Paper Citation Record · LEDGER

An Analysis of Model Robustness across Concurrent Distribution Shifts

As of 14 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 2026-08-14T06:32:32.682623+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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: 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 2026-08-14T06:32:32.682623+00:00.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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.

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 2026-08-14T06:32:32.682623+00:00.

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.

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.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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.

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 2026-08-14T06:32:32.682623+00:00.

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 2026-08-14T06:32:32.682623+00:00.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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.

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.

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.

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.

Pith citing papers

No inbound Pith citation observations are available.