3 citations · 4 across the 10 of their papers we have counts for
5 papers · 1 filter
Communication and Verification in LLM Agents towards Collaboration under Information Asymmetry
Run Peng, Ziqiao Ma, Amy Pang +5
While Large Language Model (LLM) agents are often approached from the angle of action planning/generation to accomplish a goal (e.g., given by language descriptions), their abiliti…
The Mechanistic Emergence of Symbol Grounding in Language Models
Shuyu Wu, Ziqiao Ma, Xiaoxi Luo +4
Symbol grounding (Harnad, 1990) describes how symbols such as words acquire their meanings by connecting to real-world sensorimotor experiences. Recent work has shown preliminary e…
AimBot: A Simple Auxiliary Visual Cue to Enhance Spatial Awareness of Visuomotor Policies
Yinpei Dai, Jayjun Lee, Yichi Zhang +6
In this paper, we propose AimBot, a lightweight visual augmentation technique that provides explicit spatial cues to improve visuomotor policy learning in robotic manipulation. Aim…
Vision-Language Models Are Not Pragmatically Competent in Referring Expression Generation
Ziqiao Ma, Jing Ding, Xuejun Zhang +6
Referring Expression Generation (REG) is a core task for evaluating the pragmatic competence of vision-language systems, requiring not only accurate semantic grounding but also adh…
Training Turn-by-Turn Verifiers for Dialogue Tutoring Agents: The Curious Case of LLMs as Your Coding Tutors
Jian Wang, Yinpei Dai, Yichi Zhang +3
Intelligent tutoring agents powered by large language models (LLMs) have been increasingly explored to deliver personalized knowledge in areas such as language learning and science…