works on

From the 1 of 7 linked papers with an AI index.

collaborators

7 papers

cs.CY2026

Digital Engagement, Income Disparities, and Job Seeking in the United States since 2010

Shaolong Wu, Yijiang River Dong, Siming He

The paper analyzes U.S. survey data to show that people who use the internet daily earn more and are more likely to be continuously employed than those who use it less or not at al…

cs.CL2026

Confidence Estimation for LLMs in Multi-turn Interactions

Caiqi Zhang, Ruihan Yang, Xiaochen Zhu +5

While confidence estimation is a promising direction for mitigating hallucinations in Large Language Models (LLMs), current research overwhelmingly focuses on single-turn settings.…

cs.CR2026

Privacy-R1: Privacy-Aware Multi-LLM Agent Collaboration via Reinforcement Learning

Zheng Hui, Yijiang River Dong, Sanhanat Sivapiromrat +2

When users submit queries to Large Language Models (LLMs), their prompts can often contain sensitive data, forcing a difficult choice: Send the query to a powerful proprietary LLM…

cs.CL2026

Value of Information: A Framework for Human-Agent Communication

Yijiang River Dong, Tiancheng Hu, Zheng Hui +4

Large Language Model (LLM) agents deployed for real-world tasks face a fundamental dilemma: user requests are underspecified, yet agents must decide whether to act on incomplete in…

cs.CL2026

Steer Model beyond Assistant: Controlling System Prompt Strength via Contrastive Decoding

Yijiang River Dong, Tiancheng Hu, Zheng Hui +1

Large language models excel at complex instructions yet struggle to deviate from their helpful assistant persona, as post-training instills strong priors that resist conflicting in…

cs.CL2025

When Personalization Meets Reality: A Multi-Faceted Analysis of Personalized Preference Learning

Yijiang River Dong, Tiancheng Hu, Yinhong Liu +2

While Reinforcement Learning from Human Feedback (RLHF) is widely used to align Large Language Models (LLMs) with human preferences, it typically assumes homogeneous preferences ac…