1 citations · 1 across the 6 of their papers we have counts for
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cs.AI2026
ART: Adaptive Reasoning Trees for Explainable Claim Verification
Sahil Wadhwa, Himanshu Kumar, Guanqun Yang +4
Large Language Models (LLMs) are powerful candidates for complex decision-making, leveraging vast encoded knowledge and remarkable zero-shot abilities. However, their adoption in h…
cs.AI2024
Infer Human's Intentions Before Following Natural Language Instructions
Yanming Wan, Yue Wu, Yiping Wang +2
For AI agents to be helpful to humans, they should be able to follow natural language instructions to complete everyday cooperative tasks in human environments. However, real human…
cs.AI2023★ 1 cited
Open-Ended Instructable Embodied Agents with Memory-Augmented Large Language Models
Gabriel Sarch, Yue Wu, Michael J. Tarr +1
Pre-trained and frozen large language models (LLMs) can effectively map simple scene rearrangement instructions to programs over a robot's visuomotor functions through appropriate…