CLEAR-Bias

Dataset Card for CLEAR-Bias CLEAR-Bias (Corpus for Linguistic Evaluation of Adversarial Robustness against Bias) is a benchmark dataset designed to assess the robustness of large language models (LLMs) against bias elicitation, especially under adversarial conditions. It consists of carefully curated prompts that test

Papers using CLEAR-Bias (3)

Is Reasoning All You Need? Probing Bias in the Age of Reasoning Language Models2025Benchmarking Adversarial Robustness to Bias Elicitation in Large Language Models: Scalable Automated Assessment with LLM-as-a-Judge2025Shifting Perspectives: Steering Vectors for Robust Bias Mitigation in LLMs2025