Paper Citation Record · LEDGER

Re-evaluating Group Robustness via Adaptive Class-Specific Scaling

As of 15 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 0 inbound Pith citation observations for arXiv:2412.15311.

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

pith.paper-citation-record.v1
2412.15311 v1

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T11:47:53.141784Z

measured 37 of 37 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+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

37 of 37 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 653c86a6-0582-4feb-a01e-a4eca6624f89 · outbound

This paper cites Systematic generalisation with group invariant predictions.

Re-evaluating Group Robustness via Adaptive Class-Specific Scaling Systematic generalisation with group invariant predictions

Reference 1

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Observation 67e6a408-e85b-45fe-a29f-8b7e91b3d293 · outbound

This paper cites Invariant Risk Minimization.

Re-evaluating Group Robustness via Adaptive Class-Specific Scaling Invariant Risk Minimization

Reference 2

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Observation 0aefe8aa-5891-4e7a-92e4-55d94ab5e92f · outbound

This paper cites Learning de-biased repre- sentations with biased representations.

Re-evaluating Group Robustness via Adaptive Class-Specific Scaling Learning de-biased repre- sentations with biased representations

Reference 3

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Observation ac6fd3b6-cef8-40c5-8610-75624dfa6a7f · outbound

This paper cites Functional map of the world.

Re-evaluating Group Robustness via Adaptive Class-Specific Scaling Functional map of the world

Reference 4

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Observation 543ccc3a-9125-414e-906e-de8b1751baab · outbound

This paper cites Environment inference for invariant learning.

Re-evaluating Group Robustness via Adaptive Class-Specific Scaling Environment inference for invariant learning

Reference 5

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Observation 2381707f-686c-4ba9-b2af-9f2ce2f9c85b · outbound

This paper cites Imagenet: A large-scale hierarchi- cal image database.

Re-evaluating Group Robustness via Adaptive Class-Specific Scaling Imagenet: A large-scale hierarchi- cal image database

Reference 6

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Observation f5d51e0e-ac63-4bd9-86f0-c5950e4eba22 · outbound

This paper cites Measuring statistical depen- dence with hilbert-schmidt norms.

Re-evaluating Group Robustness via Adaptive Class-Specific Scaling Measuring statistical depen- dence with hilbert-schmidt norms

Reference 7

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Observation 7ee0d190-00e9-4e37-90b5-8e008f8b8a28 · outbound

This paper cites On calibration of modern neural networks.

Re-evaluating Group Robustness via Adaptive Class-Specific Scaling On calibration of modern neural networks

Reference 8

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This paper cites Deep Residual Learning for Image Recognition.

Re-evaluating Group Robustness via Adaptive Class-Specific Scaling Deep Residual Learning for Image Recognition

Reference 9

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Observation 9c762f0e-d589-4e70-bec4-19a482bdd673 · outbound

This paper cites Learning deep representation for imbal- anced classification.

Re-evaluating Group Robustness via Adaptive Class-Specific Scaling Learning deep representation for imbal- anced classification

Reference 10

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Observation 155e4c72-16d2-4072-a1ac-f0b557e136e6 · outbound

This paper cites Densely connected convo- lutional networks.

Re-evaluating Group Robustness via Adaptive Class-Specific Scaling Densely connected convo- lutional networks

Reference 11

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Observation 285edce2-7de2-4b19-b802-d07ec5f3fa42 · outbound

This paper cites Simple data bal- ancing achieves competitive worst-group-accuracy.

Re-evaluating Group Robustness via Adaptive Class-Specific Scaling Simple data bal- ancing achieves competitive worst-group-accuracy

Reference 12

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Observation b9acdd50-8b87-4a1f-8412-e5e934d50891 · outbound

This paper cites Fairface: Face attribute dataset for balanced race, gender, and age.

Re-evaluating Group Robustness via Adaptive Class-Specific Scaling Fairface: Face attribute dataset for balanced race, gender, and age

Reference 13

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Observation f4fe8899-1133-4417-b108-5e47f16c90d0 · outbound

This paper cites Learning Debiased Classifier with Biased Committee.

Re-evaluating Group Robustness via Adaptive Class-Specific Scaling Learning Debiased Classifier with Biased Committee

Reference 14

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Observation 7aed36d4-1da1-4b03-9ef5-9f8da8d6f248 · outbound

This paper cites Last Layer Re-Training is Sufficient for Robustness to Spurious Correlations.

Re-evaluating Group Robustness via Adaptive Class-Specific Scaling Last Layer Re-Training is Sufficient for Robustness to Spurious Correlations

Reference 15

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Observation bb4b3349-a6c4-4039-a0ba-55b710fff0ac · outbound

This paper cites Wilds: A benchmark of in-the-wild distribution shifts.

Re-evaluating Group Robustness via Adaptive Class-Specific Scaling Wilds: A benchmark of in-the-wild distribution shifts

Reference 16

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Observation 03f30e53-d37b-42f7-838b-2d06b58aed51 · outbound

This paper cites Large-scale methods for distributionally ro- bust optimization.

Re-evaluating Group Robustness via Adaptive Class-Specific Scaling Large-scale methods for distributionally ro- bust optimization

Reference 17

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Observation 34030e83-ef52-4c63-aa5c-06d162a005d9 · outbound

This paper cites Just train twice: Improving group robustness without training group information.

Re-evaluating Group Robustness via Adaptive Class-Specific Scaling Just train twice: Improving group robustness without training group information

Reference 18

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Observation c8e0e320-8ab5-4285-b99a-f361339b0472 · outbound

This paper cites Avoiding spurious correlations via logit correction.

Re-evaluating Group Robustness via Adaptive Class-Specific Scaling Avoiding spurious correlations via logit correction

Reference 19

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Observation d3c0af2c-fff5-44a0-a2a2-93a58a8aca83 · outbound

This paper cites Deep learning face attributes in the wild.

Re-evaluating Group Robustness via Adaptive Class-Specific Scaling Deep learning face attributes in the wild

Reference 20

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Observation ee5a17bc-a206-4cd4-ae45-08617b12c9e3 · outbound

This paper cites Learning from failure: Training debiased classifier from biased classifier.

Re-evaluating Group Robustness via Adaptive Class-Specific Scaling Learning from failure: Training debiased classifier from biased classifier

Reference 21

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Observation dc30f988-27cb-4599-9aa7-f678bdf0cb65 · outbound

This paper cites Pytorch: An imperative style, high- performance deep learning library.

Re-evaluating Group Robustness via Adaptive Class-Specific Scaling Pytorch: An imperative style, high- performance deep learning library

Reference 22

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Observation f365bda2-ed4d-432a-8713-dc4fd7e56077 · outbound

This paper cites Probabilistic Outputs for Support Vector Machines and Comparisons to Regularized Likelihood Methods.

Re-evaluating Group Robustness via Adaptive Class-Specific Scaling Probabilistic Outputs for Support Vector Machines and Comparisons to Regularized Likelihood Methods

Reference 23

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Observation 2a0aa489-71a2-4426-8c0e-b4430b81beab · outbound

This paper cites Distributionally robust neural networks for group shifts: On the importance of regularization for worst-case gen- eralization.

Re-evaluating Group Robustness via Adaptive Class-Specific Scaling Distributionally robust neural networks for group shifts: On the importance of regularization for worst-case gen- eralization

Reference 24

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Observation fd92df94-3c4a-474c-8c00-0f43a20264fb · outbound

This paper cites DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter.

Re-evaluating Group Robustness via Adaptive Class-Specific Scaling DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter

Reference 25

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Observation abaec5a9-b719-41e0-beed-c925baaf7e0d · outbound

This paper cites Information-theoretic bias reduction via causal view of spurious correlation.

Re-evaluating Group Robustness via Adaptive Class-Specific Scaling Information-theoretic bias reduction via causal view of spurious correlation

Reference 26

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Observation 81f3c7cd-7073-47c3-a24c-cc7f2db35785 · outbound

This paper cites Unsupervised learning of debiased representations with pseudo-attributes.

Re-evaluating Group Robustness via Adaptive Class-Specific Scaling Unsupervised learning of debiased representations with pseudo-attributes

Reference 27

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Observation c28de385-83d5-489f-9440-94d5bf8e2c35 · outbound

This paper cites No subclass left behind: Fine-grained robustness in coarse-grained classifica- tion problems.

Re-evaluating Group Robustness via Adaptive Class-Specific Scaling No subclass left behind: Fine-grained robustness in coarse-grained classifica- tion problems

Reference 28

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Observation 0cddcff1-35c0-409b-b418-feed657f2103 · outbound

This paper cites The caltech-ucsd birds- 200-2011 dataset.

Re-evaluating Group Robustness via Adaptive Class-Specific Scaling The caltech-ucsd birds- 200-2011 dataset

Reference 29

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Observation bf01a128-2b6c-43ef-8f19-69a9fb1b551b · outbound

This paper cites Correct-N-Contrast: A Contrastive Approach for Improving Robustness to Spurious Correlations.

Re-evaluating Group Robustness via Adaptive Class-Specific Scaling Correct-N-Contrast: A Contrastive Approach for Improving Robustness to Spurious Correlations

Reference 30

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This paper cites Places: A 10 mil- lion image database for scene recognition.

Re-evaluating Group Robustness via Adaptive Class-Specific Scaling Places: A 10 mil- lion image database for scene recognition

Reference 31

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Observation 6ce57e5b-1580-4f12-85fd-8a13181e0c81 · outbound

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Re-evaluating Group Robustness via Adaptive Class-Specific Scaling Unresolved cited work

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Re-evaluating Group Robustness via Adaptive Class-Specific Scaling Unresolved cited work

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Re-evaluating Group Robustness via Adaptive Class-Specific Scaling Unresolved cited work

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Observation 41fefccc-e15d-478d-969d-d4f013ff5c7a · outbound

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Re-evaluating Group Robustness via Adaptive Class-Specific Scaling Unresolved cited work

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Observation 81761e4a-23b2-4b92-acab-86755c03e66a · outbound

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Re-evaluating Group Robustness via Adaptive Class-Specific Scaling spurious correlation

Reference 36

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Observation 358e9e9e-9f16-4134-b46f-e2d51802a946 · outbound

This paper cites It consists of 76,863 training images from the years 2002-2013, 19,915 validation images from the years 2013-2016, and 22,108 test images from the years 2016-2018.

Re-evaluating Group Robustness via Adaptive Class-Specific Scaling It consists of 76,863 training images from the years 2002-2013, 19,915 validation images from the years 2013-2016, and 22,108 test images from the years 2016-2018

Reference 2018

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:47:53.310149Z

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Pith citing papers

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