Bias Detection
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Benchmarks
StereoSet
rt-inod-bias
ICAT LLM bias
PlantVillage_8px
Wiki Neutrality Corpus
Most implemented
StereoSet: Measuring stereotypical bias in pretrained language models
Investigating Subtler Biases in LLMs: Ageism, Beauty, Institutional, and Nationality Bias in Generative Models
Detecting Emergent Intersectional Biases: Contextualized Word Embeddings Contain a Distribution of Human-like Biases
Automated Dependence Plots
Papers
Reference-Based Bias Detection in LLMs via Relative Representations of Hidden States
Existing bias auditing methods typically rely on model outputs, requiring costly benchmarks or judge models and potentially missing internal shifts that never appear in generated text. We propose a reference-based method…
Bias DetectionDefinitional Sensitivity in Media Bias Detection: A Multi-Definition Dataset and Benchmark
Media bias detection relies on definitions and examples that specify what counts as bias, yet these specifications often vary across datasets or remain implicit, even when given the same name. Such variation makes it unc…
Bias DetectionBiasTrace: Linking Reasoning Behaviours to Biased Outputs in LLMs
LLMs exhibit social biases that can produce inaccurate and discriminatory inferences, posing risks in high-stakes applications. While prior work has made progress in measuring and mitigating bias, it largely focuses on f…
Bias DetectionChallenges in Evaluating Explanation Methods for Static and Evolving Data
This paper addresses the limitations of Explainable Artificial Intelligence (XAI) with respect to insufficient evaluation. They are illustrated through the DetoxAI image recognition system for bias detection and concept …
Image ClassificationBias DetectionA Multi-Dimensional Evaluation of Explainability in Media Bias Detection
Detecting media bias automatically is difficult because biased framing is often subtle, yet in domains such as news analysis, accurate predictions alone are insufficient without explanations that reflect the model's unde…
Bias DetectionDemographically-Conditioned Synthetic Medical Images for Bias Mitigation and Bias Detection in Disease Classifiers
Per-subgroup fairness audits of medical image classifiers face a sample-size problem: minority subgroups in held-out test sets have so few samples that the resulting confidence intervals on per-subgroup performance are w…
Bias Detection