1 citations · 1 across the 5 of their papers we have counts for
5 papers
A Heuristic Perspective on Debiasing Language Models
Tian Lan, Yemin Wang, Chuancheng Shi +6
Language models (LMs) often acquire various biases during pre-training and may express them in interactions, potentially causing social harm. Existing methods often rely on counter…
Table Transformers for Imputing Textual Attributes
Ting-Ruen Wei, Yuan Wang, Yoshitaka Inoue +2
Missing data in tabular dataset is a common issue as the performance of downstream tasks usually depends on the completeness of the training dataset. Previous missing data imputati…
Evaluating Fairness in Large Vision-Language Models Across Diverse Demographic Attributes and Prompts
Xuyang Wu, Yuan Wang, Hsin-Tai Wu +2
Large vision-language models (LVLMs) have recently achieved significant progress, demonstrating strong capabilities in open-world visual understanding. However, it is not yet clear…
Do Large Language Models Rank Fairly? An Empirical Study on the Fairness of LLMs as Rankers
Yuan Wang, Xuyang Wu, Hsin-Tai Wu +2
The integration of Large Language Models (LLMs) in information retrieval has raised a critical reevaluation of fairness in the text-ranking models. LLMs, such as GPT models and Lla…
Mathematical Foundation and Corrections for Full Range Head Pose Estimation
Huei-Chung Hu, Xuyang Wu, Yuan Wang +2
Numerous works concerning head pose estimation (HPE) offer algorithms or proposed neural network-based approaches for extracting Euler angles from either facial key points or direc…