1 citations · 1 across the 3 of their papers we have counts for
5 papers
Beyond Output Critique: Self-Correction via Task Distillation
Hossein A. Rahmani, Mengting Wan, Pei Zhou +4
Large language models (LLMs) have shown promising self-correction abilities, where iterative refinement improves the quality of generated responses. However, most existing approach…
Teaching Language Models To Gather Information Proactively
Tenghao Huang, Sihao Chen, Muhao Chen +4
Large language models (LLMs) are increasingly expected to function as collaborative partners, engaging in back-and-forth dialogue to solve complex, ambiguous problems. However, cur…
Group Preference Alignment: Customized LLM Response Generation from In-Situ Conversations
Ishani Mondal, Jack W. Stokes, Sujay Kumar Jauhar +5
LLMs often fail to meet the specialized needs of distinct user groups due to their one-size-fits-all training paradigm \cite{lucy-etal-2024-one} and there is limited research on wh…
GenTool: Enhancing Tool Generalization in Language Models through Zero-to-One and Weak-to-Strong Simulation
Jie He, Jennifer Neville, Mengting Wan +6
Large Language Models (LLMs) can enhance their capabilities as AI assistants by integrating external tools, allowing them to access a wider range of information. While recent LLMs…
Corporate Communication Companion (CCC): An LLM-empowered Writing Assistant for Workplace Social Media
Zhuoran Lu, Sheshera Mysore, Tara Safavi +3
Workplace social media platforms enable employees to cultivate their professional image and connect with colleagues in a semi-formal environment. While semi-formal corporate commun…