Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Are Vision Transformers Robust to Spurious Correlations?
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2203.09125.
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 2026-08-06T06:34:29.942622+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-05-23T17:14:23.513216Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-23T17:15:43.637790Z
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 8502974e-852e-4f5e-86a0-b08d21e0930e · inbound
The Pragmatic Frames of Spurious Correlations in Machine Learning: Interpreting How and Why They Matter cites this paper.
The Pragmatic Frames of Spurious Correlations in Machine Learning: Interpreting How and Why They Matter Are Vision Transformers Robust to Spurious Correlations?
Reference 2
- Resolution
- verified exact
- arxiv_id, observed 2026-05-23T17:15:43.641417Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 07ace5d7-4704-4790-a2d9-654b5313806d · inbound
Deep Attention Reweighting: Post-Hoc Attention-Based Feature Aggregation in CNNs for Disentangling Core and Spurious Features under Spurious Correlations cites this paper.
Deep Attention Reweighting: Post-Hoc Attention-Based Feature Aggregation in CNNs for Disentangling Core and Spurious Features under Spurious Correlations Are Vision Transformers Robust to Spurious Correlations?
Reference 14
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T05:09:38.814612Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.