9 citations · 9 across the 2 of their papers we have counts for
4 papers
FRoM-W1: Towards General Humanoid Whole-Body Control with Language Instructions
Peng Li, Zihan Zhuang, Yangfan Gao +16
Humanoid robots are capable of performing various actions such as greeting, dancing and even backflipping. However, these motions are often hard-coded or specifically trained, whic…
MANGO: A Benchmark for Evaluating Mapping and Navigation Abilities of Large Language Models
Peng Ding, Jiading Fang, Peng Li +6
Large language models such as ChatGPT and GPT-4 have recently achieved astonishing performance on a variety of natural language processing tasks. In this paper, we propose MANGO, a…
Statler: State-Maintaining Language Models for Embodied Reasoning
Takuma Yoneda, Jiading Fang, Peng Li +7
There has been a significant research interest in employing large language models to empower intelligent robots with complex reasoning. Existing work focuses on harnessing their ab…
CodeIE: Large Code Generation Models are Better Few-Shot Information Extractors
Peng Li, Tianxiang Sun, Qiong Tang +4
Large language models (LLMs) pre-trained on massive corpora have demonstrated impressive few-shot learning ability on many NLP tasks. A common practice is to recast the task into a…