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Paper Citation Record · LEDGER

An Analysis of Model Robustness across Concurrent Distribution Shifts

As of 13 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 0 inbound Pith citation observations for arXiv:2501.04288.

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

pith.paper-citation-record.v1
2501.04288 v1

Coverage vector

measured 20 of 20 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T21:42:09.551043Z

measured 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+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

20 of 20 outbound references displayed

  • verified exact1
  • verified fuzzy1
  • unresolved17
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fe3e2c90-a69a-46a8-bebd-10ee143aef7f · outbound

This paper cites Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone.

An Analysis of Model Robustness across Concurrent Distribution Shifts Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone

Reference 1

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no resolver link, observed 2026-08-10T21:42:09.463140Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:42:09.463140Z digest=sha256:a2c6812d7766ec83280b786ec1e71d5b3156f6c07f892fd8e2c58de39c1810a2

Observation a0b6ccdf-bc2f-4e09-a187-3c59d47e52b4 · outbound

This paper cites a photo of alabel.

An Analysis of Model Robustness across Concurrent Distribution Shifts a photo of alabel

Reference 3

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malformed identifier
raw_fallback, observed 2026-08-10T21:42:10.028666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T21:42:09.541245Z digest=sha256:357d8883cdd827252f88fa4f19cdab9398b7ce3e4f25b2fd8731b230eb4d2f2f

Observation f8c9aea5-3f84-4ef3-91b8-c5a8340a8793 · outbound

This paper cites In Search of Lost Domain Generalization.

An Analysis of Model Robustness across Concurrent Distribution Shifts In Search of Lost Domain Generalization

Reference 7

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unresolved
no resolver link, observed 2026-08-10T21:42:09.492503Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:42:09.492503Z digest=sha256:3d946aa11238d0daf3289bb1e3b108aaad79b2a60a88cb632fe643a03d3ab776

Observation f857ca36-a542-4f6a-9fb4-d1bfe6b9e988 · outbound

This paper cites Benchmarking Neural Network Robustness to Common Corruptions and Perturbations.

An Analysis of Model Robustness across Concurrent Distribution Shifts Benchmarking Neural Network Robustness to Common Corruptions and Perturbations

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-10T21:42:09.496577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:42:09.496577Z digest=sha256:f8c7fe711617a8527cfa7c300c29a4048c2441c839d4721388964da27b336d9a

Observation 9d0e42de-8f18-494a-b6b6-d2d0297c2efd · outbound

This paper cites AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty.

An Analysis of Model Robustness across Concurrent Distribution Shifts AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty

Reference 9

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unresolved
no resolver link, observed 2026-08-10T21:42:09.500840Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:42:09.500840Z digest=sha256:58b5bfd9b4a917f406d79874685e06a53f2ced256b517d5a4b4e3405ed3ae4b8

Observation 52983890-8d27-481b-894b-d216adae1b82 · outbound

This paper cites Improved Baselines with Visual Instruction Tuning.

An Analysis of Model Robustness across Concurrent Distribution Shifts Improved Baselines with Visual Instruction Tuning

Reference 11

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unresolved
no resolver link, observed 2026-08-10T21:42:09.510265Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:42:09.510265Z digest=sha256:91098047e987f81095dbbaba96e485dd87f61b18e4ecabd3deecc69f1feea4c5

Observation 9a43ea9a-a50d-4deb-ad54-95f61413b0dc · outbound

This paper cites UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction.

An Analysis of Model Robustness across Concurrent Distribution Shifts UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-10T21:42:09.516149Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:42:09.516149Z digest=sha256:3036da1d09b6ba980bea57cfc970cd196885f340b44fe7c567cc1332b56d7f63

Observation 57edbbc9-21e2-4672-8e65-10f89f2c912d · outbound

This paper cites an unresolved cited work.

An Analysis of Model Robustness across Concurrent Distribution Shifts Unresolved cited work

Reference 13

Resolution
unresolved
raw_fallback, observed 2026-08-10T21:42:10.041607Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T21:42:09.520473Z digest=sha256:16fb915e0f1a413d98cec28c9a86df916cb927226c5c19716f515c4eb0862548

Observation 26606550-7c7c-43d8-b608-a8561b91ec24 · outbound

This paper cites Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization.

An Analysis of Model Robustness across Concurrent Distribution Shifts Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-10T21:42:09.524622Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:42:09.524622Z digest=sha256:78e163a80bec3f5a0c5936afccb4701c53f3e0ad948f3d72656eeaf32db8d522

Observation d5a2ca9a-960e-4d24-963b-8b664e0c7382 · outbound

This paper cites A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications.

An Analysis of Model Robustness across Concurrent Distribution Shifts A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-10T21:42:09.528866Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:42:09.528866Z digest=sha256:268eecd2045cc289e1743af297be4e9a035e4cf8e7fac973d703d71cd6c98ce5

Observation fcdf2420-2ed5-4a6e-a570-af32c680ef49 · outbound

This paper cites A Fine-Grained Analysis on Distribution Shift.

An Analysis of Model Robustness across Concurrent Distribution Shifts A Fine-Grained Analysis on Distribution Shift

Reference 16

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unresolved
no resolver link, observed 2026-08-10T21:42:09.532960Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:42:09.532960Z digest=sha256:d6e39def3a132f9225d71251cea06703fbd7aea8aede054c41a81326ebd2e419

Observation 1078e62c-c8c9-403a-b670-addb945d1f14 · outbound

This paper cites Improve Unsupervised Domain Adaptation with Mixup Training.

An Analysis of Model Robustness across Concurrent Distribution Shifts Improve Unsupervised Domain Adaptation with Mixup Training

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-10T21:42:09.537146Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:42:09.537146Z digest=sha256:7aed91413caf31758fd6516d4e5659192858848d04255fbf20e5bde64d6ead11

Observation ac1acfd4-0149-42e6-a7b7-111ee00a100e · outbound

This paper cites an unresolved cited work.

An Analysis of Model Robustness across Concurrent Distribution Shifts Unresolved cited work

Reference 19

Resolution
verified exact
raw_fallback, observed 2026-08-10T21:42:09.780212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T21:42:09.545407Z digest=sha256:49bdab90ab0e57677625f48d68cf7136be9861e30a99aaf1998b2b055debcca9

Observation da52dde3-c6b2-4e0a-a24e-5946dd9eca4e · outbound

This paper cites However, such datasets are limited as annotations are expensive.

An Analysis of Model Robustness across Concurrent Distribution Shifts However, such datasets are limited as annotations are expensive

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:42:10.016020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T21:42:09.551043Z digest=sha256:f17749af12f40cc135f5b8f9f131fe417ddefb4158fb161a02e7e097e6a7e96c

Observation 68bc7575-a037-4e05-9036-954ed74b3a8d · outbound

This paper cites ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness.

An Analysis of Model Robustness across Concurrent Distribution Shifts ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness

Reference 2016

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unresolved
no resolver link, observed 2026-08-10T21:42:09.487848Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:42:09.487848Z digest=sha256:aa836dc7801403ff362c7a3db7bfb57371a25ca7fa93dc2e945750038f689b62

Observation 5124f09e-5363-46fa-9400-ccf67321fd0e · outbound

This paper cites Invariant Risk Minimization.

An Analysis of Model Robustness across Concurrent Distribution Shifts Invariant Risk Minimization

Reference 2018

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unresolved
no resolver link, observed 2026-08-10T21:42:09.468328Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:42:09.468328Z digest=sha256:b2e88f1e080685cfea94d908bbbfe4864eef23392424a755a6fcacff51e86dcc

Observation 4bf6ea6f-a88d-4ff7-950f-9109929c8472 · outbound

This paper cites PaLI: A Jointly-Scaled Multilingual Language-Image Model.

An Analysis of Model Robustness across Concurrent Distribution Shifts PaLI: A Jointly-Scaled Multilingual Language-Image Model

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-10T21:42:09.472792Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:42:09.472792Z digest=sha256:fcac14063dc8e97842e2a43f540f2c3068fece32a1bed54bec45595dcda75eb3

Observation 2897f0e7-ba53-4954-a6d9-2d3fb34158d6 · outbound

This paper cites Invariant Causal Mechanisms through Distribution Matching.

An Analysis of Model Robustness across Concurrent Distribution Shifts Invariant Causal Mechanisms through Distribution Matching

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-10T21:42:09.477767Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:42:09.477767Z digest=sha256:a08c209e9de77140949214623f923d336c1747e2abeaf49be9fce3bda34a6e3a

Observation 0ad0c043-0db3-48f1-a4e2-75e4c7a8bf2d · outbound

This paper cites Progressive Growing of GANs for Improved Quality, Stability, and Variation.

An Analysis of Model Robustness across Concurrent Distribution Shifts Progressive Growing of GANs for Improved Quality, Stability, and Variation

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-10T21:42:09.505589Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:42:09.505589Z digest=sha256:f291527dc2c2a217e8e0eac2efb0ccde57dd321e16753dc7c3090913c4bda2f2

Observation fb20a7dc-7474-4747-b0ee-40ba149b329e · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

An Analysis of Model Robustness across Concurrent Distribution Shifts An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-10T21:42:09.483272Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:42:09.483272Z digest=sha256:25c0990ce214688380095e31b5e9c27ed2575b6282566ff55d786f0a97a2622d

Pith citing papers

No inbound Pith citation observations are available.