1 citations · 1 across the 3 of their papers we have counts for
15 papers
HindSearch: Trajectory-Level Hindsight Critique for Search-Augmented Reinforcement Learning
Haowei Liu, Jiamian Wang, Hsin-Tai Wu +2
Search-augmented LM agents are typically trained with a binary exact-match reward, which throws away most of what a failed trajectory tells us about why it failed. We introduce Hin…
ReliableTableQA:How Much Supervision Does Reliability Annotation Need?
Huei-Chung Hu, Hsin-Tai Wu, Koyo Kobayashi
We introduce ReliableTableQA, a framework for training an LLM to annotate the statistical reliability of tabular QA results, not whether the query is answerable, but whether the co…
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…
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…
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.…
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…