003ecb6","observation_id":"4754d572-cb5c-45ba-96c5-a3cbd2b471b3","resolution":{"observed_at":"2026-08-11T15:52:26.556374Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1508.06576","last_updated":"2015-09-02T08:24:59Z","snapshot_observed_at":"2026-07-06T04:27:45.692332Z","submitted_at":"2015-08-26T17:14:42Z","title":"A Neural Algorithm of Artistic Style","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1508.06576","snapshot_observed_at":"2026-08-11T15:52:26.578368Z","title":null,"venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2412.10597","last_updated":"2025-02-10T21:53:37Z","snapshot_observed_at":"2026-08-12T04:53:04.483357Z","submitted_at":"2024-12-13T22:53:16Z","title":"Err on the Side of Texture: Texture Bias on Real Data","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-11T15:52:26.578368Z"},"links":{"cited_paper":"/paper/1508.06576","citing_paper":"/paper/2412.10597"},"observation_digest":"sha256:0b5f951c9f4a9f83c458b37eebeeadc7679b9093d09b26e56f434bd4a6223649","observation_id":"ccdef954-7e9c-435b-b175-bd770bcef987","resolution":{"observed_at":"2026-08-11T15:52:26.578368Z","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":"2026-08-11T15:52:28.189126Z","title":"Deep Learning based Feature Ex- traction for Texture Classification,","venue":null,"work_id":"e95f399e-0bba-4434-9d28-9419db4e6fe0","year":2020},"citing_paper":{"arxiv_id":"2412.10597","last_updated":"2025-02-10T21:53:37Z","snapshot_observed_at":"2026-08-12T04:53:04.483357Z","submitted_at":"2024-12-13T22:53:16Z","title":"Err on the Side of Texture: Texture Bias on Real Data","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-11T15:52:26.583830Z"},"links":{"citing_paper":"/paper/2412.10597"},"observation_digest":"sha256:28fd09f0e9c60ada0228ad5c61644d4f9d5598356773e993ac9e3843b2c04be5","observation_id":"3214496b-2ba9-4195-8168-8e225b2ef522","resolution":{"observed_at":"2026-08-11T15:52:28.196271Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T15:52:28.217062Z","title":"Interpreting Adversarially Trained Convolutional Neural Networks,","venue":null,"work_id":"5c93c52c-7ccf-4ed9-82c9-79c228bd54ce","year":2019},"citing_paper":{"arxiv_id":"2412.10597","last_updated":"2025-02-10T21:53:37Z","snapshot_observed_at":"2026-08-12T04:53:04.483357Z","submitted_at":"2024-12-13T22:53:16Z","title":"Err on the Side of Texture: Texture Bias on Real Data","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-11T15:52:26.573517Z"},"links":{"citing_paper":"/paper/2412.10597"},"observation_digest":"sha256:53290948f2ccd5b64a13683253348b4609f02a4a5b9f5e99d8ef81d0a97f8c8a","observation_id":"91019e4c-bc43-4e1a-8b6f-52ffebc7f0a5","resolution":{"observed_at":"2026-08-11T15:52:28.223732Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T15:52:26.593136Z","title":"Explore the Transfor- mation Space for Adversarial Images,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2412.10597","last_updated":"2025-02-10T21:53:37Z","snapshot_observed_at":"2026-08-12T04:53:04.483357Z","submitted_at":"2024-12-13T22:53:16Z","title":"Err on the Side of Texture: Texture Bias on Real Data","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-11T15:52:26.593136Z"},"links":{"citing_paper":"/paper/2412.10597"},"observation_digest":"sha256:0139698b866fcc2c529abada0d92e50897a03e49067cf576c3d7aa84348bb179","observation_id":"c937c8a8-ca86-408a-a666-f146cba31b83","resolution":{"observed_at":"2026-08-11T15:52:26.593136Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2012.14456","last_updated":"2020-12-20T11:35:29Z","snapshot_observed_at":"2026-08-12T13:25:32.411800Z","submitted_at":"2020-12-20T11:35:29Z","title":"Color Channel Perturbation Attacks for Fooling Convolutional Neural Networks and A Defense Against Such Attacks","version":1},"cited_work":{"arxiv_id":"2012.14456","doi":"10.48550/arxiv.2012.14456","metadata_source":"pith","pith_arxiv_id":"2012.14456","snapshot_observed_at":"2026-08-11T18:16:15.004306Z","title":"Color Channel Perturbation Attacks for Fooling Convolutional Neural Networks and A Defense Against Such Attacks","venue":"cs.CV","work_id":"8cf8d3ec-9d19-4f09-9b6e-8d280340a1b4","year":2020},"citing_paper":{"arxiv_id":"2412.10597","last_updated":"2025-02-10T21:53:37Z","snapshot_observed_at":"2026-08-12T04:53:04.483357Z","submitted_at":"2024-12-13T22:53:16Z","title":"Err on the Side of Texture: Texture Bias on Real Data","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-11T15:52:26.598772Z"},"links":{"cited_paper":"/paper/2012.14456","citing_paper":"/paper/2412.10597"},"observation_digest":"sha256:4fde2bac25dab686aaf405699d2e4466e6bbf5fa2f7f379af88305c3ff73334e","observation_id":"a7f679b4-eb63-4416-8a3e-5171f64c9092","resolution":{"observed_at":"2026-08-11T15:52:26.705744Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T15:52:28.164728Z","title":"Color encoding in biologically-inspired convolutional neural networks,","venue":null,"work_id":"a597bf17-9db5-46ae-a330-993c1be09963","year":2018},"citing_paper":{"arxiv_id":"2412.10597","last_updated":"2025-02-10T21:53:37Z","snapshot_observed_at":"2026-08-12T04:53:04.483357Z","submitted_at":"2024-12-13T22:53:16Z","title":"Err on the Side of Texture: Texture Bias on Real Data","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-11T15:52:26.588636Z"},"links":{"citing_paper":"/paper/2412.10597"},"observation_digest":"sha256:d502273d62dca03c9f0ceb3878a7cf6c4529caae1ae0cf455d04273d2034841f","observation_id":"8e79487c-0582-4ecf-913a-a72631b9ea8d","resolution":{"observed_at":"2026-08-11T15:52:28.169889Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1610.08401","last_updated":"2017-03-09T17:01:25Z","snapshot_observed_at":"2026-07-06T05:16:07.194124Z","submitted_at":"2016-10-26T16:30:45Z","title":"Universal adversarial perturbations","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1610.08401","snapshot_observed_at":"2026-08-11T15:52:26.604664Z","title":"Universal adversarial perturbations,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2412.10597","last_updated":"2025-02-10T21:53:37Z","snapshot_observed_at":"2026-08-12T04:53:04.483357Z","submitted_at":"2024-12-13T22:53:16Z","title":"Err on the Side of Texture: Texture Bias on Real Data","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-11T15:52:26.604664Z"},"links":{"cited_paper":"/paper/1610.08401","citing_paper":"/paper/2412.10597"},"observation_digest":"sha256:94c052640e0d3e69c61baa0c791dbc5563ad4a4ee922d19fb5729dc75c5b090d","observation_id":"84eb2037-085b-4401-be70-3a16eb5689f9","resolution":{"observed_at":"2026-08-11T15:52:26.604664Z","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":"2026-08-11T15:52:28.139334Z","title":"These files contain the necessary instructions, images, and the script you will run for this study","venue":null,"work_id":"c23c3a08-2ef4-4a49-8132-4361d49cac42","year":null},"citing_paper":{"arxiv_id":"2412.10597","last_updated":"2025-02-10T21:53:37Z","snapshot_observed_at":"2026-08-12T04:53:04.483357Z","submitted_at":"2024-12-13T22:53:16Z","title":"Err on the Side of Texture: Texture Bias on Real Data","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-11T15:52:26.609588Z"},"links":{"citing_paper":"/paper/2412.10597"},"observation_digest":"sha256:42bc2854d5372078e9bd210fc4d753d9dd9cbd98e6b23b94c075002ccc7794a7","observation_id":"6eb77072-e224-4f3e-918d-73528c645dd9","resolution":{"observed_at":"2026-08-11T15:52:28.144770Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T15:52:28.120049Z","title":"python3 eval_packages.py package_num The script will display 100 images, one at a time in a pop-up window along with four words in the terminal","venue":null,"work_id":"aa870fe7-b578-4d38-a484-1adfa3cdedc7","year":null},"citing_paper":{"arxiv_id":"2412.10597","last_updated":"2025-02-10T21:53:37Z","snapshot_observed_at":"2026-08-12T04:53:04.483357Z","submitted_at":"2024-12-13T22:53:16Z","title":"Err on the Side of Texture: Texture Bias on Real Data","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-11T15:52:26.614679Z"},"links":{"citing_paper":"/paper/2412.10597"},"observation_digest":"sha256:ff884a81f85325ab2598bc87f65cd508096382f4ab46fa0d52bb0882c045719c","observation_id":"9f4389e0-ca44-4906-b48e-fad30f24bde9","resolution":{"observed_at":"2026-08-11T15:52:28.126106Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T15:52:28.098597Z","title":"Your task is to input the number corre- sponding to the texture that you believe is most prominent in the image","venue":null,"work_id":"76c342d7-ec47-4097-a137-d58341269ddb","year":null},"citing_paper":{"arxiv_id":"2412.10597","last_updated":"2025-02-10T21:53:37Z","snapshot_observed_at":"2026-08-12T04:53:04.483357Z","submitted_at":"2024-12-13T22:53:16Z","title":"Err on the Side of Texture: Texture Bias on Real Data","version":2},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-11T15:52:26.620617Z"},"links":{"citing_paper":"/paper/2412.10597"},"observation_digest":"sha256:27662ded3e65ff1b26c5f7b333f3749854ed5fce586d2b068d7d21d4e5dd40d0","observation_id":"7aa95d8e-6622-4fdd-82f9-398145d45cea","resolution":{"observed_at":"2026-08-11T15:52:28.107129Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T15:52:28.075792Z","title":null,"venue":null,"work_id":"90e1781a-61c1-49d9-abeb-16636d714273","year":null},"citing_paper":{"arxiv_id":"2412.10597","last_updated":"2025-02-10T21:53:37Z","snapshot_observed_at":"2026-08-12T04:53:04.483357Z","submitted_at":"2024-12-13T22:53:16Z","title":"Err on the Side of Texture: Texture Bias on Real Data","version":2},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-11T15:52:26.626592Z"},"links":{"citing_paper":"/paper/2412.10597"},"observation_digest":"sha256:776ad9ebd846f28685fb0dc2064453289aa1f942afeb1889c457706b59455e72","observation_id":"d5ca3f70-e403-4917-be0f-1180dbf7ba07","resolution":{"observed_at":"2026-08-11T15:52:28.083175Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T15:52:28.048061Z","title":null,"venue":null,"work_id":"b3dca300-1b41-4746-8c5a-072c3a8b57ad","year":null},"citing_paper":{"arxiv_id":"2412.10597","last_updated":"2025-02-10T21:53:37Z","snapshot_observed_at":"2026-08-12T04:53:04.483357Z","submitted_at":"2024-12-13T22:53:16Z","title":"Err on the Side of Texture: Texture Bias on Real Data","version":2},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-11T15:52:26.632555Z"},"links":{"citing_paper":"/paper/2412.10597"},"observation_digest":"sha256:0080b667a87d689a9fe9df5fd9c94f4117fa1249488dd179ba5f3df4e29fa82d","observation_id":"219a4dcb-9dfd-4b9a-9ffc-95b06d8b817a","resolution":{"observed_at":"2026-08-11T15:52:28.057522Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1611.01236","last_updated":"2017-02-11T00:15:46Z","snapshot_observed_at":"2026-07-06T05:17:20.642708Z","submitted_at":"2016-11-04T01:11:02Z","title":"Adversarial Machine Learning at Scale","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1611.01236","snapshot_observed_at":"2026-08-11T15:52:26.567946Z","title":"48550 / arXiv","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2412.10597","last_updated":"2025-02-10T21:53:37Z","snapshot_observed_at":"2026-08-12T04:53:04.483357Z","submitted_at":"2024-12-13T22:53:16Z","title":"Err on the Side of Texture: Texture Bias on Real Data","version":2},"reference_index":2017,"source":"pdf_text","source_observed_at":"2026-08-11T15:52:26.567946Z"},"links":{"cited_paper":"/paper/1611.01236","citing_paper":"/paper/2412.10597"},"observation_digest":"sha256:f96bbfc75a9eb8d8df0a1226fe8a46c4b5f1cb4c20d2671c3c95197a57f51be8","observation_id":"b4f2d358-8757-419c-a22f-0b5ca8066960","resolution":{"observed_at":"2026-08-11T15:52:26.567946Z","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":"2026-08-11T15:52:28.295803Z","title":"Available: http://arxiv.org/abs/1811","venue":null,"work_id":"872bcd70-e639-4f99-bcbf-3d4a3b617a99","year":null},"citing_paper":{"arxiv_id":"2412.10597","last_updated":"2025-02-10T21:53:37Z","snapshot_observed_at":"2026-08-12T04:53:04.483357Z","submitted_at":"2024-12-13T22:53:16Z","title":"Err on the Side of Texture: Texture Bias on Real Data","version":2},"reference_index":2019,"source":"pdf_text","source_observed_at":"2026-08-11T15:52:26.345199Z"},"links":{"citing_paper":"/paper/2412.10597"},"observation_digest":"sha256:20a8ee801b82c8b161571c43beef7b3af60a1fbac611223c334580a928d8bc08","observation_id":"05e4e3b2-0280-45a3-b61c-e827ebbdac92","resolution":{"observed_at":"2026-08-11T15:52:28.303749Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2412.10597","last_updated":"2025-02-10T21:53:37Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-12T04:53:04.483357Z","submitted_at":"2024-12-13T22:53:16Z","title":"Err on the Side of Texture: Texture Bias on Real Data"},"reference_resolution":{"displayed":49,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":32,"verified_exact":6,"verified_fuzzy":10},"total_outbound_references":49},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"thesis":"As of 12 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 0 inbound Pith citation observations for arXiv:2412.10597."}