{"as_of":"2026-08-04T20:48:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:8f5ce79167167a7c0bc13dc7f74ac23bb2b013709ce568649f2543a12c26aea3","coverage":[{"denominator":65,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":65,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-16T07:37:38.263234Z","state":"measured"},{"denominator":65,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":65,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-04T06:34:03.388597+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/2602.04583/citation-record","integrity":"/paper/2602.04583/integrity","json":"/paper/2602.04583/citation-record.json","paper":"/paper/2602.04583"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Ev-segnet: Semantic segmentation for event-based cameras","venue":null,"work_id":"bcc57318-4f16-4915-a628-06794eb12725","year":2019},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:183282f7a618a4f07115a3da6a31ca37fc998b8340ecf6fdda82b46ada217e26","observation_id":"b44a5813-483c-4781-b46f-0bf714b98afe","resolution":{"observed_at":"2026-05-16T07:40:45.076597Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Self-supervised learning from images with a joint-embedding predictive architecture","venue":null,"work_id":"d7cbca48-6fc6-4981-9648-d771a80414c0","year":2023},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:b10e6b77a334d3da5051e14aae3e4b0a2a546362ad34f3c3cf6d1cdfcf2004c6","observation_id":"87a6fecc-49ff-41f1-95b9-cae9208e30cc","resolution":{"observed_at":"2026-05-16T07:40:45.082867Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.09985","last_updated":"2025-06-11T17:57:09Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-11T17:57:09Z","title":"V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning","version":1},"cited_work":{"arxiv_id":"2506.09985","doi":"10.48550/arxiv.2506.09985","metadata_source":"pith","pith_arxiv_id":"2506.09985","snapshot_observed_at":"2026-07-11T02:27:49.493432Z","title":"V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning","venue":"cs.AI","work_id":"a9c28401-f16a-4933-89f0-788e2f94e52b","year":2025},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"cited_paper":"/paper/2506.09985","citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:9af76e015f07693f10d76d1da88ba4d96161402a305a77ba96d5dfc0a85bce83","observation_id":"10d87c3c-b641-4255-8841-35c48e2c3b4b","resolution":{"observed_at":"2026-05-16T07:40:44.111305Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-03T19:08:37.559938+00:00","source":"crossref_status_cache"},{"observed_at":"2026-08-03T19:08:37.559938+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2511.08544","last_updated":"2025-11-14T08:38:32Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-11-11T18:21:55Z","title":"LeJEPA: Provable and Scalable Self-Supervised Learning Without the Heuristics","version":3},"cited_work":{"arxiv_id":"2511.08544","doi":"10.48550/arxiv.2511.08544","metadata_source":"pith","pith_arxiv_id":"2511.08544","snapshot_observed_at":"2026-07-11T01:07:41.775248Z","title":"LeJEPA: Provable and Scalable Self-Supervised Learning Without the Heuristics","venue":"cs.LG","work_id":"b2114616-92b2-4b9a-80db-89bda6422f4e","year":2025},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"cited_paper":"/paper/2511.08544","citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:d4eef8cf6f74de654aee2e2cb451366e5f194af0b35c3a6c5276d3d43d65448f","observation_id":"dae3207e-b68a-42bf-a0fd-bc1cc06fdad1","resolution":{"observed_at":"2026-05-16T07:40:44.103816Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-03T19:08:37.72859+00:00","source":"crossref_status_cache"},{"observed_at":"2026-08-03T19:08:37.72859+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Fea- ture hallucination via privileged information for neuromor- phic face analysis","venue":null,"work_id":"cdcd87bf-9139-4928-87e7-b15e70d849e1","year":2024},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:32b75a675a126f52e3cbdced28781af2ebcdb3e94bc4b61478c253ebc57b998c","observation_id":"fd6b7914-de7b-401a-8a8f-4d368fcf0177","resolution":{"observed_at":"2026-05-16T07:40:45.071094Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"End-to- end object detection with transformers","venue":null,"work_id":"43533439-b275-4cba-ae02-473a7143d293","year":2020},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:5aa3826a008a2f8cc62751549a6ee91736c044db009ca59e351296d7eef8d052","observation_id":"685eefa7-98bd-4ebd-bc06-22eeb32fe80f","resolution":{"observed_at":"2026-05-16T07:40:45.075136Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Emerg- ing properties in self-supervised vision transformers","venue":null,"work_id":"8a5a47d5-320f-431e-953a-e774104b82a0","year":2021},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:8b6c1b98ed75a6cdee9966a1d111e6f630b6318fa1abfb1aeec8012bec347e4a","observation_id":"8b818e79-d07c-4959-8184-3ef970d0fcb9","resolution":{"observed_at":"2026-05-16T07:40:45.078733Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"1087d225-39eb-4058-b33a-31ca99095456","year":2017},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:ade8c494aa25764be91781c877644103d51e1ac19fd20d23bdaa3bb021002034","observation_id":"f08fc99a-2fe5-4bce-a1f2-cd6a7ba53815","resolution":{"observed_at":"2026-05-16T07:40:45.087753Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Encoder-decoder with atrous separable convolution for semantic image segmentation","venue":null,"work_id":"7bb17455-0124-46f8-9cf8-55f9d4017790","year":2018},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:203d0cd5214234ff0001e224b89e8bb4c5388a8cc0e19d42262130b79289acbd","observation_id":"f36d5644-5c9b-4350-aaf1-dae1df5785d2","resolution":{"observed_at":"2026-05-16T07:40:45.079055Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"A simple framework for contrastive learning of visual representations","venue":null,"work_id":"35ae99bb-bc56-46b8-8728-e43f3b7f236b","year":2020},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:d02792f56d2302c63d62a38a5a613456a472d642c4f3006dc49562ab540f9e2d","observation_id":"be6fa97a-5567-4a96-9113-630a2c38ca7d","resolution":{"observed_at":"2026-05-16T07:40:45.095266Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Masked-attention mask transformer for universal image segmentation","venue":null,"work_id":"820f5090-f0ad-4637-b23a-a00c7d3a619e","year":2022},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:a1899d29ee9aa0180d7d877853343840935079d1f5a9ad658b78da703176cf8c","observation_id":"68ae1861-18a5-4d3b-a0b6-a7c4eb8b3366","resolution":{"observed_at":"2026-05-16T07:40:45.064869Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2004.05007","last_updated":"2020-07-06T09:10:51Z","snapshot_observed_at":"2026-08-04T20:40:11.606127Z","submitted_at":"2020-04-10T12:23:29Z","title":"An Empirical Study of Invariant Risk Minimization","version":2},"cited_work":{"arxiv_id":"2004.05007","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2004.05007","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"J., Ham, J., and Park, K","venue":null,"work_id":"37eeec1e-e645-4928-aa67-eeb167534890","year":2004},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"cited_paper":"/paper/2004.05007","citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:8ca2f04ed5d58d60b7d40bbdabf9f8d74a3711892a1101a228f3ebe7cd2ea107","observation_id":"dc6aa781-0c1c-432e-87f7-a5c453a5bfbe","resolution":{"observed_at":"2026-05-16T07:40:44.098576Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"MMSegmentation: Openmmlab semantic segmentation toolbox and benchmark.https : / / github","venue":null,"work_id":"e966365d-84f0-45ff-97c1-0ae1158bbe0b","year":2020},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:de5098f1f7d578da5483ca367171e9365de54c936f6891b4741a593927433362","observation_id":"512180b3-5f6d-48ab-a611-672cf25c2dfc","resolution":{"observed_at":"2026-05-16T07:40:45.092390Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"The cityscapes dataset for semantic urban scene understanding","venue":null,"work_id":"2ea88dae-e936-41a8-b03c-8225f670f663","year":2016},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:bd68c19f74af08cb13c92b24aee377b1aee8da671c849afd46034c4d0e2fcb38","observation_id":"0719da1c-a490-47df-8b98-ccaa28ff5f30","resolution":{"observed_at":"2026-05-16T07:40:45.116702Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2306.02572","last_updated":"2023-06-05T03:55:26Z","snapshot_observed_at":"2026-07-06T15:37:54.747810Z","submitted_at":"2023-06-05T03:55:26Z","title":"Introduction to Latent Variable Energy-Based Models: A Path Towards Autonomous Machine Intelligence","version":1},"cited_work":{"arxiv_id":"2306.02572","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2306.02572","snapshot_observed_at":"2026-07-03T21:18:59.540675Z","title":"Introduction to latent variable energy-based models: A path towards autonomous machine intelligence.CoRR, abs/2306.02572","venue":null,"work_id":"883cc770-dcf6-4bad-83f3-fc101f5d55fe","year":2023},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"cited_paper":"/paper/2306.02572","citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:692064b2b81993c606d07460973a4d62169a1c626f768223bc4f26fd9374be5f","observation_id":"9610dd77-db03-4d8f-8019-412afc10c89b","resolution":{"observed_at":"2026-05-16T07:40:44.107919Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"You only look at one sequence: Rethinking transformer in vision through object detection.Advances in Neural Information Processing Systems, 34:26183–26197","venue":null,"work_id":"4c4d0ec9-bcab-4a9d-a718-bdefb6608676","year":2021},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:7d4b79d6bfa53cd313fedf80b005b4541152e7ca210058f0e47cdc3da9847d63","observation_id":"f9581d2d-04c4-4821-9178-d78f09cfd687","resolution":{"observed_at":"2026-05-16T07:40:45.087334Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Source-free unsupervised domain adaptation: A survey.Neural Networks, 174:106230","venue":null,"work_id":"7c52cb44-8e1c-42ae-8227-42cdfc8afccf","year":2024},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:b149a14bdb95e584d54c4a38d6f14e96ae413bfe41d12d4c13b56fc82ed7f422","observation_id":"aa770c1e-f8f3-4375-9742-3b9fd7b25ca8","resolution":{"observed_at":"2026-05-16T07:40:45.011258Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Unsupervised domain adaptation by backpropagation","venue":null,"work_id":"cc79a07f-b0a7-4f8e-8eb6-b37b86458520","year":2015},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:3985591f37d16c4dbfdb6233add533ca00b6668e609219f5ad91697b4a7220b4","observation_id":"7c9e13fa-805b-404e-ae5b-fa364b1222d6","resolution":{"observed_at":"2026-05-16T07:40:45.014057Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Domain-adversarial training of neural networks.Journal of machine learning research, 17(59):1–35","venue":null,"work_id":"deef8216-e2b3-4415-9486-19fe31fdefa9","year":2016},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:e8d0b314e57ffee1aa12f0f4622d606ceef3dd23d18b8edf4d1ed0397050e9ea","observation_id":"630b4f07-48ee-4fff-bb76-a583bb60b9d3","resolution":{"observed_at":"2026-05-16T07:40:45.005414Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Low-latency auto- motive vision with event cameras.Nat., 629(8014):1034– 1040","venue":null,"work_id":"0ea889cf-b6cf-43e2-bef5-e6bb505fd4eb","year":2024},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:7b2a6aca183467574b4da411de0310a26f79b678d62128f3d516adb234a6a351","observation_id":"f067faae-264f-44bd-a8d3-b67cc1c1ec49","resolution":{"observed_at":"2026-05-16T07:40:45.009687Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Bootstrap your own latent-a new approach to self-supervised learning.Advances in neural information processing systems, 33:21271–21284","venue":null,"work_id":"887ec790-ef0d-437b-a61f-28ac992c7096","year":2020},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:8ec4c2fec0bc55bacd4f2c0c9facd164a9a698b9fb7daaf02320d5cda5716f28","observation_id":"6a4d1725-5a7a-40a8-8104-9005ad9b0fb3","resolution":{"observed_at":"2026-05-16T07:40:45.032120Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2101.06085","last_updated":"2021-09-01T08:08:55Z","snapshot_observed_at":"2026-07-06T10:32:49.624257Z","submitted_at":"2021-01-15T12:56:18Z","title":"Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes","version":2},"cited_work":{"arxiv_id":"2101.06085","doi":"10.48550/arxiv.2101.06085","metadata_source":"arxiv_reference","pith_arxiv_id":"2101.06085","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"Deep dual-resolution networks for real-time and accu- rate semantic segmentation of road scenes","venue":null,"work_id":"6fe3b027-4a12-40c1-8e58-1a874142dd58","year":2021},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"cited_paper":"/paper/2101.06085","citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:e415b7bb32fc393985f003f39878b1007b7e553a4f0f598b982833816121294b","observation_id":"231cbfbb-6429-4ff4-bc04-0e973ac2fa9d","resolution":{"observed_at":"2026-05-16T07:40:44.116537Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"v2e: From video frames to realistic dvs events","venue":null,"work_id":"53b02048-c648-4d5e-8932-4d45b0956146","year":2021},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:c391aa4b9eb8c5f0425679078206cce7150eb5764865fae14ed56bbe65114bc1","observation_id":"3077bfe0-fde9-4ee4-911d-8bb920a92698","resolution":{"observed_at":"2026-05-16T07:40:45.118431Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Ultralytics yolov5","venue":null,"work_id":"c30d2e16-62a8-4685-9981-591c85649b3d","year":2020},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:e14c09dba3085d6c762c9c33c1272ce0ef8b776274b4d2f8e0ebda9cdc9103c3","observation_id":"6929e1f4-4d16-4aa0-9076-72b55b092817","resolution":{"observed_at":"2026-05-16T07:40:45.114530Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.17725","last_updated":"2024-10-23T09:55:22Z","snapshot_observed_at":"2026-07-06T19:38:22.461739Z","submitted_at":"2024-10-23T09:55:22Z","title":"YOLOv11: An Overview of the Key Architectural Enhancements","version":1},"cited_work":{"arxiv_id":"2410.17725","doi":"10.48550/arxiv.2410.17725","metadata_source":"pith","pith_arxiv_id":"2410.17725","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"YOLOv11: An Overview of the Key Architectural Enhancements","venue":"cs.CV","work_id":"17e84c13-a2a4-4b25-9b05-ca4ca212abfa","year":2024},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"cited_paper":"/paper/2410.17725","citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:33582346533cfe8b00eb8f056502eefcc0dce8acd1b27d83a57fb19340c8d0e3","observation_id":"2c1c0ec7-ce6a-47ce-b51f-cad84546e645","resolution":{"observed_at":"2026-05-16T07:40:44.114562Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-07-16T22:51:55.782635+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-16T22:51:55.782635+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Openess: Event-based semantic scene understanding with open vocabularies","venue":null,"work_id":"c6308a18-e68b-44ae-97a5-9c1447511715","year":2024},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:392edb7568cde8c828df7dec311ca9d3cec58fe04cabe791f0da1cedddc4dd7c","observation_id":"cb6c0a2f-0585-4a6c-a503-d1ac4be6378d","resolution":{"observed_at":"2026-05-16T07:40:45.107015Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Learning using privileged information: SV M+ and weighted SVM","venue":null,"work_id":"dfec19a9-ac20-4b60-b09d-84fea8952adc","year":2014},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:472168b90f3c89cc8a75420bdb279b22cbda350b5604420b436f57a4c1235661","observation_id":"bdbfc167-6e15-4a97-a914-fafa5e9c1cec","resolution":{"observed_at":"2026-05-16T07:40:45.103258Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1810.03756","last_updated":"2019-02-18T06:33:11Z","snapshot_observed_at":"2026-07-06T07:06:49.418477Z","submitted_at":"2018-10-09T00:17:24Z","title":"SPIGAN: Privileged Adversarial Learning from Simulation","version":3},"cited_work":{"arxiv_id":"1810.03756","doi":null,"metadata_source":"pith","pith_arxiv_id":"1810.03756","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"SPIGAN: Privileged Adversarial Learning from Simulation","venue":"cs.CV","work_id":"2564c8b1-9723-40c1-9502-50b44787213f","year":2018},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"cited_paper":"/paper/1810.03756","citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:396995379f0f8c46b95959ad254fc24cc9030fb1566980488af302d8df8ff7f4","observation_id":"c882748c-9e3a-47b0-92cc-decf9baaa45d","resolution":{"observed_at":"2026-05-16T07:40:44.099584Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"A comprehensive survey on source-free domain adap- tation.IEEE Transactions on Pattern Analysis and Machine Intelligence, 46(8):5743–5762","venue":null,"work_id":"74ac9175-499d-4c49-a557-ea51140464cc","year":2024},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:7df3f5f218ec36ad59dcfd8df3dae806b62f54de48eff76a844675fb74dc631b","observation_id":"a1926b02-9ed5-49f5-b3aa-c4fc68659507","resolution":{"observed_at":"2026-05-16T07:40:45.101339Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Refinenet: Multi-path refinement networks for high- resolution semantic segmentation","venue":null,"work_id":"7f5fdd59-19b4-435b-acae-0213c7e2cc2d","year":1925},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:d1854f6e8fa0f2661e5aac529aea2c4166184c95287f836c5441e6984688a2f9","observation_id":"79e43e02-0e3b-41ac-9231-f24512bab61f","resolution":{"observed_at":"2026-05-16T07:40:45.105160Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Microsoft coco: Common objects in context","venue":null,"work_id":"6db70d7e-04cc-4e1c-9db9-5a90181572e3","year":2014},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:9e4e5c1f17a0f3a7f5bf865f6546485b445bff28da07699f24f336553f069ce1","observation_id":"45263e95-1b31-473f-8cf9-118ccefb39d9","resolution":{"observed_at":"2026-05-16T07:40:45.108752Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Focal loss for dense object detection","venue":null,"work_id":"ca1ccd26-1f35-4b97-93f7-123d55e52bb4","year":2017},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:3a22c4b176b257cc09fafed1427da86769880d9f250102dbf931d862a71f962a","observation_id":"afee34fb-35d2-4451-b9f5-ce23db1de143","resolution":{"observed_at":"2026-05-16T07:40:45.099040Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Beyond conventional vision: Rgb-event fusion for robust object detection in dy- namic traffic scenarios.Communications in Transportation Research, 5:100202","venue":null,"work_id":"9c1c28ae-6f04-4650-abd1-4063b33a74a5","year":2025},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:7994bdb2d138266ba03cc14f23d82f02f551382e30d834564ed832428c997793","observation_id":"5ec1aeec-90a4-41e7-b91b-b2532ad15edb","resolution":{"observed_at":"2026-05-16T07:40:45.096848Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1511.03643","last_updated":"2016-02-26T02:21:52Z","snapshot_observed_at":"2026-07-06T04:36:10.443201Z","submitted_at":"2015-11-11T20:27:54Z","title":"Unifying distillation and privileged information","version":3},"cited_work":{"arxiv_id":"1511.03643","doi":null,"metadata_source":"pith","pith_arxiv_id":"1511.03643","snapshot_observed_at":"2026-07-04T08:19:43.752776Z","title":"Unifying distillation and privileged information","venue":"stat.ML","work_id":"bfd01201-4931-4336-a866-7494e82ea07b","year":2015},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"cited_paper":"/paper/1511.03643","citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:7913af657c08b109161020c0b5cbfef728b9c9550c2a0e2a9ea72fdd9230d834","observation_id":"9ec2062f-ce8b-46a2-baef-2946d44f57be","resolution":{"observed_at":"2026-05-16T07:40:44.082173Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1711.05101","last_updated":"2019-01-04T21:01:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2017-11-14T14:24:06Z","title":"Decoupled Weight Decay Regularization","version":3},"cited_work":{"arxiv_id":"1711.05101","doi":"10.1137/1.9781611972825.47","metadata_source":"pith","pith_arxiv_id":"1711.05101","snapshot_observed_at":"2026-07-11T11:50:26.030339Z","title":"Decoupled Weight Decay Regularization","venue":"cs.LG","work_id":"07ef7360-d385-4033-83f7-8384a6325204","year":2017},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"cited_paper":"/paper/1711.05101","citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:535c59c1232366f438a1df23bd2587708debe97fd0b72d6fdfec665197607d89","observation_id":"98d7007a-bc37-4420-806b-11aa2e8b8766","resolution":{"observed_at":"2026-05-16T07:40:44.112622Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Fred: The florence rgb-event drone dataset","venue":null,"work_id":"44114f6a-c0e7-41f0-87e1-6d6f0765fe07","year":2025},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:0ea95d487520aeda151b6db3a96195dbf443d4b38a74301bacf69aedc3436e7c","observation_id":"4ce23410-15a7-4b72-981f-c516bfb13ded","resolution":{"observed_at":"2026-05-16T07:40:45.112486Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Adjeroh, and Gianfranco Doretto","venue":null,"work_id":"5f0c2c13-b2d3-4b25-ae42-0548e78ec045","year":2016},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:f532f886e923f38450c3937aa329ea7e5d1b0d44101d82067d1ca410d0a39732","observation_id":"b6bdcea0-1a79-4af3-bdd2-a8f2357fe4e7","resolution":{"observed_at":"2026-05-16T07:40:45.085658Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Domain gen- eralization for semantic segmentation: a survey.Artif","venue":null,"work_id":"dc82974a-f7a3-4cc2-ba0e-53a1b4d861f9","year":2024},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:3e59ded1d7d06d32db4b0a968f5bf23bf35c71bba42c3672e054a4978ec2535f","observation_id":"39dbb1a9-fa42-4b4b-8755-9cc683e40625","resolution":{"observed_at":"2026-05-16T07:40:45.090224Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"ESIM: an open event camera simulator.Conf","venue":null,"work_id":"a0a07733-0a1e-4666-b909-517b2c8ce2d4","year":2018},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:375312e84ca6940e6ebadb2245c062398d5b56c6f1f55dd0143fccb6cbd66430","observation_id":"eac67c12-5b57-48f4-b745-73c79554f397","resolution":{"observed_at":"2026-05-16T07:40:45.081206Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Film: Frame inter- polation for large motion","venue":null,"work_id":"91a64826-1efc-4b46-8501-5f70527168c3","year":2022},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:f957c8527e10d38e08d45cca608653d26901c6bf1e4941987750cbe7e35bdc0e","observation_id":"a5b37f2c-eaf6-44cf-83ca-c11f2024620b","resolution":{"observed_at":"2026-05-16T07:40:45.094530Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Faster r-cnn: Towards real-time object detection with region proposal networks.Advances in neural information process- ing systems, 28","venue":null,"work_id":"043403f3-5bc3-4647-9f55-f3b976149ae1","year":2015},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:1cbeb5ac303090847c2281820c51a3045bb64e7ba46cd7f695ee49dd4f5c9b25","observation_id":"af9f24bd-2218-4605-aab3-f090a4261a13","resolution":{"observed_at":"2026-05-16T07:40:45.060609Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Event-aware distilled detr for object detection in an automotive context","venue":null,"work_id":"5b262553-a0e6-4621-8b35-5d3d01f371e2","year":2025},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:01bc58f96880e436dd447797f5ceaf2793ec5b1f06321f3bec19a0e8cfbd9357","observation_id":"1cbc1f26-60bf-4184-9e5b-63956c77502f","resolution":{"observed_at":"2026-05-16T07:40:45.069271Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Guided curriculum model adaptation and uncertainty-aware evalua- tion for semantic nighttime image segmentation","venue":null,"work_id":"7f536351-32f0-4f93-a46f-aca26d256261","year":2019},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:57ad4bc80d5c2d9889632b995bba9305f1e9c9fdbde3ba9a425351d432d2ee06","observation_id":"68ce1173-4904-429f-b2c2-12581dd00e70","resolution":{"observed_at":"2026-05-16T07:40:45.069069Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Predicting privileged information for height es- timation","venue":null,"work_id":"735040c3-3915-48e6-bb21-57fa49618673","year":2016},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:86363eb85a74627bf97ced2e456bad9ee559c921b7c53253e00af041948cd769","observation_id":"0d3b645f-6377-4a94-8595-0f8301111cab","resolution":{"observed_at":"2026-05-16T07:40:45.074715Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Domain gener- alization for semantic segmentation: A survey","venue":null,"work_id":"d79b080a-84eb-47e2-85e0-e538d4301831","year":2025},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:9ac15d2a1b9f9af323cf3a52808acc0658175d2a5ba250f075f1a78640bdb0ba","observation_id":"07a953a7-9843-46b8-a54b-e2094c46d679","resolution":{"observed_at":"2026-05-16T07:40:45.080969Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"f1069746-8d83-4e01-9a04-2a4206e14e1a","year":2013},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:c38bd70ff1bc7a8b3956831ea1de1f0def39f01b8b573d2461c31a5cfd2b8b27","observation_id":"84eddbba-4e37-4861-b47f-a5c1a2d88555","resolution":{"observed_at":"2026-05-16T07:40:45.104824Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Sparse-gated rgb-event fusion for small object detection in the wild.Remote Sensing, 17(17)","venue":null,"work_id":"fb51d911-f8ac-4acd-9c12-242040ca4018","year":2025},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:208f3e3ce582d5762b14991d4efb9093e3c72b5ab6ad68ef9eae40a8f9110041","observation_id":"9fb58754-47f5-4078-bf8b-91e48f4ac935","resolution":{"observed_at":"2026-05-16T07:40:45.045204Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Ess: Learning event-based semantic seg- mentation from still images","venue":null,"work_id":"831354cd-6f46-444d-8efb-59bf4ea2f438","year":2022},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:4a428e9aed069b9c379cbdebe81fbdda9d1a82aab3200689c03d4ed334d7b88c","observation_id":"f2edca50-370a-4073-b470-da75a4637e1e","resolution":{"observed_at":"2026-05-16T07:40:45.040472Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Cityscape-adverse: Benchmarking robust- ness of semantic segmentation with realistic scene modifica- tions via diffusion-based image editing.IEEE Access","venue":null,"work_id":"c6212779-af7d-4591-9df5-d884c8b7806f","year":2025},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:06c8f021bdac24d3e38aa6bedc91cf3b1ec1b543a3bf89d67eafe05ef8370839","observation_id":"1498acab-156b-4060-8975-1e1ad622f68d","resolution":{"observed_at":"2026-05-16T07:40:45.054668Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Adversarial discriminative domain adaptation","venue":null,"work_id":"ed597fcc-97cf-4666-bd34-9c02f2327c75","year":2017},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:6d66b7fffa0550337ce3f430871d1aa147f653533af69d69b900567e847074ec","observation_id":"941973f9-3b0c-4ca3-90f7-9b9415f8f8e4","resolution":{"observed_at":"2026-05-16T07:40:45.099227Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"A new learning paradigm: Learning using privileged information.Neural networks, 22(5-6):544–557","venue":null,"work_id":"1416d65f-dd58-4a76-b8ba-09608c8a8eeb","year":2009},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:f9e85796847caf93c5708b4dc3d74d19f3d68d7897a160baed32c98241e4b38e","observation_id":"d41a703b-6a98-48f1-8b93-93402901c168","resolution":{"observed_at":"2026-05-16T07:40:45.067111Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Attention is all you need.Advances in neural information processing systems, 30","venue":null,"work_id":"b03fecf9-cc5f-401c-b081-67b383acf24b","year":2017},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:1e771b6c819fa8d2ca089093bf9379ec2b4186be12345a08fbea536842762338","observation_id":"6edc39cd-a792-48e8-b729-8dcda5869cb7","resolution":{"observed_at":"2026-05-16T07:40:45.091141Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Dada: Depth-aware domain adap- tation in semantic segmentation","venue":null,"work_id":"70030840-5022-4a4a-89ab-94df243339e2","year":2019},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:200cf24bccaea886c64c46c6fc983ba971688c19e48b7e935bc6cb3325999136","observation_id":"aff7c18f-a1e1-471f-a2b2-0aa213edfa9e","resolution":{"observed_at":"2026-05-16T07:40:45.110766Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2207.02696","last_updated":"2022-07-06T14:01:58Z","snapshot_observed_at":"2026-07-06T13:28:24.787332Z","submitted_at":"2022-07-06T14:01:58Z","title":"YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors","version":1},"cited_work":{"arxiv_id":"2207.02696","doi":"10.48550/arxiv.2207.02696","metadata_source":"pith","pith_arxiv_id":"2207.02696","snapshot_observed_at":"2026-07-10T13:47:05.761907Z","title":"& Liao, H.-Y","venue":"cs.CV","work_id":"a933f8ab-bc6a-45bd-b63f-f9930b782ddc","year":2022},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"cited_paper":"/paper/2207.02696","citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:79aca4753169ce2579ede4102d8cdb11c0960f37d4c9f9a230fce608bd3b79bb","observation_id":"303a1962-01b3-4dfd-aa91-e90327f17fd1","resolution":{"observed_at":"2026-05-16T07:40:44.095857Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Generalizing to unseen domains: A survey on domain generalization.IEEE transactions on knowledge and data engineering, 35(8):8052–8072","venue":null,"work_id":"3ef294ae-fe71-4644-b46d-e59c18e1cf55","year":2022},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:89d552fee6e8abe9524b5e261df56f463febc2b0236e6c0f8db42c0c7577f639","observation_id":"0ca27284-7ea8-4914-9a9b-39f62fc0dbcd","resolution":{"observed_at":"2026-05-16T07:40:45.089294Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Segformer: Simple and efficient design for semantic segmentation with transform- ers.Advances in neural information processing systems, 34: 12077–12090","venue":null,"work_id":"d270ede0-5f1e-4718-bcbe-a97722958ba2","year":2021},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:fdb022a2dfdec13d62fcf035e129debe793bea16ab2daacaa26c1c20ca0a1153","observation_id":"62c32439-85d5-4ee7-aa9a-351708d63fd7","resolution":{"observed_at":"2026-05-16T07:40:45.097496Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Exploiting event temporal dynam- ics and sparsity characteristics for rgb-event fusion seman- tic segmentation","venue":null,"work_id":"ae4ceb54-ccec-4137-9c78-522161d6d02b","year":2025},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:db03265d942b272e2dfe63b1f77f4acac616930d4e67bfa4952c0ea05707c97f","observation_id":"df55024c-73fc-4f6b-88c5-c36665121f79","resolution":{"observed_at":"2026-05-16T07:40:45.103050Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Pyramid scene parsing network","venue":null,"work_id":"2d92f7d0-b108-4906-9cd9-bd5e2e6ffd4a","year":2017},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:a3075fed37c382e32d9876923819a0e70269970e811fbeb629937b9e05dec361","observation_id":"d67470c3-bf65-4ad8-8cfa-e44ee15f837a","resolution":{"observed_at":"2026-05-16T07:40:45.064683Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Icnet for real-time semantic segmenta- tion on high-resolution images","venue":null,"work_id":"5893a0c4-056c-4956-9948-1ecda7ff4105","year":2018},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:523b17e205e0713bff58defd0d9797cf8e042ac9503a58d1c379954fb6f24bf0","observation_id":"099898c7-4fb8-46b3-9bc5-57c94985cbbd","resolution":{"observed_at":"2026-05-16T07:40:45.070906Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Detrs beat yolos on real-time object detection","venue":null,"work_id":"684bef59-efed-4c6c-a2ba-67788bc1e9fa","year":2024},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:a89f415e7a73d6dc14b3118c4448a43d6b34bd8e2c8a17bb0ee2ba0ebfe30602","observation_id":"2e81ea17-5ad4-4b15-83eb-49738c0402e8","resolution":{"observed_at":"2026-05-16T07:40:45.085209Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"ESEG: event-based seg- mentation boosted by explicit edge-semantic guidance","venue":null,"work_id":"241d18fe-5096-4744-a05f-ddffd374451e","year":2025},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:5d778939494aa1ae6620826e6e91cd504fc4cf2f3576434939c76ead5078cfbd","observation_id":"13fa30f1-6a26-409b-aabc-ade280ffad76","resolution":{"observed_at":"2026-05-16T07:40:45.057286Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Rethinking semantic segmen- tation from a sequence-to-sequence perspective with trans- formers","venue":null,"work_id":"40d8d691-e3da-446d-a86b-5e4e1689f4f6","year":null},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:990993309002ae4076399694d41e200b46b00cb01b0d36d7e5139b850203702a","observation_id":"f0d2ac64-98dc-486f-b311-5080bc6f9d81","resolution":{"observed_at":"2026-05-16T07:40:45.046323Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Domain generalization: A survey.IEEE transactions on pattern analysis and machine intelligence, 45(4):4396–4415","venue":null,"work_id":"dfbc4426-7de8-4dd5-bd08-eb4dd17dca00","year":2022},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:816641992bbc1970c17bd0a76b564dbc46834e9406cb42f4b0ba3ff55281c832","observation_id":"6d51194f-1415-4f5f-ae30-13fdcdfed784","resolution":{"observed_at":"2026-05-16T07:40:45.106840Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1904.07850","last_updated":"2019-04-25T16:20:02Z","snapshot_observed_at":"2026-07-06T07:46:34.901111Z","submitted_at":"2019-04-16T17:54:26Z","title":"Objects as Points","version":2},"cited_work":{"arxiv_id":"1904.07850","doi":"10.48550/arxiv.1904.07850","metadata_source":"pith","pith_arxiv_id":"1904.07850","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"Objects as Points","venue":"cs.CV","work_id":"3567080d-f164-46ab-903a-02853db3a970","year":2019},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"cited_paper":"/paper/1904.07850","citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:a05216ab91164ad1ae6527e8944abf85771a0dd434e4d4b9ac0955a511a59e99","observation_id":"380c571e-c9a2-40cc-ab28-62f9fc27e3f7","resolution":{"observed_at":"2026-05-16T07:40:44.087016Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Event-based stereo visual odometry.IEEE Transactions on Robotics, 37 (5):1433–1450","venue":null,"work_id":"95875614-9e89-413b-95de-49c5eff56815","year":2021},"citing_paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization","version":2},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-05-16T07:37:38.263234Z"},"links":{"citing_paper":"/paper/2602.04583"},"observation_digest":"sha256:662d4ff86ea11640886e7b8281877d676318ff8538c1fd4f2512c54c8a27381c","observation_id":"b0233b8a-3812-469f-8688-4c4b388ca943","resolution":{"observed_at":"2026-05-16T07:40:45.034041Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2602.04583","last_updated":"2026-04-17T16:27:47Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-07-06T22:44:33.166340Z","submitted_at":"2026-02-04T14:10:36Z","title":"PEPR: Privileged Event-based Predictive Regularization for Domain Generalization"},"reference_resolution":{"displayed":65,"state_counts":{"malformed_identifier":1,"metadata_mismatch":2,"parse_uncertain":0,"unresolved":2,"verified_exact":9,"verified_fuzzy":51},"total_outbound_references":65},"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":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"thesis":"As of 4 August 2026, this Paper Citation Record lists 65 of 65 outbound references and 0 inbound Pith citation observations for arXiv:2602.04583."}