societal bia

CoBia: Constructed Conversations Can Trigger Otherwise Concealed Societal Biases in LLMs EMNLP 2025 Fine-Tuned LLMs are “Time Capsules” for Tracking Societal Bias Through Books NAACL 2025 KLAAD: Refining Attention Mechanisms to Reduce Societal Bias in Generative Language Models EMNLP 2025 LOTUS: A Leaderboard for Detailed Image Captioning from Quality to Societal Bias and User Preferences ACL 2025 Measuring Bias and Agreement in Large Language Model Presupposition Judgments ACL 2025 Red-Teaming for Uncovering Societal Bias in Large Language Models ACL 2025 SANER: Annotation-free Societal Attribute Neutralizer for Debiasing CLIP ICLR 2025 Towards Region-aware Bias Evaluation Metrics NAACL 2025 Analyzing Occupational Distribution Representation in Japanese Language Models COLING 2024 A Unified Framework and Dataset for Assessing Societal Bias in Vision-Language Models EMNLP 2024 BendVLM: Test-Time Debiasing of Vision-Language Embeddings NeurIPS 2024 CBBQ: A Chinese Bias Benchmark Dataset Curated with Human-AI Collaboration for Large Language Models COLING 2024 MAFIA: Multi-Adapter Fused Inclusive Language Models EACL 2024 Resampled Datasets Are Not Enough: Mitigating Societal Bias Beyond Single Attributes EMNLP 2024 An Empirical Study of Metrics to Measure Representational Harms in Pre-Trained Language Models ACL 2023 Debiasing Pretrained Generative Models by Uniformly Sampling Semantic Attributes NeurIPS 2023 In-Depth Look at Word Filling Societal Bias Measures EACL 2023 Uncurated Image-Text Datasets: Shedding Light on Demographic Bias CVPR 2023 Analyzing the Limits of Self-Supervision in Handling Bias in Language EMNLP 2022 A Prompt Array Keeps the Bias Away: Debiasing Vision-Language Models with Adversarial Learning AACL 2022 On Measures of Biases and Harms in NLP AACL 2022 Quantifying Societal Bias Amplification in Image Captioning CVPR 2022 RedditBias: A Real-World Resource for Bias Evaluation and Debiasing of Conversational Language Models ACL 2021 Societal Biases in Language Generation: Progress and Challenges ACL 2021 Towards a Comprehensive Understanding and Accurate Evaluation of Societal Biases in Pre-Trained Transformers NAACL 2021