Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers | Paper Citation Record

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

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone

Reference 1

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Observation eff65095-7f1d-4c31-960d-98c1df6c2017 · outbound

This paper cites FairML: ToolBox for diagnosing bias in predictive modeling.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers FairML: ToolBox for diagnosing bias in predictive modeling

Reference 2

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Observation 59a31212-b119-435d-861d-afaa53df7a02 · outbound

This paper cites Estimat- ing example difficulty using variance of gradients.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Estimat- ing example difficulty using variance of gradients

Reference 3

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This paper cites Diffusion visual counterfactual explana- tions.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Diffusion visual counterfactual explana- tions

Reference 4

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Observation 1c5df337-a7f2-4e4c-a2e8-efee107938e1 · outbound

This paper cites Kudchadkar, and James Fackler.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Kudchadkar, and James Fackler

Reference 5

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Observation 120ff368-6f1e-4c1a-8ef3-0ce7c58000ca · outbound

This paper cites Learning to Split for Automatic Bias Detection.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Learning to Split for Automatic Bias Detection

Reference 6

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This paper cites Clip retrieval: Easily compute clip embeddings and build a clip retrieval system with them.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Clip retrieval: Easily compute clip embeddings and build a clip retrieval system with them

Reference 7

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Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Unresolved cited work

Reference 8

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This paper cites Man is to computer program- mer as woman is to homemaker? debiasing word embed- dings.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Man is to computer program- mer as woman is to homemaker? debiasing word embed- dings

Reference 9

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Observation cb34da14-1142-40bb-b343-5d80b41bdb66 · outbound

This paper cites Gender shades: Inter- sectional accuracy disparities in commercial gender classi- fication.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Gender shades: Inter- sectional accuracy disparities in commercial gender classi- fication

Reference 10

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Observation 63fc8af0-8626-46e7-bddf-c3a3d2e46ba0 · outbound

This paper cites Fairvis: Visual analytics for discovering intersectional bias in machine learning.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Fairvis: Visual analytics for discovering intersectional bias in machine learning

Reference 11

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Observation 17128b7a-9674-43fb-ac87-f3aeb4fcdd5b · outbound

This paper cites Conceptual 12M: Pushing web-scale image-text pre-training to recognize long-tail visual concepts.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Conceptual 12M: Pushing web-scale image-text pre-training to recognize long-tail visual concepts

Reference 12

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Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Unresolved cited work

Reference 13

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This paper cites Say my name: a model’s bias dis- covery framework.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Say my name: a model’s bias dis- covery framework

Reference 14

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This paper cites What could go wrong? discovering and describing failure modes in computer vision.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers What could go wrong? discovering and describing failure modes in computer vision

Reference 15

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This paper cites The spotlight: A general method for discov- ering systematic errors in deep learning models.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers The spotlight: A general method for discov- ering systematic errors in deep learning models

Reference 16

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Observation 645c4d84-e32c-45a3-9e62-04a0eeb89a4b · outbound

This paper cites Openbias: Open-set bias detection in text-to-image generative models.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Openbias: Open-set bias detection in text-to-image generative models

Reference 17

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This paper cites The Llama 3 Herd of Models.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers The Llama 3 Herd of Models

Reference 18

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This paper cites Domino: Discovering sys- tematic errors with cross-modal embeddings.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Domino: Discovering sys- tematic errors with cross-modal embeddings

Reference 19

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This paper cites Datacomp: In search of the next generation of multimodal datasets.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Datacomp: In search of the next generation of multimodal datasets

Reference 20

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This paper cites Gallegos, Ryan A.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Gallegos, Ryan A

Reference 21

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This paper cites Adaptive testing of computer vision models.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Adaptive testing of computer vision models

Reference 22

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This paper cites Deep residual learning for image recognition.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Deep residual learning for image recognition

Reference 23

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This paper cites Women also snowboard: Over- coming bias in captioning models.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Women also snowboard: Over- coming bias in captioning models

Reference 24

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This paper cites Generating counterfactual explanations with natural language.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Generating counterfactual explanations with natural language

Reference 25

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This paper cites Sugarcrepe: Fixing hackable benchmarks for vision-language compositionality.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Sugarcrepe: Fixing hackable benchmarks for vision-language compositionality

Reference 26

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Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Unresolved cited work

Reference 27

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This paper cites Imagenet-x: Understanding model mistakes with factor of variation annotations.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Imagenet-x: Understanding model mistakes with factor of variation annotations

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This paper cites Miss- ingness bias in model debugging.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Miss- ingness bias in model debugging

Reference 29

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This paper cites Distilling model failures as directions in latent space.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Distilling model failures as directions in latent space

Reference 30

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This paper cites Survey of hallucination in natural language generation.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Survey of hallucination in natural language generation

Reference 31

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This paper cites Lewis, and Guha Balakrishnan.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Lewis, and Guha Balakrishnan

Reference 32

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This paper cites Discovering and miti- gating visual biases through keyword explanation.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Discovering and miti- gating visual biases through keyword explanation

Reference 33

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This paper cites Udis: Unsupervised discovery of bias in deep visual recognition models.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Udis: Unsupervised discovery of bias in deep visual recognition models

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This paper cites Discover the unknown biased attribute of an image classifier.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Discover the unknown biased attribute of an image classifier

Reference 35

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This paper cites Discover and mitigate unknown biases with debiasing alternate net- works.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Discover and mitigate unknown biases with debiasing alternate net- works

Reference 36

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

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Just train twice: Improving group robustness without training group information

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Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Visual instruction tuning

Reference 38

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Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Improved baselines with visual instruction tuning

Reference 39

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This paper cites Llava-next: Im- proved reasoning, ocr, and world knowledge, 2024.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Llava-next: Im- proved reasoning, ocr, and world knowledge, 2024

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This paper cites Deep learning face attributes in the wild.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Deep learning face attributes in the wild

Reference 41

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Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Swin transformer: Hierarchical vision transformer using shifted windows

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This paper cites Torchvision: Py- torch’s computer vision library.https://github.com/ pytorch/vision, 2016.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Torchvision: Py- torch’s computer vision library.https://github.com/ pytorch/vision, 2016

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This paper cites A survey on bias and fairness in machine learning.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers A survey on bias and fairness in machine learning

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This paper cites Gemma: Open Models Based on Gemini Research and Technology.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Gemma: Open Models Based on Gemini Research and Technology

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This paper cites Chat markup language chatml (preview), 2024.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Chat markup language chatml (preview), 2024

Reference 46

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This paper cites Model cards for model reporting.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Model cards for model reporting

Reference 47

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This paper cites FaceXFormer: A Unified Transformer for Facial Analysis.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers FaceXFormer: A Unified Transformer for Facial Analysis

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This paper cites Dissecting racial bias in an algorithm used to manage the health of populations.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Dissecting racial bias in an algorithm used to manage the health of populations

Reference 49

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Observation 2e073045-9adc-4bd7-b8e3-9a568a7a6e5b · outbound

This paper cites Omiye, Jenna C.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Omiye, Jenna C

Reference 50

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Observation 3921b6e6-e396-441c-895c-e22b74e41ef7 · outbound

This paper cites Learn- ing transferable visual models from natural language super- vision.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Learn- ing transferable visual models from natural language super- vision

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This paper cites Sentence-bert: Sentence embeddings using siamese bert-networks.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Sentence-bert: Sentence embeddings using siamese bert-networks

Reference 52

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Observation fe017fe6-d124-4e00-84f5-cd4db3ed9b02 · outbound

This paper cites PRIME: Prioritizing interpretability in failure mode extraction.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers PRIME: Prioritizing interpretability in failure mode extraction

Reference 53

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This paper cites Berg, and Li Fei-Fei.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Berg, and Li Fei-Fei

Reference 54

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This paper cites Laion-5b: An open large-scale dataset for training next generation image-text models.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Laion-5b: An open large-scale dataset for training next generation image-text models

Reference 55

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This paper cites A multimodal automated interpretability agent.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers A multimodal automated interpretability agent

Reference 56

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This paper cites Fairrag: Fair human genera- tion via fair retrieval augmentation.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Fairrag: Fair human genera- tion via fair retrieval augmentation

Reference 57

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This paper cites Revisiting weakly supervised pre-training of visual perception models.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Revisiting weakly supervised pre-training of visual perception models

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:21:00.515164Z

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This paper cites Salient imagenet: How to discover spurious features in deep learning? In ICLR, 2022.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Salient imagenet: How to discover spurious features in deep learning? In ICLR, 2022

Reference 59

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This paper cites Understanding failures of deep networks via robust feature extraction.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Understanding failures of deep networks via robust feature extraction

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:21:00.490978Z

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

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers No subclass left behind: Fine- grained robustness in coarse-grained classification problems

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:21:00.479560Z

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This paper cites Winoground: Probing vision and language models for visio- linguistic compositionality.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Winoground: Probing vision and language models for visio- linguistic compositionality

Reference 62

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This paper cites When does dough become a bagel? analyzing the remaining mistakes on imagenet.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers When does dough become a bagel? analyzing the remaining mistakes on imagenet

Reference 63

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This paper cites Revise: A tool for measuring and mitigating bias in visual datasets.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Revise: A tool for measuring and mitigating bias in visual datasets

Reference 64

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This paper cites Dis- covering bugs in vision models using off-the-shelf image generation and captioning.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Dis- covering bugs in vision models using off-the-shelf image generation and captioning

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:21:00.438593Z

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This paper cites Sigmoid loss for language image pre-training.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Sigmoid loss for language image pre-training

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:21:00.427180Z

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This paper cites Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models

Reference 67

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This paper cites Discover and mitigate multiple biased subgroups in im- age classifiers.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Discover and mitigate multiple biased subgroups in im- age classifiers

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:21:00.415561Z

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This paper cites Under- standing and evaluating racial biases in image captioning.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Under- standing and evaluating racial biases in image captioning

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:21:00.403167Z

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This paper cites Men also like shopping: Reducing gender bias amplification using corpus-level constraints.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Men also like shopping: Reducing gender bias amplification using corpus-level constraints

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:21:00.391804Z

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This paper cites Language-guided Detection and Mitigation of Unknown Dataset Bias.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Language-guided Detection and Mitigation of Unknown Dataset Bias

Reference 71

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Observation 04532ca3-caf7-49c7-858c-7ec58ff7dd98 · outbound

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Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Unresolved cited work

Reference 72

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Observation 28e55cd4-f850-404e-94b4-0a7ac7531efa · outbound

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Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers Unresolved cited work

Reference 73

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This paper cites bias attribute.

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers bias attribute

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:21:00.356126Z

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