{"as_of":"2026-08-19T05:45:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:c4c07d57084e578779eb1058dc6bfe70aee60ea1a54cbd3d129898b403fa3d4b","coverage":[{"denominator":53,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":53,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T10:09:23.870023Z","state":"measured"},{"denominator":53,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":53,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-18T06:34:40.430872+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2508.00473/citation-record","integrity":"/paper/2508.00473/integrity","json":"/paper/2508.00473/citation-record.json","paper":"/paper/2508.00473"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:09:23.671301Z","title":", \" * write output.state after.block = add.period write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.671301Z"},"links":{"citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:dff88b9fbac605cab44f82badb9732de642df3aecf880d9646ee770a80d1f2a5","observation_id":"5798ba99-e4ff-4f1a-8e13-b1138edda9b9","resolution":{"observed_at":"2026-08-06T10:09:23.671301Z","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":"2026-08-06T10:09:23.675649Z","title":"write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.675649Z"},"links":{"citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:56ee1bf37b7a4898962ac859a89e5d3a735d8cf6b7fad89bdfbbbf72c36e687b","observation_id":"92d9bf16-dc86-4ebe-8dc3-33ccec28dc35","resolution":{"observed_at":"2026-08-06T10:09:23.675649Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2112.09045","last_updated":"2021-12-16T17:35:51Z","snapshot_observed_at":"2026-08-18T07:20:43.441039Z","submitted_at":"2021-12-16T17:35:51Z","title":"The MVTec 3D-AD Dataset for Unsupervised 3D Anomaly Detection and Localization","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2112.09045","snapshot_observed_at":"2026-08-06T10:09:23.680864Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.680864Z"},"links":{"cited_paper":"/paper/2112.09045","citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:d9735150ec31dca22857ed71d8ca82413c74ead5fc0be3148c5063196875d79a","observation_id":"24e1664c-bef0-4474-8adb-652628315d08","resolution":{"observed_at":"2026-08-06T10:09:23.680864Z","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":"2026-08-06T10:09:24.552479Z","title":null,"venue":null,"work_id":"7e3555a0-dae0-436f-9c06-027deb97eb39","year":2014},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.686184Z"},"links":{"citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:3b8b0877f84842a84144555f476b6a36e5b69492fad33f3337c1c7c06d46af32","observation_id":"637cd792-76d5-4ed8-a178-751985ad43cf","resolution":{"observed_at":"2026-08-06T10:09:24.555979Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T10:09:24.540455Z","title":null,"venue":null,"work_id":"d2bf9ab3-59aa-4d2d-9ff8-4ed4bdf38ead","year":2019},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.690084Z"},"links":{"citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:c455d58f6a82e49b12b29ec3d939fe7d1de6a60499902d1ccbe28391cb116072","observation_id":"c395ebe6-a795-44cf-8d06-8db0c169b6a2","resolution":{"observed_at":"2026-08-06T10:09:24.544315Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2105.14686","last_updated":"2022-03-16T02:23:49Z","snapshot_observed_at":"2026-08-16T18:21:01.698472Z","submitted_at":"2021-05-31T03:36:49Z","title":"Fully Hyperbolic Neural Networks","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2105.14686","snapshot_observed_at":"2026-08-06T10:09:23.694101Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.694101Z"},"links":{"cited_paper":"/paper/2105.14686","citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:be73a25ab3504c2d87bc780e18ef8fe6b07a140a8129728a26d6c7119d78bf4f","observation_id":"fca97003-4c2a-4b5d-a1de-9b50667a7db5","resolution":{"observed_at":"2026-08-06T10:09:23.694101Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.04082","last_updated":"2023-09-08T02:44:37Z","snapshot_observed_at":"2026-08-19T04:26:35.949756Z","submitted_at":"2023-09-08T02:44:37Z","title":"Curve Your Attention: Mixed-Curvature Transformers for Graph Representation Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.04082","snapshot_observed_at":"2026-08-06T10:09:23.698731Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.698731Z"},"links":{"cited_paper":"/paper/2309.04082","citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:638be5dea876d1850cee210130070684056a0a03af5cf8ae15c1c0c373c28350","observation_id":"9977efe5-e23a-49a1-a64f-aa3ea99d5ae6","resolution":{"observed_at":"2026-08-06T10:09:23.698731Z","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":"2026-08-06T10:09:24.528293Z","title":null,"venue":null,"work_id":"bd393b82-ad74-443e-8c5b-637e0adeebad","year":2021},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.702837Z"},"links":{"citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:48c242e6b9627e6c51157181d4dabe24a9eb50c7806c4f13923c68c637279020","observation_id":"948ae767-44d2-491e-a5ab-cd68185b5383","resolution":{"observed_at":"2026-08-06T10:09:24.531968Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2010.11929","last_updated":"2021-06-03T13:08:56Z","snapshot_observed_at":"2026-08-16T09:25:53.087782Z","submitted_at":"2020-10-22T17:55:59Z","title":"An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.11929","snapshot_observed_at":"2026-08-06T10:09:23.707255Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.707255Z"},"links":{"cited_paper":"/paper/2010.11929","citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:2d09b4dbfc798c33c0c33ae016276bbc67a076a576e5d9f96ec81bff5d5e8d78","observation_id":"c42612b2-82ea-425f-9e28-58e8609e7f06","resolution":{"observed_at":"2026-08-06T10:09:23.707255Z","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":"2026-08-06T10:09:24.515550Z","title":null,"venue":null,"work_id":"d135112f-47a7-42fd-9e4a-458feb48f828","year":2024},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.711075Z"},"links":{"citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:bae8bc31a79cfbc41a096cbbed9c593fec4f0f850f3a09c0bcf89bc7b7ab0a0e","observation_id":"e67ddb13-941e-497c-a1f2-acf9cb401ada","resolution":{"observed_at":"2026-08-06T10:09:24.519472Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T10:09:24.503454Z","title":null,"venue":null,"work_id":"5560b01b-30cd-4385-8267-cc53c4943bbc","year":2022},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.714780Z"},"links":{"citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:a2da7fccc8c70206125fd2ef8fce78980726d9790dc7b11a5078c0d8365de20c","observation_id":"9f2d7995-142a-41f8-a771-bfb8834d8f4d","resolution":{"observed_at":"2026-08-06T10:09:24.507211Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T10:09:24.491103Z","title":null,"venue":null,"work_id":"ef6a320c-25ca-4782-a6cc-6be832b4f89e","year":2018},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.718651Z"},"links":{"citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:5f41ec65c2d2ef219e6eb1138699af79e824befc4e29b0563f034b38d627cb40","observation_id":"0c5fb4bb-c7cd-4143-84e3-794f1aec3e97","resolution":{"observed_at":"2026-08-06T10:09:24.494644Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1805.09786","last_updated":"2018-05-24T17:11:35Z","snapshot_observed_at":"2026-08-14T19:11:28.802097Z","submitted_at":"2018-05-24T17:11:35Z","title":"Hyperbolic Attention Networks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1805.09786","snapshot_observed_at":"2026-08-06T10:09:23.722218Z","title":"M.; Battaglia, P.; Bapst, V.; Raposo, D.; Santoro, A.; et al","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.722218Z"},"links":{"cited_paper":"/paper/1805.09786","citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:170df6d3c948ade02ce2e5866cf20d3bda76c1aeb83738fb2c5ed5d5ed7ced7e","observation_id":"a17ce45a-9846-4f73-bfc5-b97d5a3b3574","resolution":{"observed_at":"2026-08-06T10:09:23.722218Z","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":"2026-08-06T10:09:24.479418Z","title":null,"venue":null,"work_id":"45801017-69eb-4b9d-9a7d-f65325bc78d7","year":2024},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.726280Z"},"links":{"citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:3a2889c1ac8a9c65cb35a871826402607852f447c6136ed73901ca0e8c7f11a4","observation_id":"bb82ac4e-b191-47e4-bcb4-1d73c5e56268","resolution":{"observed_at":"2026-08-06T10:09:24.482840Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T10:09:24.467678Z","title":null,"venue":null,"work_id":"0d9caa60-5777-4868-83bd-65e986ab2ec2","year":2023},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.730053Z"},"links":{"citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:d83b4bd5d8bd95670e78822f6b61eb52c3f860fdf11c1cc9227d2309c729302f","observation_id":"e0074a08-db50-4a00-8c70-08ed08f25ec5","resolution":{"observed_at":"2026-08-06T10:09:24.471054Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T10:09:24.455628Z","title":"M.; Bennewitz, M.; Stachniss, C.; and Burgard, W","venue":null,"work_id":"a968f900-8214-44c1-93df-9f07bfbd2ce9","year":2013},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.734030Z"},"links":{"citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:f918dd0acb6d6c630be4e7b67e27de2a18fa8fc734864a91a54519ece966b710","observation_id":"0bff402c-1978-44e6-b6c3-72d9ea68a009","resolution":{"observed_at":"2026-08-06T10:09:24.459422Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T10:09:24.444104Z","title":null,"venue":null,"work_id":"68626865-4d35-4a0e-a412-e24195e3bce9","year":2024},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.738116Z"},"links":{"citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:ea1c81a71fe3dad274919f0422eeaf63676fb7f656faba422560d699847a71c5","observation_id":"205847c2-a4b0-4f59-b895-f828797962ae","resolution":{"observed_at":"2026-08-06T10:09:24.447660Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T10:09:24.431596Z","title":null,"venue":null,"work_id":"2815ac44-86fc-4ffc-a2ad-f781408de15f","year":2020},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.742063Z"},"links":{"citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:d8db128eb6ec6806d656df4bf39551eef2e76ca89e9a6639621593874b8c35ad","observation_id":"7b741e69-d42b-4843-80b3-35e3009d60f3","resolution":{"observed_at":"2026-08-06T10:09:24.435314Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T10:09:24.419038Z","title":null,"venue":null,"work_id":"9eaecf01-dacf-4df7-8fbe-4b48210c6dd2","year":2021},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.745615Z"},"links":{"citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:0a28efffe57deb63ec4198b7c4985679e3437beffb4778c2ef5ff2532abae35e","observation_id":"d7dacc4e-1ead-40fc-8f54-ba532dbdd968","resolution":{"observed_at":"2026-08-06T10:09:24.422845Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T10:09:24.406619Z","title":null,"venue":null,"work_id":"0f8f1fee-8531-45d8-9101-d41c4b6f808c","year":2019},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.749335Z"},"links":{"citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:5cf13533a07498663ea99b1722818751a6622bf0d45fb89d972761b34271f433","observation_id":"dcb561d3-5314-4221-85ba-21504ba8bf49","resolution":{"observed_at":"2026-08-06T10:09:24.410474Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2409.19252","last_updated":"2024-09-28T05:54:20Z","snapshot_observed_at":"2026-08-18T20:19:51.307217Z","submitted_at":"2024-09-28T05:54:20Z","title":"Beyond Euclidean: Dual-Space Representation Learning for Weakly Supervised Video Violence Detection","version":1},"cited_work":{"arxiv_id":"2409.19252","doi":null,"metadata_source":"pith","pith_arxiv_id":"2409.19252","snapshot_observed_at":"2026-08-06T10:09:23.940071Z","title":"Beyond Euclidean: Dual-Space Representation Learning for Weakly Supervised Video Violence Detection","venue":"cs.CV","work_id":"8a7d7fde-4997-4643-83ed-ab9f812f4501","year":2024},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.753298Z"},"links":{"cited_paper":"/paper/2409.19252","citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:e65a7a4162fb20d7ee33016cbf508cc8174b579838a5cbb46365d001d88bda0c","observation_id":"ed1409cb-7060-4145-b043-4aecceff9b9e","resolution":{"observed_at":"2026-08-06T10:09:23.944574Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T10:09:24.392825Z","title":null,"venue":null,"work_id":"8040fa34-d190-43fa-838c-19f272999ca0","year":2025},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.757252Z"},"links":{"citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:d54156e6b8857df3585f23857ae16eadb5b67d2edd63393adb0be23ae24e0afa","observation_id":"c4e24148-f052-4a65-97bb-6508765124d1","resolution":{"observed_at":"2026-08-06T10:09:24.397004Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T10:09:24.380252Z","title":null,"venue":null,"work_id":"3937ae01-f980-46ef-b0a1-1df7ce28adb4","year":2019},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.760792Z"},"links":{"citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:81388f10bce607e86566b18949f17e4803197767cb11819c95c9467077b82ba0","observation_id":"c219378d-da57-4625-a2c1-9824b1bfc8f3","resolution":{"observed_at":"2026-08-06T10:09:24.384010Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T10:09:24.366589Z","title":null,"venue":null,"work_id":"57af591c-bedd-4c41-9736-03afdc110e94","year":2024},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.764628Z"},"links":{"citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:34fcc4c4779019cba94b31952f7176c59ece6bf00a4d53967bb8b345fd89ce6f","observation_id":"85e8df24-5606-4005-83ce-ed0b0e6b6227","resolution":{"observed_at":"2026-08-06T10:09:24.370953Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T10:09:24.352683Z","title":"T.; and Snoek, C","venue":null,"work_id":"3e3f1cd9-0515-435f-81b8-e10c4db1921d","year":2020},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.768188Z"},"links":{"citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:4fa99811835522c457ee8041a2ef0f95d0e23434348cfbf6cd8540e2394fd9d5","observation_id":"af2d8b28-3afb-4472-a19f-d9892656cbee","resolution":{"observed_at":"2026-08-06T10:09:24.356600Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T10:09:24.339722Z","title":null,"venue":null,"work_id":"d4e9df72-4bde-4e12-8010-dce51e2cbc27","year":2022},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.771839Z"},"links":{"citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:dafa45447f83c52a3d79ef7679d9be78f61716a7c03f6872c3f0245fd2dbabf2","observation_id":"88bd0bd3-156c-4fca-a6cb-0b6ee60285fa","resolution":{"observed_at":"2026-08-06T10:09:24.343512Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T10:09:24.326941Z","title":null,"venue":null,"work_id":"3c46ca00-49fd-49f8-a155-59bbedebd20c","year":2024},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.775352Z"},"links":{"citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:6d9b6fba5013cc7240df5ae00921e7944a9ab8ea7334f563c7e8f4ac038dd30e","observation_id":"a923d9f7-fc51-4a80-96be-5c713f9eb65f","resolution":{"observed_at":"2026-08-06T10:09:24.330881Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T10:09:24.312143Z","title":null,"venue":null,"work_id":"45e416c2-09d3-4421-9add-0e021dee38ca","year":2022},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.778948Z"},"links":{"citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:9d3847e9a7cb0608973e9331e72910649efc2476910fb95394bd651eb2f07e6b","observation_id":"5c46dd0f-7514-4eb1-a627-89c58186b7d5","resolution":{"observed_at":"2026-08-06T10:09:24.316860Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T10:09:24.297377Z","title":null,"venue":null,"work_id":"407f19dc-8522-412c-a463-87e4bba3f49c","year":2013},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.783322Z"},"links":{"citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:7099038a06271107100f0d9033a33ce6e3e79810d57cb90b190b8fb8cec26f83","observation_id":"2098fbef-07c6-4f61-b4d9-75c47ee3f46e","resolution":{"observed_at":"2026-08-06T10:09:24.301595Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T10:09:24.284845Z","title":null,"venue":null,"work_id":"e6476b86-6abf-4ebd-a96a-64aaccfd87eb","year":2019},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.786890Z"},"links":{"citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:5d428cae50bdf7d9e61860533e2c276acb58f3719d71b5417909b5385292f6b2","observation_id":"f8380453-8727-4e4f-92bb-c3791e68c490","resolution":{"observed_at":"2026-08-06T10:09:24.288506Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T10:09:24.272651Z","title":null,"venue":null,"work_id":"bbce5b9f-327d-4843-a3f2-083d8121b537","year":2020},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.790445Z"},"links":{"citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:c99f4ad89b2a4799cf5aeb833737c193e1eb327327cdca78be160e983f309162","observation_id":"a529747f-6c50-4cc2-8bdd-8c7c07338ccd","resolution":{"observed_at":"2026-08-06T10:09:24.276255Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.18797","last_updated":"2024-02-13T16:00:01Z","snapshot_observed_at":"2026-08-16T15:28:26.936967Z","submitted_at":"2023-05-30T07:18:56Z","title":"Learning Weakly Supervised Audio-Visual Violence Detection in Hyperbolic Space","version":3},"cited_work":{"arxiv_id":"2305.18797","doi":null,"metadata_source":"pith","pith_arxiv_id":"2305.18797","snapshot_observed_at":"2026-08-06T10:09:23.919185Z","title":"Learning Weakly Supervised Audio-Visual Violence Detection in Hyperbolic Space","venue":"cs.CV","work_id":"c726386b-8e0c-4da8-9114-1b5b6712abef","year":2023},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.793993Z"},"links":{"cited_paper":"/paper/2305.18797","citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:9e01c92d87524bfc303cab2ae7ede2381f0e12267bc4b263fc2dd37600baebc7","observation_id":"8f74e1fc-1a46-473d-b36a-a966fb0b9c83","resolution":{"observed_at":"2026-08-06T10:09:23.925242Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T10:09:24.259456Z","title":"R.; Su, H.; Mo, K.; and Guibas, L","venue":null,"work_id":"ff13fc0d-f2a5-40fb-9e43-01997d18652d","year":2017},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.797718Z"},"links":{"citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:7435c8b54d208379ab16df1256497caaa9a3884e7521bd2401cd50f2540bba96","observation_id":"6325822d-c1eb-40e2-9bf5-ceea57138bfe","resolution":{"observed_at":"2026-08-06T10:09:24.263331Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T10:09:24.247004Z","title":"R.; Yi, L.; Su, H.; and Guibas, L","venue":null,"work_id":"880f67fa-517b-4fe8-a1d7-39139c061289","year":2017},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.801117Z"},"links":{"citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:a361a64fb26e0da20bd79a858b4bf056678ddb03b220274055c43fdc917daa7e","observation_id":"fb78fca5-bb9c-4cc0-b6f8-d43701fa6e38","resolution":{"observed_at":"2026-08-06T10:09:24.251076Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T10:09:23.804591Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.804591Z"},"links":{"citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:773ab694a3877f6eba67ba96ed6f19e6a6a81a07922e4bfa392bc85dd3935486","observation_id":"c05f5b58-8116-41c6-a261-2b4e3957b9b3","resolution":{"observed_at":"2026-08-06T10:09:23.804591Z","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":"2026-08-06T10:09:24.225671Z","title":null,"venue":null,"work_id":"909a5a19-70c5-4811-8ab7-6ef2cc111b21","year":2022},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.808311Z"},"links":{"citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:e8663a131c0dabb41bca6f4fd1c3f7dce7b6e962d7a0e0ce32753298e89a2bda","observation_id":"92bc9f2d-7043-49c7-8e65-84c8f720e65f","resolution":{"observed_at":"2026-08-06T10:09:24.229549Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T10:09:24.212433Z","title":null,"venue":null,"work_id":"a0edd58a-1dbd-4048-95d5-c70e5b07ba86","year":2022},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.812109Z"},"links":{"citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:812d85af6e5f33418ed8625d58e3f5500d884ca647eccd3bd7ae731a3903bf00","observation_id":"19dcd09f-0712-41ca-a48f-c7c98fd542c9","resolution":{"observed_at":"2026-08-06T10:09:24.216647Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T10:09:24.198175Z","title":null,"venue":null,"work_id":"eb25293b-a343-4c47-96e2-64ee486c3d90","year":2015},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.815650Z"},"links":{"citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:93dbed03cf6d5b880af4210cd58461ad6b2fd584232e93f98c018d0632b29426","observation_id":"bc3e5bf4-8b75-4ef4-91f1-f98f8785231d","resolution":{"observed_at":"2026-08-06T10:09:24.202244Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2006.08210","last_updated":"2021-03-17T14:36:34Z","snapshot_observed_at":"2026-08-10T04:16:11.756351Z","submitted_at":"2020-06-15T08:23:20Z","title":"Hyperbolic Neural Networks++","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2006.08210","snapshot_observed_at":"2026-08-06T10:09:23.819168Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.819168Z"},"links":{"cited_paper":"/paper/2006.08210","citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:159cc97e812891d645c5a1f9cfef0a38afcf5c4e4b24e812015ff8fc10f4978e","observation_id":"b4615892-375b-44c2-b794-6429bd0069b8","resolution":{"observed_at":"2026-08-06T10:09:23.819168Z","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":"2026-08-06T10:09:24.185887Z","title":null,"venue":null,"work_id":"4ad83f30-f4b1-4aec-8034-053d3eb23859","year":2024},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.822837Z"},"links":{"citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:8895d9fbe70f943fd55a8692450788a79064b32ae2f6fdda0a9f0c7b4b123235","observation_id":"75851bc6-410d-4740-bc3d-a83fb5b4a32c","resolution":{"observed_at":"2026-08-06T10:09:24.189647Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T10:09:24.173050Z","title":null,"venue":null,"work_id":"964058a1-3110-4a8d-97a4-daaa6506b557","year":2021},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.826423Z"},"links":{"citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:37cb19a17838a44cd1ce6c5b71f35f8b3d66b9211705efa02fb275d53d9f7df7","observation_id":"3b01a62d-3000-4c6e-9a31-48052a84c1ca","resolution":{"observed_at":"2026-08-06T10:09:24.176824Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T10:09:24.160260Z","title":null,"venue":null,"work_id":"7090d51f-e550-41a5-b156-3ae5b628e27a","year":2022},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.829870Z"},"links":{"citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:07815b1ec6c8ab37628dbb2ef99982a628dd0c4d104662903a92f1b16dbbcd42","observation_id":"461969b8-6672-4d94-bef7-c8ff203d35aa","resolution":{"observed_at":"2026-08-06T10:09:24.164131Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T10:09:24.148056Z","title":"A.; Pham, Q.-H.; Hua, B.-S.; Nguyen, T.; and Yeung, S.-K","venue":null,"work_id":"2c11cc62-d99d-4a4a-b70a-4dcd21854ca4","year":2019},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.833367Z"},"links":{"citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:b695b52583aa8201d7f012b3814f438129ef141dc4acf2f9b8472845e47d3f3c","observation_id":"a48c47cf-d27f-4785-960e-4d8b693d61d3","resolution":{"observed_at":"2026-08-06T10:09:24.151675Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T10:09:23.837076Z","title":"N.; Kaiser, .; and Polosukhin, I","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.837076Z"},"links":{"citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:729eaf037c9615da41db6a9be41c3b934ccea7d3e19033f4874cd7b5d81157ac","observation_id":"3b10fecc-f6c7-4c3d-8583-cfc6dabf234f","resolution":{"observed_at":"2026-08-06T10:09:23.837076Z","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":"2026-08-06T10:09:24.126154Z","title":"E.; Bronstein, M","venue":null,"work_id":"40bd3698-3d43-443e-a9a5-76f4fe26184e","year":2019},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.840580Z"},"links":{"citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:faefedf5525ec348c8d4a8fa419f99258508955d017ecbd2d52b5bc06955e849","observation_id":"24c27b2b-d939-456b-8208-c76cf4da8ff6","resolution":{"observed_at":"2026-08-06T10:09:24.129979Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T10:09:24.112825Z","title":null,"venue":null,"work_id":"4aa74852-5885-4866-9373-5456578e6eb2","year":2023},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.844232Z"},"links":{"citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:b183c4d306aa42b502b2d4421d19894f6146bd402c78e8bff9e8952e1ab39c09","observation_id":"50589ed2-e908-4692-a555-93fb87db8259","resolution":{"observed_at":"2026-08-06T10:09:24.116605Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T10:09:24.099455Z","title":null,"venue":null,"work_id":"553c4c4c-c8ca-4f3b-9c88-660726339ecd","year":2020},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.848234Z"},"links":{"citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:0d97af87e738283b157b94997ef581508058ff9baf860136ed465424a071b2fb","observation_id":"c9b1f2d7-a62e-4a8a-827a-149f6e6f132d","resolution":{"observed_at":"2026-08-06T10:09:24.103291Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T10:09:24.086328Z","title":"C.; Liu, J.; King, I.; and Ying, R","venue":null,"work_id":"c62d7b54-ff09-4ada-b54f-7f06924a4eb5","year":2024},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.851632Z"},"links":{"citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:fc63b698a377493a94744f21ca0d95d47fd65ad91559123c2199a3c3002d66e3","observation_id":"e5dc8d77-3af4-4157-b7e8-b2e343f9f976","resolution":{"observed_at":"2026-08-06T10:09:24.090351Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T10:09:24.073600Z","title":null,"venue":null,"work_id":"95830a75-157b-4115-b37c-f5ecf27940fb","year":2024},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":49,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.855281Z"},"links":{"citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:fa1f701392bb073489037278fad43a770fc896befe94a909c2d4eccf5cca0f4a","observation_id":"fe405e00-043a-4d85-9fbe-b08241dcb1df","resolution":{"observed_at":"2026-08-06T10:09:24.077190Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T10:09:24.061060Z","title":null,"venue":null,"work_id":"ae5ef4a7-ba20-4c87-aa7c-d453fb0a810d","year":2021},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":50,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.858709Z"},"links":{"citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:c89ec87605d11a0c8ec25b98ba33d1ccb1dbacbac605113eb98442b7bdb14bb6","observation_id":"a119a625-3cac-4d06-812f-ece9a46fd95f","resolution":{"observed_at":"2026-08-06T10:09:24.064748Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T10:09:24.048226Z","title":null,"venue":null,"work_id":"698a1640-a6c0-43d7-8ab8-17e4d3cb94d1","year":2025},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":51,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.862311Z"},"links":{"citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:ef7f50047d4eaad659980641dcbca5c5ef69009739ff80afe51ba353265836e2","observation_id":"c5519ad2-f165-4cd7-a507-cd0a369580fc","resolution":{"observed_at":"2026-08-06T10:09:24.052118Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T10:09:24.034500Z","title":null,"venue":null,"work_id":"e821fcf0-2fbf-4761-8339-7c3808c8ea1f","year":2024},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":52,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.865994Z"},"links":{"citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:fbe69a5418c576fe9a2716f7773ca903eb66523800d79e5d7d176c131eedb82c","observation_id":"b055531a-2d65-4997-97b2-24897c01c3ee","resolution":{"observed_at":"2026-08-06T10:09:24.038970Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T10:09:24.021587Z","title":null,"venue":null,"work_id":"65a3dd81-a3b6-4c4c-ac14-4b7c1f310e9b","year":2018},"citing_paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection","version":1},"reference_index":53,"source":"arxiv_source","source_observed_at":"2026-08-06T10:09:23.870023Z"},"links":{"citing_paper":"/paper/2508.00473"},"observation_digest":"sha256:f261e4fce7f8ee3914da33deb7a45e1a9d9afe3796c2e7dc857798521b1da7d8","observation_id":"203df4b9-13bc-40dc-9ebf-91c0f65a6f5b","resolution":{"observed_at":"2026-08-06T10:09:24.025435Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2508.00473","last_updated":"2025-08-01T09:50:20Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-14T01:44:55.733694Z","submitted_at":"2025-08-01T09:50:20Z","title":"HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection"},"reference_resolution":{"displayed":53,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":44,"verified_exact":2,"verified_fuzzy":7},"total_outbound_references":53},"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":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"thesis":"As of 19 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 0 inbound Pith citation observations for arXiv:2508.00473."}