{"as_of":"2026-08-10T11:09:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:fa848551b5d1f8ba6d6d3ec30bc448abbe5061dca801cacc8bd0fad7324d53ca","coverage":[{"denominator":70,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":70,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T11:47:50.880083Z","state":"measured"},{"denominator":71,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":71,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-06-26T04:35:51.583460Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"arxiv_reference","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":0,"observed_at":"2026-08-05T02:28:24.338817Z","source":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"cited_work":{"arxiv_id":"2506.01511","doi":"10.48550/arxiv.2506.01511","metadata_source":"arxiv_reference","pith_arxiv_id":"2506.01511","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Enhancing diffusion-based unrestricted adversarial attacks via adversary preferences alignment","venue":"ArXiv.org","work_id":"2cbf0f2c-52b6-4a42-9d06-8d479b67fffb","year":2025},"citing_paper":{"arxiv_id":"2606.26566","last_updated":"2026-06-25T03:32:12Z","snapshot_observed_at":"2026-08-03T17:22:40.185111Z","submitted_at":"2026-06-25T03:32:12Z","title":"Adversarial Diffusion Across Modalities: A Fusion Survey of Attacks, Defenses, and Evaluation for Text, Vision, and Vision-Language Models","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-06-26T04:35:51.583460Z"},"links":{"cited_paper":"/paper/2506.01511","citing_paper":"/paper/2606.26566"},"observation_digest":"sha256:1f8366ec190ecc69a59099d63301fa7782ff1117c782ee54e71f9aa3499ae48f","observation_id":"7da8628c-176c-4c14-b5f0-663abaf92874","resolution":{"observed_at":"2026-06-26T04:38:59.167224Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2506.01511/citation-record","integrity":"/paper/2506.01511/integrity","json":"/paper/2506.01511/citation-record.json","paper":"/paper/2506.01511"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:48:07.806459Z","title":"Alberti, and Tandri Gauksson","venue":null,"work_id":"5c68f56f-bbec-4d2f-9ec0-74ea68d647c9","year":2019},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:59.085901Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:b6a9f865b7d06a42cecfcf3e2b480f4e922a2b2f966b29e9777281030167fbec","observation_id":"66912fae-f7d5-41a8-ac88-b98afdff4524","resolution":{"observed_at":"2026-08-07T11:48:07.852034Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:48:07.718680Z","title":"Li, and David A","venue":null,"work_id":"47998e71-06fe-412d-99a9-777cfe85dcfa","year":2019},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:59.132081Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:6c50302e834c866755974132bd7299be50317ce96c9645f6d19f2db07f89dab9","observation_id":"ac188a76-cd98-4f5e-b032-b2fcf78cbd70","resolution":{"observed_at":"2026-08-07T11:48:07.757733Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:48:07.657369Z","title":"Training diffusion models with reinforce- ment learning","venue":null,"work_id":"e2aa6ef6-7b03-4012-9cf9-711732336601","year":2024},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:59.164300Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:026813b32a9ae1ab22be2796e919b3b3cb8e194660c33feca25d77e8504cd639","observation_id":"faeed672-61c9-4a6c-b100-0bab1b842b3d","resolution":{"observed_at":"2026-08-07T11:48:07.684571Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:48:07.576707Z","title":"IQA-PyTorch: Pytorch toolbox for image quality assessment","venue":null,"work_id":"a4c0d1c6-b955-47fa-ba5b-a744b1c50b2a","year":2022},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:59.206016Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:a8feb4a567e8f2b34879760cf39f48e4d20f622512c5381ff7e853927aa2b180","observation_id":"56fdc742-cf16-48d0-9999-70f93eb32a79","resolution":{"observed_at":"2026-08-07T11:48:07.612097Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:46:59.243337Z","title":"Enhancing diffusion models with text-encoder reinforcement learning","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:59.243337Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:67548fb428bc27fd7039fa95feb8fa6577a248b239112b1bbc8e734b71d99d3e","observation_id":"3ee1dd4b-55c8-4fcc-a714-9dcf2a1a4b6d","resolution":{"observed_at":"2026-08-07T11:46:59.243337Z","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":"2026-08-07T11:48:07.494038Z","title":"Diffusion models for impercepti- ble and transferable adversarial attack","venue":null,"work_id":"6b879a99-46dc-4443-a374-ad5579b28347","year":2023},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:59.279189Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:9be362c8e4075818fb2edf582c13f1be8e60fc2c91055c1666539b0add84cf77","observation_id":"92b443e6-3f3b-4f40-a12c-40e61de8c567","resolution":{"observed_at":"2026-08-07T11:48:07.520683Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1604.06174","last_updated":"2016-04-22T19:21:36Z","snapshot_observed_at":"2026-08-08T09:03:25.135475Z","submitted_at":"2016-04-21T04:15:27Z","title":"Training Deep Nets with Sublinear Memory Cost","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1604.06174","snapshot_observed_at":"2026-08-07T11:46:59.320940Z","title":"Training deep nets with sublinear memory cost","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:59.320940Z"},"links":{"cited_paper":"/paper/1604.06174","citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:d060e4991079808afb21cb31486a17de99e4db51745f74d9c2aa41b5861ff5d3","observation_id":"30258d80-a91d-4c75-b205-09df1220e0d4","resolution":{"observed_at":"2026-08-07T11:46:59.320940Z","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":"2026-08-07T11:48:07.440570Z","title":"Advdiffuser: Natural adversarial example synthesis with diffusion models","venue":null,"work_id":"fac2b1c0-3398-4c13-ba4a-b84f8f26af1a","year":2023},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:59.358785Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:28af472099188d8c6ee73ba0251959743e7a3628b6b270e93f4a2e6b7eaf5b69","observation_id":"4d5504d6-16af-426e-ba65-0fce4a5e2f84","resolution":{"observed_at":"2026-08-07T11:48:07.464475Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:48:07.359436Z","title":"Content-based unrestricted ad- versarial attack","venue":null,"work_id":"2e59322a-0e42-4020-a8dc-1eb324ef5072","year":2024},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:59.401834Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:d0c665e92cbb7cfad94390b1c37fbed01f18a2880513361d8c671374a2061399","observation_id":"1ec4bdf0-c45f-4355-8cc3-808d13405a14","resolution":{"observed_at":"2026-08-07T11:48:07.388704Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:48:07.278705Z","title":"Directly fine-tuning diffusion models on differentiable re- wards","venue":null,"work_id":"6bf2948d-38a5-4e31-917e-f363538820ce","year":2024},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:59.436531Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:0bfba95f03b4f8c7efe49952eb4b1d76003951ecc8f16fa1dc49a543217aaef5","observation_id":"5d048b4c-732d-413f-85d6-b9f9a99f7d36","resolution":{"observed_at":"2026-08-07T11:48:07.314521Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:48:07.219778Z","title":"Advdiff: Generating unrestricted adversarial examples using diffusion models","venue":null,"work_id":"c1681c83-a13d-42d0-aa6b-6eb79704a855","year":2024},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:59.473375Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:a439641dcae428f74fe7ebaade8d16f5dfdeb6f462decefb636227b787fcfc9c","observation_id":"95261d59-80c6-4967-9ace-b64c87039e77","resolution":{"observed_at":"2026-08-07T11:48:07.236425Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:48:07.155979Z","title":"Imagenet large scale visual recognition competition 2012 (ilsvrc2012)","venue":null,"work_id":"1cb4fe8c-3a84-4ac3-81d1-e58c9d08d909","year":2012},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:59.507056Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:32bd51cac26a3fbbfc2035988d5fca33410d5e8c82de17e535e85c1f1bf45ecf","observation_id":"47ca93da-d899-4d00-9ceb-dc00ae8037c3","resolution":{"observed_at":"2026-08-07T11:48:07.179179Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:48:07.111053Z","title":"Diffusion models beat gans on image synthesis","venue":null,"work_id":"da4597ac-82cc-4594-aec3-b2f48234f166","year":2021},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:59.540253Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:40b95223667dca1c22c2da6c7c36109d733a98069fe21b8e5d4ef0a265d9ca99","observation_id":"866a5768-c32d-4807-81c1-78171ba10219","resolution":{"observed_at":"2026-08-07T11:48:07.126992Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:48:06.450650Z","title":"Boosting adversarial at- tacks with momentum","venue":null,"work_id":"2e9c666f-f0f5-4489-a7c6-48b111400a7f","year":2018},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:59.577360Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:5f60467a7e777a1a1d0c079817effcd58d372dde0e68ef77caca4d1d77fc5bbf","observation_id":"064b3f2d-f7a3-4798-a325-607568722637","resolution":{"observed_at":"2026-08-07T11:48:07.039774Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:48:06.386045Z","title":"Evading defenses to transferable adversarial examples by translation-invariant attacks","venue":null,"work_id":"983a9903-332e-4e39-86c0-848b378337a0","year":2019},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:59.621326Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:7cc5bb8f2c2a39fecdc2c065f3fdcaaf9a63c6761c3d79f4f657667af3cb5f89","observation_id":"672a4cb0-d215-4e3a-b451-44b95e6fed90","resolution":{"observed_at":"2026-08-07T11:48:06.405581Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:48:06.314279Z","title":"An image is worth 16x16 words: Transformers for image recognition at scale","venue":null,"work_id":"c56c465b-a083-44ae-b52b-a0ae2b9691e5","year":2021},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:59.668249Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:948437a1137de5dc0ecccb8af4892a4ac6f8439f977f49e81ac5a090bd3d9137","observation_id":"5adf6fef-74ea-4b8c-be2c-6be027c23a6e","resolution":{"observed_at":"2026-08-07T11:48:06.341211Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:48:06.230791Z","title":"Re- inforcement learning for fine-tuning text-to-image diffusion models","venue":null,"work_id":"c98c7661-3f88-418b-b18b-1db8a7da0f1e","year":2023},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:59.704587Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:956b26add19c55180e18ef265b0ae65c86996e1d8ba7cdac1d34ee4735d10129","observation_id":"a15a9b0e-fbda-42a3-b784-f35cceba4257","resolution":{"observed_at":"2026-08-07T11:48:06.260392Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:48:06.159463Z","title":"Wichmann, and Wieland Brendel","venue":null,"work_id":"806fba02-f591-4a68-b60e-fc3b740d7f96","year":2019},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:59.747797Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:d90c639da775eade7d916a9b835da795f829233a3343e19f2bd14ae8fb7f71f9","observation_id":"70231c75-15fc-4630-a328-c1a157f9c8c9","resolution":{"observed_at":"2026-08-07T11:48:06.188908Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:48:06.077390Z","title":"Shortcut learning in deep neural networks","venue":null,"work_id":"472f4918-e94f-4491-896f-8d3dc3528fd6","year":2020},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:59.791125Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:772d644aa27509e7e9be8123f614a709ba7f9054010a33ddeb6a4d97a1647f0a","observation_id":"c3f0f222-f451-49bc-88cc-703f63680102","resolution":{"observed_at":"2026-08-07T11:48:06.115903Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:48:06.005641Z","title":"Mix-of-show: Decentralized low- rank adaptation for multi-concept customization of diffusion models","venue":null,"work_id":"af3ff097-6356-4de0-9076-20f4723b361b","year":2024},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:59.845122Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:646a99db5c071bcd445406979d809e5f619441c5369e765b373a7cf46c6bb7bf","observation_id":"09d8463b-5a15-4f08-8f4a-c62db9180356","resolution":{"observed_at":"2026-08-07T11:48:06.033900Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:48:05.928295Z","title":"Countering adversarial images using input transformations","venue":null,"work_id":"f4bca513-73ea-4760-878f-b8e69ff632cd","year":2018},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:59.882382Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:2eda1f9c8737f50e9560b7d204be47ee51c5b49b5942f08c699ad91a8441154c","observation_id":"5f7ab34a-fc4b-4d0b-bcd9-e45c727a04e9","resolution":{"observed_at":"2026-08-07T11:48:05.962763Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:46:59.917798Z","title":"Deep residual learning for image recognition","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:59.917798Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:6e72db7cf0fbea11b65f599695fb712af1b38ccd7ff5e8998f98bc23de21fd7e","observation_id":"07c23bd5-39a8-4a1b-ba1b-b551e3c6e1aa","resolution":{"observed_at":"2026-08-07T11:46:59.917798Z","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":"2026-08-07T11:48:05.853421Z","title":"Denoising diffu- sion probabilistic models","venue":null,"work_id":"cb6f00d9-f50d-429b-ba85-e9cc05cf262c","year":2020},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:59.965353Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:03226d445d1a210db118a2cf9eeb8c1336885d7baba4f392decd7d529578b0b9","observation_id":"e29318d3-83bc-4d77-b5a4-82e18eda13ce","resolution":{"observed_at":"2026-08-07T11:48:05.876957Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:48:05.771614Z","title":"Semantic adver- sarial examples","venue":null,"work_id":"b883205c-f2ad-4b00-8fc7-67f54357030a","year":2018},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:00.000863Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:bce38305734d2bd5d17fe603b3dbb268bc5381d964406c06ddbb2daa279f8715","observation_id":"c15b79d3-6ff6-44fb-bcb9-ee741a83fe4c","resolution":{"observed_at":"2026-08-07T11:48:05.808786Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:48:05.688621Z","title":"LoRA: Low-rank adaptation of large language models","venue":null,"work_id":"9158dcf2-5cb5-441f-8d70-f634bb9cde51","year":2022},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:00.033451Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:47cb912117a6d3f9266b5c8c74a145d8cb2162ec3af7e6a6521e6353a1a5b163","observation_id":"a9a19de0-8d53-4c48-9d5f-595889a99de1","resolution":{"observed_at":"2026-08-07T11:48:05.729089Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:48:05.611613Z","title":"Weinberger","venue":null,"work_id":"f8d5d2b9-f3c7-40e9-91ba-fbfeb13b0c46","year":null},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:00.067563Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:48d64fb81d14200fd3240334cf400b580eacc44618d312fb167c50638fba4a44","observation_id":"a36f6b59-96c6-4fcf-9e95-f790dc2bd08c","resolution":{"observed_at":"2026-08-07T11:48:05.640234Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:48:05.541106Z","title":"Efficient decision-based black-box patch attacks on video recognition","venue":null,"work_id":"c7c8f924-4985-4491-9242-6d735de5e483","year":2023},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:00.110911Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:56d9df7c92730966fba30e8a7df3a6678f5f834f8df21f0aa108661c637583e2","observation_id":"4033c7d6-1a35-45d3-85e2-289276858be4","resolution":{"observed_at":"2026-08-07T11:48:05.567691Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:48:05.460335Z","title":"Towards decision-based sparse attacks on video recognition","venue":null,"work_id":"a5692928-6746-4c0b-9dc6-039e8e2580bc","year":2023},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:00.149049Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:d11e8ed61b5ae1eacef513f75514844c6fab9aea70c40495aad097214084e9ed","observation_id":"9611ed01-9704-4d67-a951-6a0c368ba813","resolution":{"observed_at":"2026-08-07T11:48:05.494464Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:48:05.376204Z","title":"Exploring the 9 adversarial robustness of video object segmentation via one- shot adversarial attacks","venue":null,"work_id":"e73ecd56-a312-4f43-9e4b-4d5732967a40","year":2023},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:00.183508Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:480d409d7315232fecb7ff80f92195b4ef2074d94a2d743f3cf3e317255332c1","observation_id":"6bd802cd-d1d1-4fdf-bfa7-bf7db4ac1b35","resolution":{"observed_at":"2026-08-07T11:48:05.416574Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:48:05.285895Z","title":"Perceptual losses for real-time style transfer and super-resolution","venue":null,"work_id":"325c3bd7-3a1d-4237-a880-e35c4e3d4b57","year":2016},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:00.219195Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:bc9b8e783d420d0f15b1bd1e5847f111e652079eec0e070d3564d6560414e910","observation_id":"6000cb86-9b10-4a62-916c-0ec23f5c5c1f","resolution":{"observed_at":"2026-08-07T11:48:05.325930Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:47:00.264670Z","title":"Ad- versarial examples in the physical world","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:00.264670Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:50de3cbd858622c367e34081ac2bae099939fd86aa9e63327706e547fd2bc226","observation_id":"9760cb8e-168b-4f92-ba34-701975db1e6a","resolution":{"observed_at":"2026-08-07T11:47:00.264670Z","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":"2026-08-07T11:48:05.198015Z","title":"Functional adversarial attacks","venue":null,"work_id":"1c4a4a9d-233b-4e3e-834c-b4591510195c","year":2019},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:00.307387Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:2f2c1145a0843ac24f5d06a64572418a45913d55c64bd50a60fb8c07f6cd4ed2","observation_id":"3ea8617e-a136-44a1-bd97-8cefd81c5fde","resolution":{"observed_at":"2026-08-07T11:48:05.224921Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:48:05.131844Z","title":"Perceptual adversarial robustness: Defense against unseen threat mod- els","venue":null,"work_id":"dbee6aaa-ef42-4cc3-8550-a35f227b13dd","year":2021},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:00.343067Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:676e1f8ce02bb93fabf8990f9565a4a6aac0fd19c2c0ead6bf8c395ccf8085c0","observation_id":"2d46b2ae-a7ac-4662-95f1-73593896f746","resolution":{"observed_at":"2026-08-07T11:48:05.156429Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:48:05.037679Z","title":"Parrot: Pareto-optimal multi-reward reinforce- ment learning framework for text-to-image generation","venue":null,"work_id":"d1c1748f-0bd9-4e43-8809-3665e1fbf966","year":2024},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:00.379363Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:01bf4e55fcd8e32fbc297adde9356b88ab9df42ddc3a45d5253f4a395bd7f95b","observation_id":"97dd4b90-7b32-4b72-891e-32f0f413551b","resolution":{"observed_at":"2026-08-07T11:48:05.090162Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:48:04.965718Z","title":"Controlnet++: Improving conditional controls with efficient consistency feedback","venue":null,"work_id":"9559eeae-3915-467e-9274-491d3d28aee8","year":2024},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:00.422341Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:15f8f4e9deac85b26fd197475ff3d249ba6c06ec3117e618414c433c05684518","observation_id":"99a45240-eaad-4472-9fe6-4aa46173448f","resolution":{"observed_at":"2026-08-07T11:48:04.992652Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.16031","last_updated":"2022-11-03T01:57:47Z","snapshot_observed_at":"2026-08-01T18:46:18.835120Z","submitted_at":"2022-10-28T10:07:25Z","title":"UPainting: Unified Text-to-Image Diffusion Generation with Cross-modal Guidance","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.16031","snapshot_observed_at":"2026-08-07T11:47:00.459493Z","title":"Upainting: Unified text-to-image diffu- sion generation with cross-modal guidance","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:00.459493Z"},"links":{"cited_paper":"/paper/2210.16031","citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:063c2dfb42cfc4132cbfab8c0e2fa595f12e45bd883317b5a63eeb4cf855b4b2","observation_id":"cee066ff-61d6-4789-a1f8-00d63ab8e5b4","resolution":{"observed_at":"2026-08-07T11:47:00.459493Z","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":"2026-08-07T11:48:04.881559Z","title":"Yuille, and Cihang Xie","venue":null,"work_id":"c218c03b-f014-43d6-904b-f302c354ece4","year":2021},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:00.510055Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:f5609ec0f4d8cde4dd8794dcc4c6cef37880f8a314b7d0451131344380ef12af","observation_id":"dfb36753-dc6c-453e-b6a8-dc6ac927f756","resolution":{"observed_at":"2026-08-07T11:48:04.923074Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:48:04.850865Z","title":"Textcraftor: Your text encoder can be image quality controller","venue":null,"work_id":"7c986238-f3e7-4206-a876-82ecced70b04","year":2024},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:00.568591Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:1ad0e3538ca860f85fc958abda967079bf5becaac119eb8cc59785b26a5f7a55","observation_id":"61e0a788-6acf-4ad0-8dac-1350a19c4a3c","resolution":{"observed_at":"2026-08-07T11:48:04.860735Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.04314","last_updated":"2025-03-25T17:06:27Z","snapshot_observed_at":"2026-08-06T20:07:18.681767Z","submitted_at":"2024-06-06T17:57:09Z","title":"Aesthetic Post-Training Diffusion Models from Generic Preferences with Step-by-step Preference Optimization","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.04314","snapshot_observed_at":"2026-08-07T11:47:00.600957Z","title":"Step-aware prefer- ence optimization: Aligning preference with denoising per- formance at each step","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:00.600957Z"},"links":{"cited_paper":"/paper/2406.04314","citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:165cebd5b8673530860a2d09a56d296f1355709a4914ad1cf50cbf2e1442562c","observation_id":"04fd1a4d-7037-4407-a05a-267e226ce8c3","resolution":{"observed_at":"2026-08-07T11:47:00.600957Z","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":"2026-08-07T11:48:04.824139Z","title":"Defense against adversarial attacks using high-level representation guided denoiser","venue":null,"work_id":"fc957f30-adf1-4600-95c0-48070565870b","year":null},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:00.634469Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:b634af9657ce8c059c85070c8da1298e3baf63839b6f66266ce949aca68d5a4d","observation_id":"41e2e29e-57bc-41f5-8111-6d3f525fd4c5","resolution":{"observed_at":"2026-08-07T11:48:04.834808Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:47:00.669250Z","title":"Alignment of dif- fusion models: Fundamentals, challenges, and future","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:00.669250Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:9e764ac6a93591fc42efd9141c331be2c327cdebc85a2a905480d3f7b7d88f6f","observation_id":"40fe17ee-f828-4215-9a7a-b1734e79b73c","resolution":{"observed_at":"2026-08-07T11:47:00.669250Z","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":"2026-08-07T11:47:00.705257Z","title":"Swin transformer: Hierarchical vision transformer using shifted windows","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:00.705257Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:a510c7f2d45efa4ed69a16473c0c55a0e379c925bbd8e3682433b66a6acf6561","observation_id":"c75af83b-e102-467f-a8ba-b41525bd1d4b","resolution":{"observed_at":"2026-08-07T11:47:00.705257Z","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":"2026-08-07T11:48:04.780679Z","title":"Towards deep learning models resistant to adversarial attacks","venue":null,"work_id":"5f5f1bba-fae4-4eee-91cc-a0200eb9858f","year":2018},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:00.748570Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:8b72aa1a2263089d4529ab4f8924c3db59483a85d00cc3e75284f90812baa9fa","observation_id":"4787b06e-44f4-4275-a3f9-990025f3df12","resolution":{"observed_at":"2026-08-07T11:48:04.791554Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:48:04.744172Z","title":"Mobilevit: Light- weight, general-purpose, and mobile-friendly vision trans- former","venue":null,"work_id":"b36e52a0-e07d-4d87-b6c9-e5bacaac17fe","year":2022},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:00.792019Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:5f8e601202fb8813ea04de29fb5f768fa66103ab4eaa06a54c60a999d4646e8a","observation_id":"87075dfa-cc98-4d77-9d58-4cd16a34c6c8","resolution":{"observed_at":"2026-08-07T11:48:04.757268Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:48:04.711262Z","title":"Ava: A large-scale database for aesthetic visual analysis","venue":null,"work_id":"273edca0-c6f2-4329-a5bd-c4ce2a3bcd71","year":2012},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:49.032618Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:6b816fc53a5d132df39b822290dfe70c92c47797765608477c466bbb8e351a5e","observation_id":"4cdc8a60-89bb-46cc-83a6-bae832459149","resolution":{"observed_at":"2026-08-07T11:48:04.727395Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:48:04.672611Z","title":"Diffusion models for adversarial purification","venue":null,"work_id":"df3a069e-6995-4e96-a27f-62af16ac7a62","year":2022},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:49.594651Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:e8229afee95d2c5abcb17bc2f323deedcf2a231b65d7fd10fbc2aaa31db6ccac","observation_id":"a4b721b9-d6df-4cc0-8b12-a0544a1084fb","resolution":{"observed_at":"2026-08-07T11:48:04.691081Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.02240","last_updated":"2025-05-12T18:56:21Z","snapshot_observed_at":"2026-07-06T19:26:49.672415Z","submitted_at":"2024-10-03T06:25:53Z","title":"SCA: Improve Semantic Consistent in Unrestricted Adversarial Attacks via DDPM Inversion","version":6},"cited_work":{"arxiv_id":"2410.02240","doi":null,"metadata_source":"pith","pith_arxiv_id":"2410.02240","snapshot_observed_at":"2026-08-07T11:47:50.997169Z","title":"SCA: Improve Semantic Consistent in Unrestricted Adversarial Attacks via DDPM Inversion","venue":"cs.CV","work_id":"891fd44b-2119-4b36-a4d1-6ef10e5b70fd","year":2024},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:49.663010Z"},"links":{"cited_paper":"/paper/2410.02240","citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:1d12754047b482f3cb4ee18a9710c02b37933bac67a698490cf76d88fbfa03c4","observation_id":"5a794710-f273-45b3-84e7-c114c7a0c160","resolution":{"observed_at":"2026-08-07T11:47:51.044422Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.03739","last_updated":"2024-11-07T03:54:22Z","snapshot_observed_at":"2026-07-06T16:28:22.350574Z","submitted_at":"2023-10-05T17:59:18Z","title":"Aligning Text-to-Image Diffusion Models with Reward Backpropagation","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.03739","snapshot_observed_at":"2026-08-07T11:47:49.716814Z","title":"Aligning text-to-image diffusion models with reward backpropagation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:49.716814Z"},"links":{"cited_paper":"/paper/2310.03739","citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:5adc83f27a9f18e9e1690cc18f47c39728a41afc40af0c67922a2f9a9dad394a","observation_id":"b9966f4a-cca6-4203-8db1-7c4ffaa55f5c","resolution":{"observed_at":"2026-08-07T11:47:49.716814Z","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":"2026-08-07T11:48:04.630204Z","title":"Semanticadv: Generating adver- sarial examples via attribute-conditioned image editing","venue":null,"work_id":"a2b878db-5dae-4b55-8500-ed27e25a127f","year":2020},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:49.779187Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:fb29348a29ccef305b5558148ae2372b9fc504cabcb2b4f2e5aa772074ac81de","observation_id":"c7bc4ce8-9ad3-44e3-918d-16cbbd1f9d47","resolution":{"observed_at":"2026-08-07T11:48:04.649015Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:48:04.585151Z","title":"Learn- ing transferable visual models from natural language super- vision","venue":null,"work_id":"df93cfa9-571a-4576-9647-3dc96a146911","year":2021},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:49.835131Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:2c030323aab7ad1f1d6d9c64c3c950ac781e14f2c29ec75f27feab5cacbbccf3","observation_id":"bc87b0b6-feac-4c1c-ae70-7a6c569b985a","resolution":{"observed_at":"2026-08-07T11:48:04.608923Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:48:04.539393Z","title":"High-resolution image syn- thesis with latent diffusion models","venue":null,"work_id":"4363b6fe-d38c-4b50-ab5d-d694c36eab5d","year":2022},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:49.919265Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:133a35db4e0ce5eb87f53ac0c37662c7c2109171be1a7aefac90ca295cdaad44","observation_id":"4f0a6394-e513-439f-8979-eb13dd4f3ab9","resolution":{"observed_at":"2026-08-07T11:48:04.561319Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:48:04.505978Z","title":"Howard, Menglong Zhu, Andrey Zhmoginov, and Liang-Chieh Chen","venue":null,"work_id":"5ee7e0cc-ab12-491e-a6a6-ed8a14fb3bfd","year":2018},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:49.987207Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:0eef2cfaca463af690ef77e4b1663c4bce90477255d7f0498cfb884cd5f6852e","observation_id":"6c9d8e1c-f66d-43b2-9e47-8de1e7b8fe27","resolution":{"observed_at":"2026-08-07T11:48:04.517879Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1707.06347","last_updated":"2017-08-28T09:20:06Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2017-07-20T02:32:33Z","title":"Proximal Policy Optimization Algorithms","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1707.06347","snapshot_observed_at":"2026-08-07T11:47:50.046492Z","title":"Proximal policy optimization algo- rithms","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:50.046492Z"},"links":{"cited_paper":"/paper/1707.06347","citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:43cb638e40b7ac5af493e31d853080a150f104aa6d392ff2c529cfd81af97f08","observation_id":"06ea9c27-7beb-4067-ba2b-ea1c451f6875","resolution":{"observed_at":"2026-08-07T11:47:50.046492Z","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":"2026-08-07T11:48:04.470374Z","title":"Colorfool: Semantic adversarial coloriza- tion","venue":null,"work_id":"6b8e84df-ad84-4978-88da-9e1d7f1201e7","year":2020},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:50.079217Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:b7c6e341ea08b734a8f5904f0edae57c81ecd2f57747038df5b8a8d322abad3b","observation_id":"e57f083d-db5e-4c1c-a8fa-77fbb17968dd","resolution":{"observed_at":"2026-08-07T11:48:04.483861Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:48:04.436039Z","title":"Revisiting adversarial training for imagenet: Architectures, training and generalization across threat models","venue":null,"work_id":"d144ae6e-f2b8-4222-8df6-9af5fb027bb2","year":null},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:50.149434Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:0ec7081013740b0722074d957ab830dc9da83891f51f87eda914dd782622a1e3","observation_id":"ed0b3181-c290-45c7-9a10-bc7f208a678b","resolution":{"observed_at":"2026-08-07T11:48:04.447622Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:47:50.207225Z","title":"Denois- ing diffusion implicit models","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:50.207225Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:9906be5968759d445f89aa4d18f1ff4050ec5b42dbdcad3cda50c6972c7b36b5","observation_id":"43180df5-13ef-4a12-b1be-5d9161c6e9b1","resolution":{"observed_at":"2026-08-07T11:47:50.207225Z","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":"2026-08-07T11:48:04.390888Z","title":"Rethinking the in- ception architecture for computer vision","venue":null,"work_id":"1ebf727a-a640-4611-b049-9215e75ddc2f","year":2016},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:50.268530Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:c423415385e6a645f01ba32520b0bf59e6f1d47f1a1ca91749f1e1870423f7ff","observation_id":"2bb2840b-5dc9-43ea-a85c-690a4dded643","resolution":{"observed_at":"2026-08-07T11:48:04.403690Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:48:04.358398Z","title":null,"venue":null,"work_id":"c9a4e4e3-e57b-46a2-86a9-5f9d289826ae","year":null},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:50.310860Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:15dc2ee390449102e8f36785d8fb91fc676ac9e5b6d4f5cdd923afbf180f5cd1","observation_id":"c7a83b7e-e6a0-4d3f-ab91-335016d93606","resolution":{"observed_at":"2026-08-07T11:48:04.369697Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:48:04.325250Z","title":"Goodfellow, Dan Boneh, and Patrick D","venue":null,"work_id":"216ef68e-fc42-4854-9884-8ad3375aa194","year":null},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:50.357770Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:2baa6ce0a84f512b741cbe7c605591a89e347cb3f3e0a79fe4101ea6ffdfa80a","observation_id":"fa40cfce-7466-4054-8bfe-3b109654cab1","resolution":{"observed_at":"2026-08-07T11:48:04.338421Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:48:04.293226Z","title":"Diffusion model align- ment using direct preference optimization","venue":null,"work_id":"123b8b03-1dee-4a5f-a427-4ee2306ba40b","year":2024},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:50.408993Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:d9f2f240e16c0a4ea5c1bb74763f12a3f8e99576ed15ec0b0d71da37b85701e1","observation_id":"cc62e51d-6bb6-4a94-a1f7-9adb7145cb3e","resolution":{"observed_at":"2026-08-07T11:48:04.307539Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:48:04.262778Z","title":"PVT v2: Improved baselines with pyramid vision transformer","venue":null,"work_id":"0c89ab2f-b32c-4072-9290-4d8646655b1b","year":2022},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:50.456187Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:9c1660cf178bb8385922c1a302b5cb990ca9e407ccfd924d866a811de7df5f17","observation_id":"14d7f804-c2d9-44a2-ac41-fdd873a27378","resolution":{"observed_at":"2026-08-07T11:48:04.275533Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:47:52.201949Z","title":"Struc- ture invariant transformation for better adversarial transfer- ability","venue":null,"work_id":"a11afa6e-e385-4c6d-90f7-8f58b03fb4df","year":2023},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:50.493145Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:6f38becea9f342371e1282f18b1ef53a83de67d5d91417cb2a7fcf939e1e659c","observation_id":"3fb66acb-6fd4-4e4f-bfd5-67710f17db7a","resolution":{"observed_at":"2026-08-07T11:47:52.231210Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:47:52.089674Z","title":"Spatially transformed adversarial ex- amples","venue":null,"work_id":"1b18d3ea-aa93-4944-bf38-c0dee630ee0d","year":2018},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:50.554174Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:d8166f5e8ce840e9eac79f31d42d881e6a2de6219f55a5fae7d2ff90c8498668","observation_id":"74599fff-d08a-4035-a99a-7526d5dff110","resolution":{"observed_at":"2026-08-07T11:47:52.157996Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:47:52.012270Z","title":null,"venue":null,"work_id":"61e3fd33-6486-4f84-af94-c130059a9cbe","year":2018},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:50.587600Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:03fa03e5ee7281d0dddd0301979ca31083559d0e4da3f5f9926c5386ec30ae5b","observation_id":"2fa9c23a-5852-4e32-9392-c84456b3d8b0","resolution":{"observed_at":"2026-08-07T11:47:52.044009Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:47:51.928185Z","title":"Improving transferabil- ity of adversarial examples with input diversity","venue":null,"work_id":"4d4feac0-9a22-4d8a-af95-05c3de47aa55","year":null},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:50.633872Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:15a8f587a592eb9e8bf7b447dc41f76984eacbc2ec19ab37bbed01c943b5eec1","observation_id":"7c315343-3f04-4d26-b713-1104a984b7a4","resolution":{"observed_at":"2026-08-07T11:47:51.956449Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:47:51.866252Z","title":"Feature squeezing: Detecting adversarial examples in deep neural networks","venue":null,"work_id":"a20b6f5b-f7c6-406a-af79-345fbf5a660d","year":2018},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:50.668703Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:0a59c9d1946e4379d9db335760adae4d010429cd255d0220826fe2d9c8d9f3cb","observation_id":"1ecadb49-7865-4a40-b4d7-3bc83eaafaa2","resolution":{"observed_at":"2026-08-07T11:47:51.893554Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:47:51.806525Z","title":"Diffusion-based adversarial sample generation for improved stealthiness and controllability","venue":null,"work_id":"d8dd2204-7211-4d39-8954-aa357289ec39","year":2023},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:50.719702Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:2624461cb9ff87f76b8dd4fd45ce3a8322c6d9869277de680775b30a3378dfc4","observation_id":"81c33e61-cfa2-4923-a750-6b8668bc97cb","resolution":{"observed_at":"2026-08-07T11:47:51.821726Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:47:51.666651Z","title":"Natural color fool: Towards boosting black-box unrestricted attacks","venue":null,"work_id":"bc62c1f3-d568-4f41-91a4-7ee8dbbea5db","year":2022},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:50.763291Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:017ff7cadf92f4b250ebebff6ee1202fe7b3ce1e53c54bd75c11b0e7063b9bb3","observation_id":"df7b8ffa-0880-4de4-a46a-937601d206a4","resolution":{"observed_at":"2026-08-07T11:47:51.767361Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:47:51.494930Z","title":"Diffmorpher: Unleashing the capability of diffu- sion models for image morphing","venue":null,"work_id":"567fb8fa-51b6-4e84-90c0-963c46f72c07","year":2024},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:50.848088Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:21fb5832c4aa48e322081aba5b00844f8e864e6e81636eb9ba8a6e5d761d8109","observation_id":"44b7b892-89b8-47ac-af34-38f3f3cbf4a9","resolution":{"observed_at":"2026-08-07T11:47:51.572895Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:47:51.303096Z","title":null,"venue":null,"work_id":"5dc1faf5-c8db-4f96-a63e-a5c740ea2541","year":2020},"citing_paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment","version":1},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:50.880083Z"},"links":{"citing_paper":"/paper/2506.01511"},"observation_digest":"sha256:7d45a3b236d0ad9f4ebeaefa7f6504ff935772c4eca94eebb279f912b45e7f27","observation_id":"d466b596-bcfa-4dee-bc33-9719f100b718","resolution":{"observed_at":"2026-08-07T11:47:51.387749Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2506.01511","last_updated":"2025-06-02T10:18:09Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-10T04:13:20.707758Z","submitted_at":"2025-06-02T10:18:09Z","title":"Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment"},"reference_resolution":{"displayed":70,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":14,"verified_exact":1,"verified_fuzzy":55},"total_outbound_references":70},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 70 of 70 outbound references and 1 inbound Pith citation observation for arXiv:2506.01511."}