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Paper Citation Record · LEDGER

Salient ImageNet: How to discover spurious features in Deep Learning?

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2110.04301.

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

pith.paper-citation-record.v1
2110.04301 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:58:54.461506Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

20
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 17583874-3941-4865-b3c4-bb702c1f6d2f · inbound

MaskMedPaint: Masked Medical Image Inpainting with Diffusion Models for Mitigation of Spurious Correlations cites this paper.

MaskMedPaint: Masked Medical Image Inpainting with Diffusion Models for Mitigation of Spurious Correlations Salient ImageNet: How to discover spurious features in Deep Learning?

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-12T19:30:14.594675Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T19:30:14.594675Z digest=sha256:5a917c2b881664a9f8e64dd8300c54e7955f2668031d7735cdbb832482549d1c

Observation 4e472d25-5b37-43f6-b41a-62b933d5d8d5 · inbound

Escaping the SpuriVerse: Can Large Vision-Language Models Generalize Beyond Seen Spurious Correlations? cites this paper.

Escaping the SpuriVerse: Can Large Vision-Language Models Generalize Beyond Seen Spurious Correlations? Salient ImageNet: How to discover spurious features in Deep Learning?

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-15T18:58:54.461506Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:58:54.461506Z digest=sha256:cf35fd5fc7afbe79aa87b87845e29903ab57d8e41c9a626628dfb7b4cd3147f7

Observation df05d2f8-a6bc-41ec-99ff-812450ddf684 · inbound

Shortcut Learning in Generalist Robot Policies: The Role of Dataset Diversity and Fragmentation cites this paper.

Shortcut Learning in Generalist Robot Policies: The Role of Dataset Diversity and Fragmentation Salient ImageNet: How to discover spurious features in Deep Learning?

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-05T22:50:43.760875Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:50:43.760875Z digest=sha256:9f2c6bf7837516d899456af0bee4e1a24d1d8762633b88f678e092a1fd5007cb

Observation 945a2a45-89ff-4c26-a00d-cfe74713465d · inbound

SPARSE Data, Rich Results: Few-Shot Semi-Supervised Learning via Class-Conditioned Image Translation cites this paper.

SPARSE Data, Rich Results: Few-Shot Semi-Supervised Learning via Class-Conditioned Image Translation Salient ImageNet: How to discover spurious features in Deep Learning?

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-05T22:46:43.463517Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:46:43.463517Z digest=sha256:ac7c70c5bbb01015db0c7e9c551ecbef06c91cf5a849352abc6f11bcecc427c3

Observation 9746d7fc-bd35-4bc3-a4b3-9309a1f9565c · inbound

Token-Based Detection of Spurious Correlations in Vision Transformers cites this paper.

Token-Based Detection of Spurious Correlations in Vision Transformers Salient ImageNet: How to discover spurious features in Deep Learning?

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-05T10:31:37.401626Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:31:37.401626Z digest=sha256:db0e06b7d5dbbb9475668f37f607a4198fc86eb519481158451dee28c5f2878c

Observation 8b5c6c1a-0c5f-4ed8-9154-83ef9facc99e · inbound

UNBOX: Unveiling Black-box visual models with Natural-language cites this paper.

UNBOX: Unveiling Black-box visual models with Natural-language Salient ImageNet: How to discover spurious features in Deep Learning?

Reference 43

Resolution
verified exact
arxiv_id, observed 2026-05-15T14:30:03.679405Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-15T14:27:21.335382Z digest=sha256:0cc876f093a2f7bbe571f484e3fd8f14c4c96c29a47b3f514abcdc273f5edab7

Observation 3e9cb08c-f2ab-4bf2-92f2-e8720a2eca40 · inbound

Spurious Correlation Learning in Preference Optimization: Mechanisms, Consequences, and Mitigation via Tie Training cites this paper.

Spurious Correlation Learning in Preference Optimization: Mechanisms, Consequences, and Mitigation via Tie Training Salient ImageNet: How to discover spurious features in Deep Learning?

Reference 30

Resolution
metadata mismatch
arxiv_id, observed 2026-05-13T06:32:24.294535Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-05-13T06:30:51.812541Z digest=sha256:612c632a368e119f5d3b9a565e883716d9808b08d4bff23e5eb39963e3d25ee9

Observation 0ed6e474-ceec-4f60-b44e-5ebfec08731b · inbound

MAPS: A Synthetic Dataset for Probing Vision Models in a Controlled 3D Scene Space cites this paper.

MAPS: A Synthetic Dataset for Probing Vision Models in a Controlled 3D Scene Space Salient ImageNet: How to discover spurious features in Deep Learning?

Reference 54

Resolution
verified exact
arxiv_id, observed 2026-05-21T06:34:00.709753Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-21T06:31:38.977531Z digest=sha256:edebaeeccd9b7018a667ec673ceabdf414a68dc39e0a6ddb6443c0d9cd917cba

Observation 28f74321-e10c-4112-b90a-c1d251dbaef9 · inbound

Cumulative Meta-Learning from Active Learning Queries for Robustness to Spurious Correlations cites this paper.

Cumulative Meta-Learning from Active Learning Queries for Robustness to Spurious Correlations Salient ImageNet: How to discover spurious features in Deep Learning?

Reference 57

Resolution
verified exact
arxiv_id, observed 2026-05-21T06:29:41.857670Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-05-21T06:29:04.835827Z digest=sha256:0e80ce2c5509d27eac143bce74cd13434573d46be74a7a40440528758f11ab8f

Observation 1a836f1d-e184-4d68-a635-3f3cbc1d8927 · inbound

TEVI: Text-Conditioned Editing of Visual Representations via Sparse Autoencoders for Improved Vision-Language Alignment cites this paper.

TEVI: Text-Conditioned Editing of Visual Representations via Sparse Autoencoders for Improved Vision-Language Alignment Salient ImageNet: How to discover spurious features in Deep Learning?

Reference 218

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T16:47:10.108212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-06-27T22:22:01.979434Z digest=sha256:8a9f54e1e1747d44fc856e03172e13b7b92c4c15aa975a76f1a6933aad0d944c