2 papers
cs.AI2026
Auditing evaluation artifacts and data leakage in large language model systems for rare disease diagnosis
Jian Yang, Peilin Liu, Xiaohan Li +4
Augmented large language model (LLM) systems have reported high benchmark accuracies in rare disease diagnosis, yet their real-world clinical utility remains unproven. A recent met…
cs.CV2024
Think Before You Act: A Two-Stage Framework for Mitigating Gender Bias Towards Vision-Language Tasks
Yunqi Zhang, Songda Li, Chunyuan Deng +2
Gender bias in vision-language models (VLMs) can reinforce harmful stereotypes and discrimination. In this paper, we focus on mitigating gender bias towards vision-language tasks.…