4 citations · 13 across the 14 of their papers we have counts for
14 papers
BookAsSumQA: An Evaluation Framework for Aspect-Based Book Summarization via Question Answering
Ryuhei Miyazato, Ting-Ruen Wei, Xuyang Wu +2
Aspect-based summarization aims to generate summaries that highlight specific aspects of a text, enabling more personalized and targeted summaries. However, its application to book…
A Survey on Feedback-based Multi-step Reasoning for Large Language Models on Mathematics
Ting-Ruen Wei, Haowei Liu, Xuyang Wu +1
Recent progress in large language models (LLM) found chain-of-thought prompting strategies to improve the reasoning ability of LLMs by encouraging problem solving through multiple…
Does Reasoning Introduce Bias? A Study of Social Bias Evaluation and Mitigation in LLM Reasoning
Xuyang Wu, Jinming Nian, Ting-Ruen Wei +3
Recent advances in large language models (LLMs) have enabled automatic generation of chain-of-thought (CoT) reasoning, leading to strong performance on tasks such as math and code.…
CLERF: Contrastive LEaRning for Full Range Head Pose Estimation
Ting-Ruen Wei, Haowei Liu, Huei-Chung Hu +3
We introduce a novel framework for representation learning in head pose estimation (HPE). Previously such a scheme was difficult due to head pose data sparsity, making triplet samp…
RaCT: Ranking-aware Chain-of-Thought Optimization for LLMs
Haowei Liu, Xuyang Wu, Guohao Sun +2
In information retrieval, large language models (LLMs) have demonstrated remarkable potential in text reranking tasks by leveraging their sophisticated natural language understandi…
Meta Learning to Rank for Sparsely Supervised Queries
Xuyang Wu, Ajit Puthenputhussery, Hongwei Shang +2
Supervisory signals are a critical resource for training learning to rank models. In many real-world search and retrieval scenarios, these signals may not be readily available or c…
Does RAG Introduce Unfairness in LLMs? Evaluating Fairness in Retrieval-Augmented Generation Systems
Xuyang Wu, Shuowei Li, Hsin-Tai Wu +2
Retrieval-Augmented Generation (RAG) has recently gained significant attention for its enhanced ability to integrate external knowledge sources into open-domain question answering…
Full-range Head Pose Geometric Data Augmentations
Huei-Chung Hu, Xuyang Wu, Haowei Liu +2
Many head pose estimation (HPE) methods promise the ability to create full-range datasets, theoretically allowing the estimation of the rotation and positioning of the head from va…
Passage-specific Prompt Tuning for Passage Reranking in Question Answering with Large Language Models
Xuyang Wu, Zhiyuan Peng, Krishna Sravanthi Rajanala Sai +2
Effective passage retrieval and reranking methods have been widely utilized to identify suitable candidates in open-domain question answering tasks, recent studies have resorted to…
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…
HPE-CogVLM: Advancing Vision Language Models with a Head Pose Grounding Task
Yu Tian, Tianqi Shao, Tsukasa Demizu +2
Head pose estimation (HPE) requires a sophisticated understanding of 3D spatial relationships to generate precise yaw, pitch, and roll angles. Previous HPE models, primarily CNN-ba…
Q-PEFT: Query-dependent Parameter Efficient Fine-tuning for Text Reranking with Large Language Models
Zhiyuan Peng, Xuyang Wu, Qifan Wang +2
Parameter Efficient Fine-Tuning (PEFT) methods have been extensively utilized in Large Language Models (LLMs) to improve the down-streaming tasks without the cost of fine-tuing the…
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…