{"as_of":"2026-08-08T13:11:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:d1a0a4e0bd8c6a88fd112e5a785984865ca41bb2dec9d5b9224b0716aa016c05","coverage":[{"denominator":69,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":69,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T15:25:00.131075Z","state":"measured"},{"denominator":73,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":73,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":4,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":4,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-04T12:27:30.763780Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-06-30T10:04:36.130406Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.15441","snapshot_observed_at":"2026-08-04T12:27:30.763780Z","title":"o m, Johan Edstedt, Fredrik Kahl, and Georg B \\","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2510.03511","last_updated":"2026-06-02T22:28:21Z","snapshot_observed_at":"2026-08-04T12:27:29.054298Z","submitted_at":"2025-10-03T20:51:25Z","title":"Platonic Transformers: A Solid Choice For Equivariance","version":3},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-04T12:27:30.763780Z"},"links":{"cited_paper":"/paper/2505.15441","citing_paper":"/paper/2510.03511"},"observation_digest":"sha256:53d8fd3b1da98ba3ed537f71450d90901c8880e6ebfc3b0b1b051e52f01acf2f","observation_id":"a9be8c19-4284-4297-a167-a0398f5b1dac","resolution":{"observed_at":"2026-08-04T12:27:30.763780Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"cited_work":{"arxiv_id":"2505.15441","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2505.15441","snapshot_observed_at":"2026-07-07T03:18:46.986811Z","title":"Stronger vits with octic equivariance","venue":null,"work_id":"f73a4a8e-c6aa-42ab-8558-132aef2dff77","year":2025},"citing_paper":{"arxiv_id":"2604.11809","last_updated":"2026-04-13T17:59:58Z","snapshot_observed_at":"2026-07-06T23:00:08.171601Z","submitted_at":"2026-04-13T17:59:58Z","title":"Who Handles Orientation? Investigating Invariance in Feature Matching","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-05-10T15:06:13.894356Z"},"links":{"cited_paper":"/paper/2505.15441","citing_paper":"/paper/2604.11809"},"observation_digest":"sha256:a346650908022ce5cda8aa0199f38eed53f102c33af1f7a7f0b236132ed0109b","observation_id":"6f5e8a57-bb5f-4ff4-84a1-9bf866a8ca89","resolution":{"observed_at":"2026-07-07T03:18:46.986811Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"cited_work":{"arxiv_id":"2505.15441","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2505.15441","snapshot_observed_at":"2026-07-07T03:18:46.986811Z","title":"Stronger vits with octic equivariance","venue":null,"work_id":"f73a4a8e-c6aa-42ab-8558-132aef2dff77","year":2025},"citing_paper":{"arxiv_id":"2606.27864","last_updated":"2026-06-29T08:45:30Z","snapshot_observed_at":"2026-08-01T05:39:17.476652Z","submitted_at":"2026-06-26T09:05:47Z","title":"A Unified Framework for Vision Transformers Equivariant to Discrete Subgroups of $\\mathrm{O}(2)$","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-06-29T04:37:29.865733Z"},"links":{"cited_paper":"/paper/2505.15441","citing_paper":"/paper/2606.27864"},"observation_digest":"sha256:dc344e5bbc90f2c086ee37d7e8c5f9aa473b89cfa8269a19e3cc4612c0dba92c","observation_id":"959c1bd3-4cd5-41d9-bc60-2a1beea51387","resolution":{"observed_at":"2026-07-07T03:18:46.986811Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"cited_work":{"arxiv_id":"2505.15441","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2505.15441","snapshot_observed_at":"2026-07-07T03:18:46.986811Z","title":"Stronger vits with octic equivariance","venue":null,"work_id":"f73a4a8e-c6aa-42ab-8558-132aef2dff77","year":2025},"citing_paper":{"arxiv_id":"2606.27864","last_updated":"2026-06-29T08:45:30Z","snapshot_observed_at":"2026-08-01T05:39:17.476652Z","submitted_at":"2026-06-26T09:05:47Z","title":"A Unified Framework for Vision Transformers Equivariant to Discrete Subgroups of $\\mathrm{O}(2)$","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-06-30T09:59:55.032554Z"},"links":{"cited_paper":"/paper/2505.15441","citing_paper":"/paper/2606.27864"},"observation_digest":"sha256:d8ff78d02689c876ce56f2ae0289d0cb28a41252bb43fbde97b269cfccd0894b","observation_id":"6a117b49-53d8-4dc6-863a-a1acaadf77d2","resolution":{"observed_at":"2026-07-07T03:18:46.986811Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2505.15441/citation-record","integrity":"/paper/2505.15441/integrity","json":"/paper/2505.15441/citation-record.json","paper":"/paper/2505.15441"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:24:56.665763Z","title":"write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-07T15:24:56.665763Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:8e078cea1dded3a3183b0194b24668ae197d38370d81e75ffc883d88746b5dd5","observation_id":"bbde78ef-2731-47fe-9e57-760ed0ae9bd1","resolution":{"observed_at":"2026-08-07T15:24:56.665763Z","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":"2026-08-07T15:24:56.728074Z","title":"@esa (Ref","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-07T15:24:56.728074Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:cf0ce2935f061554b555da84192cfa8ea4bd5070438267cccdd387cce230b340","observation_id":"01c3b81a-edba-4007-b7a7-ed4f423763aa","resolution":{"observed_at":"2026-08-07T15:24:56.728074Z","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":"2026-08-07T15:24:56.801523Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-07T15:24:56.801523Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:4b15cb53d5d592f14765b718b23ed2d5b3dda6b75af9da796ad81b4d0703ea39","observation_id":"677ab94a-43ef-422d-84ed-e67708d7dd15","resolution":{"observed_at":"2026-08-07T15:24:56.801523Z","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":"2026-08-07T15:25:01.661016Z","title":null,"venue":null,"work_id":"3409108b-32cd-4872-8070-405cfe337423","year":null},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-07T15:24:56.911514Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:d855c09da956b8b84a98c9da0d8d2fc47a8f9a1b7e0817cfb04a8afbf74f8045","observation_id":"dd47ed3d-a8f4-4a56-97f0-d24e9f54e3b8","resolution":{"observed_at":"2026-08-07T15:25:01.665793Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T15:24:57.003786Z","title":"Accurate structure prediction of biomolecular interactions with alphafold 3","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-07T15:24:57.003786Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:acb477da4851c13f2d48000b35405dc026ba5f57d653469134f0b1080a2f4bba","observation_id":"d9986c00-5005-46c0-b8b6-ab78941d8af3","resolution":{"observed_at":"2026-08-07T15:24:57.003786Z","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":"2026-08-07T15:25:01.644099Z","title":"Getting vit in shape: Scaling laws for compute-optimal model design","venue":null,"work_id":"a456f763-33cc-465c-890f-e2f0c86a04d1","year":2023},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-07T15:24:57.047687Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:6c8ff29ec23cc2aa7b790a50ac0112e93b8a5424a876a7b48b01e62f2e0a240a","observation_id":"5a7838e7-4130-458b-9f2f-3a220c078e16","resolution":{"observed_at":"2026-08-07T15:25:01.647307Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T15:25:01.633374Z","title":"Vn-transformer: Rotation-equivariant attention for vector neurons","venue":null,"work_id":"ab739448-a9b7-4d9a-8428-93448aa0440d","year":2023},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-07T15:24:57.098576Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:6c026ec73844e589694177555f1097446c6615cef018771621bf413c9b82a0b0","observation_id":"5d9e5b79-2b3d-4fb4-9de7-5b689d84d6ee","resolution":{"observed_at":"2026-08-07T15:25:01.636695Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T15:25:01.623353Z","title":"How to scale your model","venue":null,"work_id":"aba194dc-b969-4b0c-81be-24b5cf28bfb5","year":2025},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-07T15:24:57.211394Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:4e9b4fd2969850ebbbd522fe27fa5a48636cb6daeba6020b080dd51c84727ac2","observation_id":"e30d4d6e-7c20-4958-b957-449c47129dab","resolution":{"observed_at":"2026-08-07T15:25:01.626989Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T15:25:01.613043Z","title":"Roto-translation covariant convolutional networks for medical image analysis","venue":null,"work_id":"d1763fbf-1dc6-49e5-8d80-3bc95dbafffd","year":2018},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-07T15:24:57.300351Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:d501a6a8dfd5730f9ecdf3fa8936276ef95c188174e297b1f3c1e4de567d8dc4","observation_id":"853b16d9-9877-40d1-a3d1-5a7bee12ea73","resolution":{"observed_at":"2026-08-07T15:25:01.616532Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T15:24:57.401554Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-07T15:24:57.401554Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:ceef2d1a28c0d1160612a43e1626c26b5897e937c3f856ab08ead4c140a03fe7","observation_id":"b6ce0b7d-f608-49c6-b58d-40ed676c7a9f","resolution":{"observed_at":"2026-08-07T15:24:57.401554Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.13986","last_updated":"2025-05-08T23:11:05Z","snapshot_observed_at":"2026-07-06T20:25:12.962104Z","submitted_at":"2025-01-23T08:20:47Z","title":"An Efficient Sparse Kernel Generator for O(3)-Equivariant Deep Networks","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.13986","snapshot_observed_at":"2026-08-07T15:24:57.516131Z","title":"An Efficient Sparse Kernel Generator for O(3)-Equivariant Deep Networks","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-07T15:24:57.516131Z"},"links":{"cited_paper":"/paper/2501.13986","citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:099a9d9f40b7f64ae1eaa32e0df068b3c33d85355d45f004486094936b49bfc1","observation_id":"3bd2a9cf-6352-4f3a-a3ba-679f933ca5fa","resolution":{"observed_at":"2026-08-07T15:24:57.516131Z","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":"2026-08-07T15:25:01.596055Z","title":"o kman, David Nordstr \\","venue":null,"work_id":"372b0347-3a82-4612-8171-37ed3183e156","year":2025},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-07T15:24:57.614315Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:6dfe794598c1b746160dbcd70f6f5f810d8f50e8f3842e0dcc837e922c2f134a","observation_id":"34f3dbb6-4662-4648-8d25-94a0defc6851","resolution":{"observed_at":"2026-08-07T15:25:01.599198Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T15:25:01.586153Z","title":"Does equivariance matter at scale? Transactions on Machine Learning Research, 2025","venue":null,"work_id":"9a2c407c-a430-4b41-a316-026c8f8e8645","year":2025},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-07T15:24:57.701324Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:81480e183e3e4ab479d1af9891545179dec07fa856014b9077b351f5b688d727","observation_id":"2cac53fe-7815-4e95-8841-3e4e8c4a564e","resolution":{"observed_at":"2026-08-07T15:25:01.589647Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T15:25:01.575982Z","title":"Group-invariant max filtering","venue":null,"work_id":"75d7ebba-869b-403d-97bb-76a07d37311f","year":2024},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-07T15:24:57.774739Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:83ef72243b82d412976f05bd7299b54669829a37f1116cdf3101c20e2ba7ea1e","observation_id":"3179e332-da79-44d7-ae34-59ca306cd42c","resolution":{"observed_at":"2026-08-07T15:25:01.579105Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T15:24:57.855836Z","title":"End-to-end object detection with transformers","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-07T15:24:57.855836Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:77ae0d1715e7c1f91cca3a336b3ff69a50eb4292dfc611cd56444b80138c2f2c","observation_id":"7aa98e4b-4989-41c0-a343-3e557f7e159c","resolution":{"observed_at":"2026-08-07T15:24:57.855836Z","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":"2026-08-07T15:25:01.566915Z","title":"Sparsevit: Revisiting activation sparsity for efficient high-resolution vision transformer","venue":null,"work_id":"da8fc6cf-1145-440c-b992-0d9106b81370","year":2023},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-07T15:24:57.962103Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:975bc9df707df5cbb9c3d4f1285346844e0528d68bc5c7e081ef0e2222ab31fc","observation_id":"ce8086ae-52f1-4286-9a59-b3c7b72b0f42","resolution":{"observed_at":"2026-08-07T15:25:01.570106Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T15:24:58.082342Z","title":"Group equivariant convolutional networks","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-07T15:24:58.082342Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:98609de7081d480fb97dd26de8769ba53ca46e0dacae9deea1ea621be5235c38","observation_id":"1e440d77-a292-469b-a512-e5793cda4fdc","resolution":{"observed_at":"2026-08-07T15:24:58.082342Z","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":"2026-08-07T15:25:01.552516Z","title":"Steerable CNN s","venue":null,"work_id":"dfe588e8-e6e7-4b86-a2a4-b41ca54444bb","year":2017},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-07T15:24:58.190410Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:b7928ac6ee83fcc24f53b7d829cd1004321a91e4281fd17d72b5ed3dc85f343d","observation_id":"fb29af2d-a095-4127-88dd-a6b53096ae57","resolution":{"observed_at":"2026-08-07T15:25:01.555924Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T15:24:58.284285Z","title":"Flash A ttention-2: Faster attention with better parallelism and work partitioning","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-07T15:24:58.284285Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:e2ae4fc08d7a554a2bb2ac11cfd7c717006ede2d3195d77fd42c8a590a420ed7","observation_id":"fafee053-559f-495d-8f85-425b7d1fcab5","resolution":{"observed_at":"2026-08-07T15:24:58.284285Z","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":"2026-08-07T15:25:01.537546Z","title":"Cluster and predict latents patches for improved masked image modeling","venue":null,"work_id":"a994b98d-1f54-454a-95c6-42d6b9664d8e","year":2025},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-07T15:24:58.359833Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:77d945439b3efca0305cc1d779550da1b4e3735fe62f6e79093290da08040ae2","observation_id":"440e3251-3bbc-499b-8ec0-39ab22dea2fa","resolution":{"observed_at":"2026-08-07T15:25:01.540977Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T15:25:01.527776Z","title":null,"venue":null,"work_id":"0e6941aa-7226-4306-8e7d-2ef5603ae946","year":2023},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-07T15:24:58.422557Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:0436a1d831a3af0d69ef349ac6ea6bbe7b788414fb780b0c00599fbdd47315b1","observation_id":"b9eefcc2-4de2-4623-a72c-aa1ccccdc7cf","resolution":{"observed_at":"2026-08-07T15:25:01.530806Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T15:24:58.506512Z","title":"Imagenet: A large-scale hierarchical image database","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-07T15:24:58.506512Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:60a886ae73413e843f189fed45cc80da1493396309122ec218c09b7b0c86f029","observation_id":"876d975a-e885-4dd5-ba31-61240268f68b","resolution":{"observed_at":"2026-08-07T15:24:58.506512Z","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":"2026-08-07T15:25:01.517157Z","title":"Exploiting cyclic symmetry in convolutional neural networks","venue":null,"work_id":"a38d9ea3-3ce9-438c-ad4b-370bc9cbc0c7","year":2016},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-07T15:24:58.596019Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:2d0c07690fc2b565e94b049868251c695ccff526f3876617b500bd828bcbf8eb","observation_id":"3cac26f9-8337-427b-b742-5588855e3f40","resolution":{"observed_at":"2026-08-07T15:25:01.520696Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T15:24:58.715060Z","title":"An image is worth 16x16 words: Transformers for image recognition at scale","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-07T15:24:58.715060Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:829194810a6669c2651f095f6885d17de588177bcb22f659b875c02e221b1bef","observation_id":"3932664e-0165-4365-812e-3b7ff2f61637","resolution":{"observed_at":"2026-08-07T15:24:58.715060Z","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":"2026-08-07T15:25:01.501062Z","title":"RoMa: Robust Dense Feature Matching","venue":null,"work_id":"9784db7f-5c9c-4361-ae1c-8d76cedac7d9","year":2024},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-07T15:24:58.772009Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:39d192acb359aa7b3b3a9aeda2c9d5b2ef20a5a497b0fc0558a9c6b573869251","observation_id":"04aa91e7-d192-45a7-84b4-a50db98acff9","resolution":{"observed_at":"2026-08-07T15:25:01.504604Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T15:24:58.857404Z","title":"The pascal visual object classes (voc) challenge","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-07T15:24:58.857404Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:4032628dc96c5fb2444179f29453c766ef4dfd0937649e800f75e60917fae3a3","observation_id":"e3d38edd-e969-4d9b-a3e9-9bb93a3b8ee7","resolution":{"observed_at":"2026-08-07T15:24:58.857404Z","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":"2026-08-07T15:25:01.490962Z","title":"The invariantring package for macaulay2","venue":null,"work_id":"f3686d71-493c-4f47-9d77-7bd45dd12fb7","year":2024},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-07T15:24:58.904614Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:e31e3fdbf32cb1dbbe743dbc9d35f4f198f88c44c037eccc186b559d4b23aa70","observation_id":"1969a6a1-9730-4634-8f21-c36088e40aae","resolution":{"observed_at":"2026-08-07T15:25:01.493941Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T15:25:01.482394Z","title":"Fuchs, Daniel E","venue":null,"work_id":"0946bcbc-691b-4129-b68f-b33c76cc02a1","year":2020},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-07T15:24:58.976486Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:a03c82c67b7974e41de16fd4e3bf292910e742a84ca537dc76ecb8d3065e4ae2","observation_id":"52bb86f6-0da0-484e-8b3c-94efe6cc7e44","resolution":{"observed_at":"2026-08-07T15:25:01.485208Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T15:24:59.012570Z","title":"Grayson and Michael E","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-07T15:24:59.012570Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:de3e923ba7dda760d81aae628ad897e39ad86fe3d379815bdbab92ce92a6848c","observation_id":"c7248ed7-e4dd-44d3-8c5f-700cbdfb709d","resolution":{"observed_at":"2026-08-07T15:24:59.012570Z","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":"2026-08-07T15:25:01.468700Z","title":"Neighborhood attention transformer","venue":null,"work_id":"a1b073dc-616e-4200-a8e8-37965110f18f","year":2023},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-07T15:24:59.119733Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:cdb606129dc9d9e5fbd500e88c6d276f8c933c48e06ced46645a29434e0f7c4f","observation_id":"1f6bb21c-3891-43e2-98af-3170b4c16153","resolution":{"observed_at":"2026-08-07T15:25:01.471376Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T15:25:01.461016Z","title":"Efficient equivariant network","venue":null,"work_id":"00caf373-984d-49c5-bcc5-fb40e9b2e185","year":2021},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-07T15:24:59.187070Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:3507f711e3a0f975d37a5ec6b35f741fc8c0e85cd787c42deb19199a83e1c285","observation_id":"9bfd56da-e94f-4669-b48d-cb3aff50b498","resolution":{"observed_at":"2026-08-07T15:25:01.463574Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1606.08415","last_updated":"2023-06-06T01:53:32Z","snapshot_observed_at":"2026-07-06T05:01:27.910364Z","submitted_at":"2016-06-27T19:20:40Z","title":"Gaussian Error Linear Units (GELUs)","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1606.08415","snapshot_observed_at":"2026-08-07T15:24:59.238459Z","title":"Gaussian error linear units (gelus)","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-07T15:24:59.238459Z"},"links":{"cited_paper":"/paper/1606.08415","citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:c512f5cedcb0608ebe719d65dd63687415029a4043b719aa8c4ae9a32f2ce7c3","observation_id":"6a0818ae-84b2-437e-8773-d6fbae098627","resolution":{"observed_at":"2026-08-07T15:24:59.238459Z","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":"2026-08-07T15:25:01.452448Z","title":"Lietransformer: Equivariant self-attention for lie groups","venue":null,"work_id":"9596929d-2ff7-4e3a-8f3f-0d7eb5053796","year":2021},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-07T15:24:59.336107Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:d0ae439f3ddbc47aa63850b11c25fd7aa500fac332919ea48a21f8d64a366f5b","observation_id":"b9a62267-ae79-4634-9dfd-1391eb3f2cf3","resolution":{"observed_at":"2026-08-07T15:25:01.455821Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T15:25:01.444218Z","title":"Equivariance with learned canonicalization functions","venue":null,"work_id":"1bf13a28-7d1c-4c12-9c79-f3e5e2d0cb99","year":2023},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-07T15:24:59.405692Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:827858279bfbb497bcf9915232f2ef513910b0bc9cb622743aa74662aa4a7d8a","observation_id":"984f466b-1ac3-4080-adc2-585d0ed62b35","resolution":{"observed_at":"2026-08-07T15:25:01.447247Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T15:25:01.434369Z","title":"The bispectrum as a source of phase-sensitive invariants for fourier descriptors: a group-theoretic approach","venue":null,"work_id":"7a1b14c5-f9a8-441d-89e2-c3fca10dc292","year":2012},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-07T15:24:59.516102Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:c9f7ec8de0f0d38324f12de5b15034f669d4b2e9da1dce349b92eca831321ff0","observation_id":"56f99f12-68b2-4576-a86d-c15a34758035","resolution":{"observed_at":"2026-08-07T15:25:01.437811Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2001.08361","last_updated":"2020-01-23T03:59:20Z","snapshot_observed_at":"2026-07-06T08:52:12.656082Z","submitted_at":"2020-01-23T03:59:20Z","title":"Scaling Laws for Neural Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2001.08361","snapshot_observed_at":"2026-08-07T15:24:59.577874Z","title":"Scaling laws for neural language models","venue":null,"work_id":null,"year":2001},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-07T15:24:59.577874Z"},"links":{"cited_paper":"/paper/2001.08361","citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:f705a561a0cd4bba2d5ac902b89919d1728219414303c4ce7a03759a1c45b527","observation_id":"14716639-babc-4242-b0ce-2ef7127cd55a","resolution":{"observed_at":"2026-08-07T15:24:59.577874Z","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":"2026-08-07T15:25:01.424929Z","title":"Berg, Wan-Yen Lo, Piotr Dollar, and Ross Girshick","venue":null,"work_id":"b41b0ef6-96e2-4c1c-931d-b2b8c30944a3","year":2023},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-07T15:24:59.674663Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:a3243db86f67ad36626d7138d4ce24af8d67a58e2e2feeb9938db4824d5918aa","observation_id":"992a2c43-b201-43ca-b9b3-94b69edf5577","resolution":{"observed_at":"2026-08-07T15:25:01.427730Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T15:25:01.415925Z","title":"Dinobloom: a foundation model for generalizable cell embeddings in hematology","venue":null,"work_id":"93c2a47d-ca14-4450-a542-8e3657135d6b","year":2024},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-07T15:24:59.805402Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:e9711b704367c49772288a642845c116ec5730c8a80dfa8376e0bfbeb264c8df","observation_id":"b13db8d9-780d-4428-bf4a-cb88eed5ae65","resolution":{"observed_at":"2026-08-07T15:25:01.418984Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T15:25:01.406772Z","title":"Steerable transformers for volumetric data","venue":null,"work_id":"92e984dd-f2fa-42c8-9849-0d06f33ea34f","year":2025},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-07T15:24:59.960266Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:aec5ed3bcfc597b8ccb72eecc0fa3baa6e4ea0e13a31b410c41c51404d7bfe32","observation_id":"4fd2b8d2-faef-4c0f-acb0-a4b7923fc8cf","resolution":{"observed_at":"2026-08-07T15:25:01.410416Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T15:25:01.397817Z","title":"Equiformer: Equivariant graph attention transformer for 3d atomistic graphs","venue":null,"work_id":"d17c2c84-cf65-41ce-a9f5-e06a12df860f","year":2023},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-07T15:25:00.039434Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:f920835a939a9c46f31295ce39e20ca34f73f559f06c7f0f2a45c0947264328f","observation_id":"3c99fe2a-704c-45f3-8ba9-8398426ff886","resolution":{"observed_at":"2026-08-07T15:25:01.400769Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T15:25:00.042971Z","title":"Swin transformer: Hierarchical vision transformer using shifted windows","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-07T15:25:00.042971Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:27bbc6fb6e0f48edef195515b16a09f4545d254431317f058dedc8586fd2f6b6","observation_id":"6434e677-4eba-44c8-a1bd-26cdbff7f382","resolution":{"observed_at":"2026-08-07T15:25:00.042971Z","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":"2026-08-07T15:25:00.046384Z","title":"An expert-annotated dataset of bone marrow cytology in hematologic malignancies","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-07T15:25:00.046384Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:bd771c0f782450faa64f3a57e8c383901fa0bf2fef49e960b2816b8fa7b06f57","observation_id":"0c38a006-955e-4e62-a104-52ee698ad3c7","resolution":{"observed_at":"2026-08-07T15:25:00.046384Z","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":"2026-08-07T15:25:01.389530Z","title":"cuEquivariance : High-performance equivariant neural networks","venue":null,"work_id":"1ee3528e-aa4f-40f7-b9f5-00bc8ef4db97","year":null},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-08-07T15:25:00.049897Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:17d6bc49e25a1e861d70c6559601ec2b0c92882452e3ee6da0b284c424e005ed","observation_id":"0c84bdb6-34c5-44c7-8cf9-ec9f0075c3f4","resolution":{"observed_at":"2026-08-07T15:25:01.392412Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T15:25:00.053461Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-08-07T15:25:00.053461Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:b6af1dde5bb324c67c72d5dcd472483f452b08e4ec3a931d95e85b287bc4eb05","observation_id":"89a22307-641c-4434-8a60-38bf04ad771d","resolution":{"observed_at":"2026-08-07T15:25:00.053461Z","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":"2026-08-07T15:25:01.374106Z","title":"Pytorch: An imperative style, high-performance deep learning library","venue":null,"work_id":"fb128fc2-da18-4fe0-bd1b-0812390a8dd3","year":2019},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-07T15:25:00.056620Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:2443d6fc5922f967a44a273c675e59c9d08b781770df283d0662b619463795bc","observation_id":"ac162541-b0e3-4e3f-8f7c-28b5cb477e0d","resolution":{"observed_at":"2026-08-07T15:25:01.377262Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T15:25:00.059876Z","title":"Learning transferable visual models from natural language supervision","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-08-07T15:25:00.059876Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:43a5170cac03ec2600478753b1efbe3a9ef01e48990ca25851851b7a9d681fea","observation_id":"073f9b7f-a775-43eb-9dc6-a52308e6c746","resolution":{"observed_at":"2026-08-07T15:25:00.059876Z","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":"2026-08-07T15:25:01.357719Z","title":null,"venue":null,"work_id":"7b0acbd7-8a2f-41e4-806b-aadc761f80c8","year":2019},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-08-07T15:25:00.063396Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:9ce7c933b7411f06d322ffde14858d6e88412a474918c393b7cd325af3a7d5d8","observation_id":"050e85e7-1670-49c7-92e1-5e08ce5ceb3a","resolution":{"observed_at":"2026-08-07T15:25:01.360891Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T15:25:01.347839Z","title":"Rojas-Gomez, Teck-Yian Lim, Minh N","venue":null,"work_id":"f94f03c4-7c13-4f86-9dda-3d7119ae9d94","year":2024},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-08-07T15:25:00.066774Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:9fb54bbdeea506c3b564be1f45d6dd55138adb35c8a89a95c72c7c8f639a2e57","observation_id":"b24e5e57-cf9c-42cb-9557-dbc7398c01d9","resolution":{"observed_at":"2026-08-07T15:25:01.351357Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T15:25:01.337582Z","title":"Attentive group equivariant convolutional networks","venue":null,"work_id":"26d25677-9270-4bd8-877a-4b58449720bf","year":2020},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":49,"source":"arxiv_source","source_observed_at":"2026-08-07T15:25:00.069748Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:4ed24ec404780867c4156311b6246d8630e2654cd428ed98ffc32c7480132391","observation_id":"04f08762-28b9-488b-9b8d-5e52f14059e6","resolution":{"observed_at":"2026-08-07T15:25:01.341392Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T15:25:00.072822Z","title":"Imagenet large scale visual recognition challenge","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":50,"source":"arxiv_source","source_observed_at":"2026-08-07T15:25:00.072822Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:1a176ba85fe09d9819c3f443d8c83f8ae9b5d441365e6ea0a2ab5a6d70dcb9bc","observation_id":"6d3dda3a-4831-4f83-9e82-0e591b75cd77","resolution":{"observed_at":"2026-08-07T15:25:00.072822Z","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":"2026-08-07T15:25:01.314512Z","title":"A general framework for robust g-invariance in g-equivariant networks","venue":null,"work_id":"611169b1-f299-4f67-8ac8-172f328ddf64","year":2023},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":51,"source":"arxiv_source","source_observed_at":"2026-08-07T15:25:00.075731Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:6569cf8fb71e12c108060c370df5cd874b0371960c2524cce01856bb7493d8bc","observation_id":"0a6b075b-e5e0-4a83-b244-7f65b2a45c00","resolution":{"observed_at":"2026-08-07T15:25:01.322042Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T15:25:00.079099Z","title":"Linear Representations of Finite Groups , volume 42 of Graduate Texts in Mathematics","venue":null,"work_id":null,"year":1977},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":52,"source":"arxiv_source","source_observed_at":"2026-08-07T15:25:00.079099Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:bc18105950dd5bbacc5fd7aa03368d4a255c6cda05fb36f05e5347e43c9390ab","observation_id":"488246ac-a2a3-4be3-949f-d09dc5438ff1","resolution":{"observed_at":"2026-08-07T15:25:00.079099Z","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":"2026-08-07T15:25:00.082462Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":53,"source":"arxiv_source","source_observed_at":"2026-08-07T15:25:00.082462Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:ec5f8cfe6e7db0d3b93007ddd7f15d698229c8b8ca629ad44938ffa0ddd41b18","observation_id":"884df359-cb9b-4099-97a2-bb9fcdf1d99c","resolution":{"observed_at":"2026-08-07T15:25:00.082462Z","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":"2026-08-07T15:25:01.296428Z","title":"Deit iii: Revenge of the vit","venue":null,"work_id":"0fcc9e26-edba-4667-83af-7929d1bccdd1","year":2022},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":54,"source":"arxiv_source","source_observed_at":"2026-08-07T15:25:00.085422Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:16a9734b2db2010b056681143542b93c2e151d0ce9516223d57dd4fcb23cf117","observation_id":"d66495ab-dae1-4aa7-a1b8-ae902b7e3261","resolution":{"observed_at":"2026-08-07T15:25:01.304235Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2501.01999","last_updated":"2025-06-02T02:43:00Z","snapshot_observed_at":"2026-07-06T20:16:22.788626Z","submitted_at":"2025-01-01T07:00:41Z","title":"Probing Equivariance and Symmetry Breaking in Convolutional Networks","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.01999","snapshot_observed_at":"2026-08-07T15:25:00.088220Z","title":"On the utility of equivariance and symmetry breaking in deep learning architectures on point clouds","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":55,"source":"arxiv_source","source_observed_at":"2026-08-07T15:25:00.088220Z"},"links":{"cited_paper":"/paper/2501.01999","citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:1083581016c7682a4d521cff4e4aba5ef685f977ac03e950c45d1f040c330d9c","observation_id":"2080a968-4a48-4648-b484-eca3e9e4bed6","resolution":{"observed_at":"2026-08-07T15:25:00.088220Z","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":"2026-08-07T15:25:01.283486Z","title":"Benchmarking representation learning for natural world image collections","venue":null,"work_id":"602f83d8-e49f-410e-ac51-ed01fa53f0d2","year":2021},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":56,"source":"arxiv_source","source_observed_at":"2026-08-07T15:25:00.091327Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:af1fc63df99b911abd0bdb324dab1a66b14ecc7212ec6dbe1502e0f21c09e010","observation_id":"56229692-0a08-4198-b321-5ad9c8617b82","resolution":{"observed_at":"2026-08-07T15:25:01.289037Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T15:25:00.094139Z","title":"Attention is all you need","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":57,"source":"arxiv_source","source_observed_at":"2026-08-07T15:25:00.094139Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:5cad1b62f3e158141700dc610db0a1475a369dee4c8c4f26425fb249ca35e0b1","observation_id":"33a34b82-5c15-4afa-b7dd-7ac7cb4441a3","resolution":{"observed_at":"2026-08-07T15:25:00.094139Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.11651","last_updated":"2025-03-14T17:59:47Z","snapshot_observed_at":"2026-08-07T17:03:09.355801Z","submitted_at":"2025-03-14T17:59:47Z","title":"VGGT: Visual Geometry Grounded Transformer","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.11651","snapshot_observed_at":"2026-08-07T15:25:00.097364Z","title":"Vggt: Visual geometry grounded transformer, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":58,"source":"arxiv_source","source_observed_at":"2026-08-07T15:25:00.097364Z"},"links":{"cited_paper":"/paper/2503.11651","citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:2107164056e3feefa915e84a788bdd4a15720d9dc7e9f376b490900e106b2d90","observation_id":"76c1902a-cd4b-4764-aa8a-9990c3e1a3c8","resolution":{"observed_at":"2026-08-07T15:25:00.097364Z","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":"2026-08-07T15:25:01.266456Z","title":"Dust3r: Geometric 3d vision made easy","venue":null,"work_id":"fa28cd9e-0d4e-4946-8f40-b28862f25c1d","year":2024},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":59,"source":"arxiv_source","source_observed_at":"2026-08-07T15:25:00.100816Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:0170a2cc2d58c3af7422fc6c45c56e115a73e48b0142477db66bcfa7028dc7b7","observation_id":"59d2a013-a693-4b7d-a00c-5d1c021c3818","resolution":{"observed_at":"2026-08-07T15:25:01.270335Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T15:25:01.255069Z","title":"Swallowing the bitter pill: Simplified scalable conformer generation","venue":null,"work_id":"b0ad7027-5377-4ff4-ad4b-2232667a5ec6","year":2024},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":60,"source":"arxiv_source","source_observed_at":"2026-08-07T15:25:00.104240Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:b7c61caff53240ee7e5177d2ae6d8c1b9f3c434d10841807d3631538ac57813b","observation_id":"a564d382-238b-4913-8aa6-3ec51fdd062e","resolution":{"observed_at":"2026-08-07T15:25:01.258709Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T15:25:01.241367Z","title":"General E(2) -equivariant steerable CNN s","venue":null,"work_id":"2328f4c7-08dd-4707-8076-c2d691a1c3fd","year":2019},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":61,"source":"arxiv_source","source_observed_at":"2026-08-07T15:25:00.107801Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:fd0a32d62725b4ca13b6cdf16f83406799c900094974e3232ec93824526f7082","observation_id":"a5cc7fec-fa18-4668-bfe9-7aca779859c0","resolution":{"observed_at":"2026-08-07T15:25:01.247437Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T15:25:00.110748Z","title":"Pytorch image models","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":62,"source":"arxiv_source","source_observed_at":"2026-08-07T15:25:00.110748Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:cacbd98291002b2c6885e359393b00bf4ea8ffb6a6c97d3e0b48f6aafa91bb62","observation_id":"f7ac04d5-8ffc-4323-ac5e-3d64d2066577","resolution":{"observed_at":"2026-08-07T15:25:00.110748Z","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":"2026-08-07T15:25:01.210127Z","title":"Representation theory and invariant neural networks","venue":null,"work_id":"d9dec66f-9137-4c71-b845-67958f5c085e","year":1996},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":63,"source":"arxiv_source","source_observed_at":"2026-08-07T15:25:00.113990Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:aac236b6c5806e20272ab62c7e2b3914d23b5d606a026e13106b3d18f9354cac","observation_id":"a383838c-415a-463e-9136-61a4ee781e84","resolution":{"observed_at":"2026-08-07T15:25:01.220306Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T15:25:01.099039Z","title":"Cvt: Introducing convolutions to vision transformers","venue":null,"work_id":"82fbca66-4017-4944-8958-37fb46a1c82f","year":2021},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":64,"source":"arxiv_source","source_observed_at":"2026-08-07T15:25:00.116987Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:844afa9f3f272eb76a5968b5e850950b21866387ca73f6bc03fd3038c667632c","observation_id":"5fd7f0c3-796f-4eb4-83e1-a5a9faa439aa","resolution":{"observed_at":"2026-08-07T15:25:01.179230Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T15:25:01.014105Z","title":"e (2) -equivariant vision transformer","venue":null,"work_id":"cb509398-5969-4f18-a97a-82d61a69323c","year":2023},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":65,"source":"arxiv_source","source_observed_at":"2026-08-07T15:25:00.119569Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:456ad50bfb828c0ed70fae3f353489df05909f69b0bfbf147471a408652a94a4","observation_id":"016e0189-061c-4297-9758-3f0e6857c9bd","resolution":{"observed_at":"2026-08-07T15:25:01.079647Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T15:25:00.736850Z","title":"Scaling vision transformers","venue":null,"work_id":"494e09cf-0735-46b0-993f-9157aee8ce77","year":2022},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":66,"source":"arxiv_source","source_observed_at":"2026-08-07T15:25:00.122203Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:78c2cccedf1217c2b3b093413e463e5bd594c8c829007ee38d3d74a9a4824b41","observation_id":"02636207-895d-4df1-af95-d46b395bb7aa","resolution":{"observed_at":"2026-08-07T15:25:00.823101Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T15:25:00.579958Z","title":"Places: A 10 million image database for scene recognition","venue":null,"work_id":"b91fa445-b5a1-45cb-9c63-9eaa3a4a7e38","year":2017},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":67,"source":"arxiv_source","source_observed_at":"2026-08-07T15:25:00.124906Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:35d6ea326d6038ce3466c1462c81c4f4c6fd0314cd5347156958d8b1cf17d45f","observation_id":"ec9226b8-1929-431c-9505-6a685a337fd3","resolution":{"observed_at":"2026-08-07T15:25:00.632362Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T15:25:00.461183Z","title":"Scene parsing through ade20k dataset","venue":null,"work_id":"32987be3-c828-4656-bf43-f2e32d4b7c22","year":2017},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":68,"source":"arxiv_source","source_observed_at":"2026-08-07T15:25:00.128279Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:b395ab5a733094ea86792594994d0387890f08141a4e6c098ef4ced46b97dbc1","observation_id":"e4308765-75f1-45f9-a154-43f8de0a3eb6","resolution":{"observed_at":"2026-08-07T15:25:00.519956Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T15:25:00.131075Z","title":"Semantic understanding of scenes through the ade20k dataset","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance","version":5},"reference_index":69,"source":"arxiv_source","source_observed_at":"2026-08-07T15:25:00.131075Z"},"links":{"citing_paper":"/paper/2505.15441"},"observation_digest":"sha256:26ddaaca8008fb7024b7763b6f1bcf19f1b1ef61b0e56782373c8e9612cf8280","observation_id":"0b044900-2ae1-4dcf-866f-b74598099022","resolution":{"observed_at":"2026-08-07T15:25:00.131075Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2505.15441","last_updated":"2026-07-06T10:16:05Z","latest_version":5,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-07T15:15:28.038723Z","submitted_at":"2025-05-21T12:22:53Z","title":"Quick ViTs: Speeding up Vision Transformers through Equivariance"},"reference_resolution":{"displayed":69,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":30,"verified_exact":0,"verified_fuzzy":39},"total_outbound_references":69},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 69 of 69 outbound references and 4 inbound Pith citation observations for arXiv:2505.15441."}