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Paper Citation Record · LEDGER

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization

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.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2602.04583 v2

Coverage vector

measured 65 of 65 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-16T07:37:38.263234Z

measured 65 of 65 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

65 of 65 outbound references displayed

  • verified exact9
  • verified fuzzy51
  • unresolved2
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b44a5813-483c-4781-b46f-0bf714b98afe · outbound

This paper cites Ev-segnet: Semantic segmentation for event-based cameras.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization Ev-segnet: Semantic segmentation for event-based cameras

Reference 1

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verified fuzzy
raw_fallback, observed 2026-05-16T07:40:45.076597Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:183282f7a618a4f07115a3da6a31ca37fc998b8340ecf6fdda82b46ada217e26

Observation 87a6fecc-49ff-41f1-95b9-cae9208e30cc · outbound

This paper cites Self-supervised learning from images with a joint-embedding predictive architecture.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization Self-supervised learning from images with a joint-embedding predictive architecture

Reference 2

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verified fuzzy
raw_fallback, observed 2026-05-16T07:40:45.082867Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:b10e6b77a334d3da5051e14aae3e4b0a2a546362ad34f3c3cf6d1cdfcf2004c6

Observation 10d87c3c-b641-4255-8841-35c48e2c3b4b · outbound

This paper cites V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning

Reference 3

Resolution
verified exact
local_arxiv, observed 2026-05-16T07:40:44.111305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:9af76e015f07693f10d76d1da88ba4d96161402a305a77ba96d5dfc0a85bce83

Observation dae3207e-b68a-42bf-a0fd-bc1cc06fdad1 · outbound

This paper cites LeJEPA: Provable and Scalable Self-Supervised Learning Without the Heuristics.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization LeJEPA: Provable and Scalable Self-Supervised Learning Without the Heuristics

Reference 4

Resolution
verified exact
local_arxiv, observed 2026-05-16T07:40:44.103816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:d4eef8cf6f74de654aee2e2cb451366e5f194af0b35c3a6c5276d3d43d65448f

Observation fd6b7914-de7b-401a-8a8f-4d368fcf0177 · outbound

This paper cites Fea- ture hallucination via privileged information for neuromor- phic face analysis.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization Fea- ture hallucination via privileged information for neuromor- phic face analysis

Reference 5

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verified fuzzy
raw_fallback, observed 2026-05-16T07:40:45.071094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:32b75a675a126f52e3cbdced28781af2ebcdb3e94bc4b61478c253ebc57b998c

Observation 685eefa7-98bd-4ebd-bc06-22eeb32fe80f · outbound

This paper cites End-to- end object detection with transformers.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization End-to- end object detection with transformers

Reference 6

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verified fuzzy
raw_fallback, observed 2026-05-16T07:40:45.075136Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:5aa3826a008a2f8cc62751549a6ee91736c044db009ca59e351296d7eef8d052

Observation 8b818e79-d07c-4959-8184-3ef970d0fcb9 · outbound

This paper cites Emerg- ing properties in self-supervised vision transformers.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization Emerg- ing properties in self-supervised vision transformers

Reference 7

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verified fuzzy
raw_fallback, observed 2026-05-16T07:40:45.078733Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:8b6c1b98ed75a6cdee9966a1d111e6f630b6318fa1abfb1aeec8012bec347e4a

Observation f08fc99a-2fe5-4bce-a1f2-cd6a7ba53815 · outbound

This paper cites an unresolved cited work.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization Unresolved cited work

Reference 8

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unresolved
raw_fallback, observed 2026-05-16T07:40:45.087753Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:ade8c494aa25764be91781c877644103d51e1ac19fd20d23bdaa3bb021002034

Observation f36d5644-5c9b-4350-aaf1-dae1df5785d2 · outbound

This paper cites Encoder-decoder with atrous separable convolution for semantic image segmentation.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization Encoder-decoder with atrous separable convolution for semantic image segmentation

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T07:40:45.079055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:203d0cd5214234ff0001e224b89e8bb4c5388a8cc0e19d42262130b79289acbd

Observation be6fa97a-5567-4a96-9113-630a2c38ca7d · outbound

This paper cites A simple framework for contrastive learning of visual representations.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization A simple framework for contrastive learning of visual representations

Reference 10

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verified fuzzy
raw_fallback, observed 2026-05-16T07:40:45.095266Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:d02792f56d2302c63d62a38a5a613456a472d642c4f3006dc49562ab540f9e2d

Observation 68ae1861-18a5-4d3b-a0b6-a7c4eb8b3366 · outbound

This paper cites Masked-attention mask transformer for universal image segmentation.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization Masked-attention mask transformer for universal image segmentation

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T07:40:45.064869Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:a1899d29ee9aa0180d7d877853343840935079d1f5a9ad658b78da703176cf8c

Observation dc6aa781-0c1c-432e-87f7-a5c453a5bfbe · outbound

This paper cites An Empirical Study of Invariant Risk Minimization.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization An Empirical Study of Invariant Risk Minimization

Reference 12

Resolution
metadata mismatch
arxiv_id, observed 2026-05-16T07:40:44.098576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:c1e56ebb0a66d140ba8dcecb8048898b8554483db37877d6d53278011babe700

Observation 512180b3-5f6d-48ab-a611-672cf25c2dfc · outbound

This paper cites MMSegmentation: Openmmlab semantic segmentation toolbox and benchmark.https : / / github.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization MMSegmentation: Openmmlab semantic segmentation toolbox and benchmark.https : / / github

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T07:40:45.092390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:de5098f1f7d578da5483ca367171e9365de54c936f6891b4741a593927433362

Observation 0719da1c-a490-47df-8b98-ccaa28ff5f30 · outbound

This paper cites The cityscapes dataset for semantic urban scene understanding.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization The cityscapes dataset for semantic urban scene understanding

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T07:40:45.116702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:bd68c19f74af08cb13c92b24aee377b1aee8da671c849afd46034c4d0e2fcb38

Observation 9610dd77-db03-4d8f-8019-412afc10c89b · outbound

This paper cites Introduction to Latent Variable Energy-Based Models: A Path Towards Autonomous Machine Intelligence.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization Introduction to Latent Variable Energy-Based Models: A Path Towards Autonomous Machine Intelligence

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-05-16T07:40:44.107919Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:692064b2b81993c606d07460973a4d62169a1c626f768223bc4f26fd9374be5f

Observation f9581d2d-04c4-4821-9178-d78f09cfd687 · outbound

This paper cites You only look at one sequence: Rethinking transformer in vision through object detection.Advances in Neural Information Processing Systems, 34:26183–26197.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization You only look at one sequence: Rethinking transformer in vision through object detection.Advances in Neural Information Processing Systems, 34:26183–26197

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T07:40:45.087334Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:7d4b79d6bfa53cd313fedf80b005b4541152e7ca210058f0e47cdc3da9847d63

Observation aa770c1e-f8f3-4375-9742-3b9fd7b25ca8 · outbound

This paper cites Source-free unsupervised domain adaptation: A survey.Neural Networks, 174:106230.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization Source-free unsupervised domain adaptation: A survey.Neural Networks, 174:106230

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T07:40:45.011258Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:b149a14bdb95e584d54c4a38d6f14e96ae413bfe41d12d4c13b56fc82ed7f422

Observation 7c9e13fa-805b-404e-ae5b-fa364b1222d6 · outbound

This paper cites Unsupervised domain adaptation by backpropagation.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization Unsupervised domain adaptation by backpropagation

Reference 18

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raw_fallback, observed 2026-05-16T07:40:45.014057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:3985591f37d16c4dbfdb6233add533ca00b6668e609219f5ad91697b4a7220b4

Observation 630b4f07-48ee-4fff-bb76-a583bb60b9d3 · outbound

This paper cites Domain-adversarial training of neural networks.Journal of machine learning research, 17(59):1–35.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization Domain-adversarial training of neural networks.Journal of machine learning research, 17(59):1–35

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T07:40:45.005414Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:e8d0b314e57ffee1aa12f0f4622d606ceef3dd23d18b8edf4d1ed0397050e9ea

Observation f067faae-264f-44bd-a8d3-b67cc1c1ec49 · outbound

This paper cites Low-latency auto- motive vision with event cameras.Nat., 629(8014):1034– 1040.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization Low-latency auto- motive vision with event cameras.Nat., 629(8014):1034– 1040

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T07:40:45.009687Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:7b2a6aca183467574b4da411de0310a26f79b678d62128f3d516adb234a6a351

Observation 6a4d1725-5a7a-40a8-8104-9005ad9b0fb3 · outbound

This paper cites Bootstrap your own latent-a new approach to self-supervised learning.Advances in neural information processing systems, 33:21271–21284.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization Bootstrap your own latent-a new approach to self-supervised learning.Advances in neural information processing systems, 33:21271–21284

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T07:40:45.032120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:8ec4c2fec0bc55bacd4f2c0c9facd164a9a698b9fb7daaf02320d5cda5716f28

Observation 231cbfbb-6429-4ff4-bc04-0e973ac2fa9d · outbound

This paper cites Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-05-16T07:40:44.116537Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:e415b7bb32fc393985f003f39878b1007b7e553a4f0f598b982833816121294b

Observation 3077bfe0-fde9-4ee4-911d-8bb920a92698 · outbound

This paper cites v2e: From video frames to realistic dvs events.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization v2e: From video frames to realistic dvs events

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T07:40:45.118431Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:c391aa4b9eb8c5f0425679078206cce7150eb5764865fae14ed56bbe65114bc1

Observation 6929e1f4-4d16-4aa0-9076-72b55b092817 · outbound

This paper cites Ultralytics yolov5.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization Ultralytics yolov5

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T07:40:45.114530Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:e14c09dba3085d6c762c9c33c1272ce0ef8b776274b4d2f8e0ebda9cdc9103c3

Observation 2c1c0ec7-ce6a-47ce-b51f-cad84546e645 · outbound

This paper cites YOLOv11: An Overview of the Key Architectural Enhancements.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization YOLOv11: An Overview of the Key Architectural Enhancements

Reference 25

Resolution
verified exact
local_arxiv, observed 2026-05-16T07:40:44.114562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:33582346533cfe8b00eb8f056502eefcc0dce8acd1b27d83a57fb19340c8d0e3

Observation cb6c0a2f-0585-4a6c-a503-d1ac4be6378d · outbound

This paper cites Openess: Event-based semantic scene understanding with open vocabularies.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization Openess: Event-based semantic scene understanding with open vocabularies

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T07:40:45.107015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:392edb7568cde8c828df7dec311ca9d3cec58fe04cabe791f0da1cedddc4dd7c

Observation bdbfc167-6e15-4a97-a914-fafa5e9c1cec · outbound

This paper cites Learning using privileged information: SV M+ and weighted SVM.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization Learning using privileged information: SV M+ and weighted SVM

Reference 27

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verified fuzzy
raw_fallback, observed 2026-05-16T07:40:45.103258Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:472168b90f3c89cc8a75420bdb279b22cbda350b5604420b436f57a4c1235661

Observation c882748c-9e3a-47b0-92cc-decf9baaa45d · outbound

This paper cites SPIGAN: Privileged Adversarial Learning from Simulation.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization SPIGAN: Privileged Adversarial Learning from Simulation

Reference 28

Resolution
verified exact
local_arxiv, observed 2026-05-16T07:40:44.099584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:396995379f0f8c46b95959ad254fc24cc9030fb1566980488af302d8df8ff7f4

Observation a1926b02-9ed5-49f5-b3aa-c4fc68659507 · outbound

This paper cites A comprehensive survey on source-free domain adap- tation.IEEE Transactions on Pattern Analysis and Machine Intelligence, 46(8):5743–5762.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization A comprehensive survey on source-free domain adap- tation.IEEE Transactions on Pattern Analysis and Machine Intelligence, 46(8):5743–5762

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T07:40:45.101339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:7df3f5f218ec36ad59dcfd8df3dae806b62f54de48eff76a844675fb74dc631b

Observation 79e43e02-0e3b-41ac-9231-f24512bab61f · outbound

This paper cites Refinenet: Multi-path refinement networks for high- resolution semantic segmentation.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization Refinenet: Multi-path refinement networks for high- resolution semantic segmentation

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T07:40:45.105160Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:d1854f6e8fa0f2661e5aac529aea2c4166184c95287f836c5441e6984688a2f9

Observation 45263e95-1b31-473f-8cf9-118ccefb39d9 · outbound

This paper cites Microsoft coco: Common objects in context.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization Microsoft coco: Common objects in context

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T07:40:45.108752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:9e4e5c1f17a0f3a7f5bf865f6546485b445bff28da07699f24f336553f069ce1

Observation afee34fb-35d2-4451-b9f5-ce23db1de143 · outbound

This paper cites Focal loss for dense object detection.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization Focal loss for dense object detection

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T07:40:45.099040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:3a22c4b176b257cc09fafed1427da86769880d9f250102dbf931d862a71f962a

Observation 5ec1aeec-90a4-41e7-b91b-b2532ad15edb · outbound

This paper cites Beyond conventional vision: Rgb-event fusion for robust object detection in dy- namic traffic scenarios.Communications in Transportation Research, 5:100202.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization Beyond conventional vision: Rgb-event fusion for robust object detection in dy- namic traffic scenarios.Communications in Transportation Research, 5:100202

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T07:40:45.096848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:7994bdb2d138266ba03cc14f23d82f02f551382e30d834564ed832428c997793

Observation 9ec2062f-ce8b-46a2-baef-2946d44f57be · outbound

This paper cites Unifying distillation and privileged information.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization Unifying distillation and privileged information

Reference 34

Resolution
verified exact
local_arxiv, observed 2026-05-16T07:40:44.082173Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:7913af657c08b109161020c0b5cbfef728b9c9550c2a0e2a9ea72fdd9230d834

Observation 98d7007a-bc37-4420-806b-11aa2e8b8766 · outbound

This paper cites Decoupled Weight Decay Regularization.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization Decoupled Weight Decay Regularization

Reference 35

Resolution
verified exact
local_arxiv, observed 2026-05-16T07:40:44.112622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:535c59c1232366f438a1df23bd2587708debe97fd0b72d6fdfec665197607d89

Observation 4ce23410-15a7-4b72-981f-c516bfb13ded · outbound

This paper cites Fred: The florence rgb-event drone dataset.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization Fred: The florence rgb-event drone dataset

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T07:40:45.112486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:0ea95d487520aeda151b6db3a96195dbf443d4b38a74301bacf69aedc3436e7c

Observation b6bdcea0-1a79-4af3-bdd2-a8f2357fe4e7 · outbound

This paper cites Adjeroh, and Gianfranco Doretto.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization Adjeroh, and Gianfranco Doretto

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T07:40:45.085658Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:f532f886e923f38450c3937aa329ea7e5d1b0d44101d82067d1ca410d0a39732

Observation 39dbb1a9-fa42-4b4b-8755-9cc683e40625 · outbound

This paper cites Domain gen- eralization for semantic segmentation: a survey.Artif.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization Domain gen- eralization for semantic segmentation: a survey.Artif

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T07:40:45.090224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:3e59ded1d7d06d32db4b0a968f5bf23bf35c71bba42c3672e054a4978ec2535f

Observation eac67c12-5b57-48f4-b745-73c79554f397 · outbound

This paper cites ESIM: an open event camera simulator.Conf.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization ESIM: an open event camera simulator.Conf

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T07:40:45.081206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:375312e84ca6940e6ebadb2245c062398d5b56c6f1f55dd0143fccb6cbd66430

Observation a5b37f2c-eaf6-44cf-83ca-c11f2024620b · outbound

This paper cites Film: Frame inter- polation for large motion.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization Film: Frame inter- polation for large motion

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T07:40:45.094530Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:f957c8527e10d38e08d45cca608653d26901c6bf1e4941987750cbe7e35bdc0e

Observation af9f24bd-2218-4605-aab3-f090a4261a13 · outbound

This paper cites Faster r-cnn: Towards real-time object detection with region proposal networks.Advances in neural information process- ing systems, 28.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization Faster r-cnn: Towards real-time object detection with region proposal networks.Advances in neural information process- ing systems, 28

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T07:40:45.060609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:1cbeb5ac303090847c2281820c51a3045bb64e7ba46cd7f695ee49dd4f5c9b25

Observation 1cbc1f26-60bf-4184-9e5b-63956c77502f · outbound

This paper cites Event-aware distilled detr for object detection in an automotive context.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization Event-aware distilled detr for object detection in an automotive context

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T07:40:45.069271Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:01bc58f96880e436dd447797f5ceaf2793ec5b1f06321f3bec19a0e8cfbd9357

Observation 68ce1173-4904-429f-b2c2-12581dd00e70 · outbound

This paper cites Guided curriculum model adaptation and uncertainty-aware evalua- tion for semantic nighttime image segmentation.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization Guided curriculum model adaptation and uncertainty-aware evalua- tion for semantic nighttime image segmentation

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T07:40:45.069069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:57ad4bc80d5c2d9889632b995bba9305f1e9c9fdbde3ba9a425351d432d2ee06

Observation 0d3b645f-6377-4a94-8595-0f8301111cab · outbound

This paper cites Predicting privileged information for height es- timation.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization Predicting privileged information for height es- timation

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T07:40:45.074715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:86363eb85a74627bf97ced2e456bad9ee559c921b7c53253e00af041948cd769

Observation 07a953a7-9843-46b8-a54b-e2094c46d679 · outbound

This paper cites Domain gener- alization for semantic segmentation: A survey.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization Domain gener- alization for semantic segmentation: A survey

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T07:40:45.080969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:9ac15d2a1b9f9af323cf3a52808acc0658175d2a5ba250f075f1a78640bdb0ba

Observation 84eddbba-4e37-4861-b47f-a5c1a2d88555 · outbound

This paper cites an unresolved cited work.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization Unresolved cited work

Reference 46

Resolution
unresolved
raw_fallback, observed 2026-05-16T07:40:45.104824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:c38bd70ff1bc7a8b3956831ea1de1f0def39f01b8b573d2461c31a5cfd2b8b27

Observation 9fb58754-47f5-4078-bf8b-91e48f4ac935 · outbound

This paper cites Sparse-gated rgb-event fusion for small object detection in the wild.Remote Sensing, 17(17).

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization Sparse-gated rgb-event fusion for small object detection in the wild.Remote Sensing, 17(17)

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T07:40:45.045204Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:208f3e3ce582d5762b14991d4efb9093e3c72b5ab6ad68ef9eae40a8f9110041

Observation f2edca50-370a-4073-b470-da75a4637e1e · outbound

This paper cites Ess: Learning event-based semantic seg- mentation from still images.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization Ess: Learning event-based semantic seg- mentation from still images

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T07:40:45.040472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:4a428e9aed069b9c379cbdebe81fbdda9d1a82aab3200689c03d4ed334d7b88c

Observation 1498acab-156b-4060-8975-1e1ad622f68d · outbound

This paper cites Cityscape-adverse: Benchmarking robust- ness of semantic segmentation with realistic scene modifica- tions via diffusion-based image editing.IEEE Access.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization Cityscape-adverse: Benchmarking robust- ness of semantic segmentation with realistic scene modifica- tions via diffusion-based image editing.IEEE Access

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T07:40:45.054668Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:06c8f021bdac24d3e38aa6bedc91cf3b1ec1b543a3bf89d67eafe05ef8370839

Observation 941973f9-3b0c-4ca3-90f7-9b9415f8f8e4 · outbound

This paper cites Adversarial discriminative domain adaptation.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization Adversarial discriminative domain adaptation

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T07:40:45.099227Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:6d66b7fffa0550337ce3f430871d1aa147f653533af69d69b900567e847074ec

Observation d41a703b-6a98-48f1-8b93-93402901c168 · outbound

This paper cites A new learning paradigm: Learning using privileged information.Neural networks, 22(5-6):544–557.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization A new learning paradigm: Learning using privileged information.Neural networks, 22(5-6):544–557

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T07:40:45.067111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:f9e85796847caf93c5708b4dc3d74d19f3d68d7897a160baed32c98241e4b38e

Observation 6edc39cd-a792-48e8-b729-8dcda5869cb7 · outbound

This paper cites Attention is all you need.Advances in neural information processing systems, 30.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization Attention is all you need.Advances in neural information processing systems, 30

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T07:40:45.091141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:1e771b6c819fa8d2ca089093bf9379ec2b4186be12345a08fbea536842762338

Observation aff7c18f-a1e1-471f-a2b2-0aa213edfa9e · outbound

This paper cites Dada: Depth-aware domain adap- tation in semantic segmentation.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization Dada: Depth-aware domain adap- tation in semantic segmentation

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T07:40:45.110766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:200cf24bccaea886c64c46c6fc983ba971688c19e48b7e935bc6cb3325999136

Observation 303a1962-01b3-4dfd-aa91-e90327f17fd1 · outbound

This paper cites YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors

Reference 54

Resolution
metadata mismatch
arxiv_id, observed 2026-05-16T07:40:44.095857Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:79aca4753169ce2579ede4102d8cdb11c0960f37d4c9f9a230fce608bd3b79bb

Observation 0ca27284-7ea8-4914-9a9b-39f62fc0dbcd · outbound

This paper cites Generalizing to unseen domains: A survey on domain generalization.IEEE transactions on knowledge and data engineering, 35(8):8052–8072.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization Generalizing to unseen domains: A survey on domain generalization.IEEE transactions on knowledge and data engineering, 35(8):8052–8072

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T07:40:45.089294Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:89d552fee6e8abe9524b5e261df56f463febc2b0236e6c0f8db42c0c7577f639

Observation 62c32439-85d5-4ee7-aa9a-351708d63fd7 · outbound

This paper cites Segformer: Simple and efficient design for semantic segmentation with transform- ers.Advances in neural information processing systems, 34: 12077–12090.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization Segformer: Simple and efficient design for semantic segmentation with transform- ers.Advances in neural information processing systems, 34: 12077–12090

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T07:40:45.097496Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:fdb022a2dfdec13d62fcf035e129debe793bea16ab2daacaa26c1c20ca0a1153

Observation df55024c-73fc-4f6b-88c5-c36665121f79 · outbound

This paper cites Exploiting event temporal dynam- ics and sparsity characteristics for rgb-event fusion seman- tic segmentation.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization Exploiting event temporal dynam- ics and sparsity characteristics for rgb-event fusion seman- tic segmentation

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T07:40:45.103050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:db03265d942b272e2dfe63b1f77f4acac616930d4e67bfa4952c0ea05707c97f

Observation d67470c3-bf65-4ad8-8cfa-e44ee15f837a · outbound

This paper cites Pyramid scene parsing network.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization Pyramid scene parsing network

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T07:40:45.064683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:a3075fed37c382e32d9876923819a0e70269970e811fbeb629937b9e05dec361

Observation 099898c7-4fb8-46b3-9bc5-57c94985cbbd · outbound

This paper cites Icnet for real-time semantic segmenta- tion on high-resolution images.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization Icnet for real-time semantic segmenta- tion on high-resolution images

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T07:40:45.070906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:523b17e205e0713bff58defd0d9797cf8e042ac9503a58d1c379954fb6f24bf0

Observation 2e81ea17-5ad4-4b15-83eb-49738c0402e8 · outbound

This paper cites Detrs beat yolos on real-time object detection.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization Detrs beat yolos on real-time object detection

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T07:40:45.085209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:a89f415e7a73d6dc14b3118c4448a43d6b34bd8e2c8a17bb0ee2ba0ebfe30602

Observation 13fa30f1-6a26-409b-aabc-ade280ffad76 · outbound

This paper cites ESEG: event-based seg- mentation boosted by explicit edge-semantic guidance.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization ESEG: event-based seg- mentation boosted by explicit edge-semantic guidance

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T07:40:45.057286Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:5d778939494aa1ae6620826e6e91cd504fc4cf2f3576434939c76ead5078cfbd

Observation f0d2ac64-98dc-486f-b311-5080bc6f9d81 · outbound

This paper cites Rethinking semantic segmen- tation from a sequence-to-sequence perspective with trans- formers.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization Rethinking semantic segmen- tation from a sequence-to-sequence perspective with trans- formers

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T07:40:45.046323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:990993309002ae4076399694d41e200b46b00cb01b0d36d7e5139b850203702a

Observation 6d51194f-1415-4f5f-ae30-13fdcdfed784 · outbound

This paper cites Domain generalization: A survey.IEEE transactions on pattern analysis and machine intelligence, 45(4):4396–4415.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization Domain generalization: A survey.IEEE transactions on pattern analysis and machine intelligence, 45(4):4396–4415

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T07:40:45.106840Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:816641992bbc1970c17bd0a76b564dbc46834e9406cb42f4b0ba3ff55281c832

Observation 380c571e-c9a2-40cc-ab28-62f9fc27e3f7 · outbound

This paper cites Objects as Points.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization Objects as Points

Reference 64

Resolution
verified exact
local_arxiv, observed 2026-05-16T07:40:44.087016Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:a05216ab91164ad1ae6527e8944abf85771a0dd434e4d4b9ac0955a511a59e99

Observation b0233b8a-3812-469f-8688-4c4b388ca943 · outbound

This paper cites Event-based stereo visual odometry.IEEE Transactions on Robotics, 37 (5):1433–1450.

PEPR: Privileged Event-based Predictive Regularization for Domain Generalization Event-based stereo visual odometry.IEEE Transactions on Robotics, 37 (5):1433–1450

Reference 65

Resolution
malformed identifier
raw_fallback, observed 2026-05-16T07:40:45.034041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T07:37:38.263234Z digest=sha256:662d4ff86ea11640886e7b8281877d676318ff8538c1fd4f2512c54c8a27381c

Pith citing papers

No inbound Pith citation observations are available.