demographic bia

ALPHA: Action-Based Learning for Pluralistic Human Alignment in Large Language Models AAAI 2026 Ask Me Again Differently: GRAS for Measuring Bias in Vision Language Models on Gender, Race, Age, and Skin Tone EACL 2026 Bias at the End of the Score CVPR 2026 Bias Is a Subspace, Not a Coordinate: A Geometric Rethinking of Post-hoc Debiasing in Vision-Language Models CVPR 2026 Decoupling Bias, Aligning Distributions: Synergistic Fairness Optimization for Deepfake Detection CVPR 2026 Evaluating the Impact of Medical Image Reconstruction on Downstream AI Fairness and Performance MIDL 2026 FairVLM: Enhancing Fairness and Prompt Sensitivity in Vision Language Models for Medical Image Segmentation WACV 2026 Identifying Bias in Machine-generated Text Detection ACL 2026 Identity-Robust Language Model Generation via Content Integrity Preservation ACL 2026 On the Interplay between Human Label Variation and Model Fairness EACL 2026 Operationalizing Pluralistic Values in Large Language Model Alignment Reveals Trade-offs in Safety, Inclusivity, and Model Behavior AAAI 2026 Thesis Proposal: Auditing and Mitigating Demographic Bias in Multi-Stage Retrieval Systems for Criminal Justice Applications ACL 2026 AI-Face: A Million-Scale Demographically Annotated AI-Generated Face Dataset and Fairness Benchmark CVPR 2025 An Analysis of Large Language Models for Simulating User Responses in Surveys IJCNLP 2025 A Rapid Test for Accuracy and Bias of Face Recognition Technology WACV 2025 Are LLMs Empathetic to All? Investigating the Influence of Multi-Demographic Personas on a Model’s Empathy EMNLP 2025 Assessing the Reliability of LLMs Annotations in the Context of Demographic Bias and Model Explanation ACL 2025 Auditing Political Bias in Text Generation by GPT-4 using Sociocultural and Demographic Personas: Case of Bengali Ethnolinguistic Communities AACL 2025 Bidirectional Human–AI Collaboration for Equitable Student Performance Prediction via Deep Uncertainty Learning IJCAI 2025 Building Trust in Clinical LLMs: Bias Analysis and Dataset Transparency EMNLP 2025 Disentangling Biased Representations: A Causal Intervention Framework for Fairer NLP Models ACL 2025 Elucidating Mechanisms of Demographic Bias in LLMs for Healthcare EMNLP 2025 Evaluating AI for Finance: Is AI Credible at Assessing Investment Risk Appetite? EMNLP 2025 Evaluating Fairness in Large Vision-Language Models Across Diverse Demographic Attributes and Prompts EMNLP 2025 Evaluating Human Perception and Bias in AI-Generated Humor COLING 2025