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20242026
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cs.CL2026

Beyond Local vs. External: A Game-Theoretic Framework for Trustworthy Knowledge Acquisition

Rujing Yao, Yufei Shi, Yang Wu +5

Cloud-hosted Large Language Models (LLMs) offer unmatched reasoning capabilities and dynamic knowledge, yet submitting raw queries to these external services risks exposing sensiti…

cs.CL2026

"Excuse me, may I say something..." CoLabScience, A Proactive AI Assistant for Biomedical Discovery and LLM-Expert Collaborations

Yang Wu, Jinhong Yu, Jingwei Xiong +2

The integration of Large Language Models (LLMs) into scientific workflows presents exciting opportunities to accelerate biomedical discovery. However, the reactive nature of LLMs,…

cs.CL2025

Teaching According to Students' Aptitude: Personalized Mathematics Tutoring via Persona-, Memory-, and Forgetting-Aware LLMs

Yang Wu, Rujing Yao, Tong Zhang +4

Large Language Models (LLMs) are increasingly integrated into intelligent tutoring systems to provide human-like and adaptive instruction. However, most existing approaches fail to…

cs.CL2025

Elevating Legal LLM Responses: Harnessing Trainable Logical Structures and Semantic Knowledge with Legal Reasoning

Rujing Yao, Yang Wu, Chenghao Wang +3

Large Language Models (LLMs) have achieved impressive results across numerous domains, yet they experience notable deficiencies in legal question-answering tasks. LLMs often genera…

cs.CL2025

Intelligent Legal Assistant: An Interactive Clarification System for Legal Question Answering

Rujing Yao, Yiquan Wu, Tong Zhang +7

The rise of large language models has opened new avenues for users seeking legal advice. However, users often lack professional legal knowledge, which can lead to questions that om…

cs.CL2024

Knowledge-Infused Legal Wisdom: Navigating LLM Consultation through the Lens of Diagnostics and Positive-Unlabeled Reinforcement Learning

Yang Wu, Chenghao Wang, Ece Gumusel +1

The integration of generative Large Language Models (LLMs) into various applications, including the legal domain, has been accelerated by their expansive and versatile nature. Howe…