Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Vision Models Are More Robust And Fair When Pretrained On Uncurated Images Without Supervision
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2202.08360.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-08T12:12:30.698078Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-15T13:26:53.963779Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation b6df6ee8-6465-4775-ab8a-2522ce7a9d75 · inbound
R3M: A Universal Visual Representation for Robot Manipulation cites this paper.
R3M: A Universal Visual Representation for Robot Manipulation Vision Models Are More Robust And Fair When Pretrained On Uncurated Images Without Supervision
Reference 13
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T13:26:53.967176Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 8ba28ccd-9876-4e0d-9bab-498307162344 · inbound
DINOv2: Learning Robust Visual Features without Supervision cites this paper.
DINOv2: Learning Robust Visual Features without Supervision Vision Models Are More Robust And Fair When Pretrained On Uncurated Images Without Supervision
Reference 12
- Resolution
- verified exact
- arxiv_id, observed 2026-05-09T04:17:20.412841Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 527c3422-2315-4ed5-932b-77c2d1f15290 · inbound
Vision Transformers Need Registers cites this paper.
Vision Transformers Need Registers Vision Models Are More Robust And Fair When Pretrained On Uncurated Images Without Supervision
Reference 15
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-13T09:41:38.184117Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 3a7462ef-1539-44e5-9c73-55a7a8aba4d0 · inbound
Revisiting Feature Prediction for Learning Visual Representations from Video cites this paper.
Revisiting Feature Prediction for Learning Visual Representations from Video Vision Models Are More Robust And Fair When Pretrained On Uncurated Images Without Supervision
Reference 115
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-12T12:40:23.934267Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation ce691cb0-a1e3-42be-8825-ad63d52dfaf6 · inbound
Scaling Pre-training to One Hundred Billion Data for Vision Language Models cites this paper.
Scaling Pre-training to One Hundred Billion Data for Vision Language Models Vision Models Are More Robust And Fair When Pretrained On Uncurated Images Without Supervision
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T12:12:30.698078Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f3cba657-06aa-439d-83b6-dc58ec640525 · inbound
Data-Driven Self-Supervised Learning for the Discovery of Solution Singularity for Partial Differential Equations cites this paper.
Data-Driven Self-Supervised Learning for the Discovery of Solution Singularity for Partial Differential Equations Vision Models Are More Robust And Fair When Pretrained On Uncurated Images Without Supervision
Reference 32
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T21:49:11.864829Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 29e6aaa7-c7cb-4fe2-95f7-0e40921d68e5 · inbound
Improving Remote Sensing Classification using Topological Data Analysis and Convolutional Neural Networks cites this paper.
Improving Remote Sensing Classification using Topological Data Analysis and Convolutional Neural Networks Vision Models Are More Robust And Fair When Pretrained On Uncurated Images Without Supervision
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T17:36:38.129558Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bca69808-93c8-4ca4-9ac4-b5f6415c5da4 · inbound
Understanding the Effects of Distractors on Reasoning Vision-Language Models cites this paper.
Understanding the Effects of Distractors on Reasoning Vision-Language Models Vision Models Are More Robust And Fair When Pretrained On Uncurated Images Without Supervision
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T20:08:00.686537Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9c5a6414-787f-464f-91df-b2899f208387 · inbound
Geographic Diversity Beats Data Volume for Cross-Domain Generalization in Zero-Label JEPA Driving World Models cites this paper.
Geographic Diversity Beats Data Volume for Cross-Domain Generalization in Zero-Label JEPA Driving World Models Vision Models Are More Robust And Fair When Pretrained On Uncurated Images Without Supervision
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-07-11T18:32:47.329159Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.