1 citations · 4 across the 7 of their papers we have counts for
8 papers
Survival Games: Human-LLM Strategic Showdowns under Severe Resource Scarcity
Zhihong Chen, Yiqian Yang, Jinzhao Zhou +3
The rapid advancement of large language models (LLMs) raises critical concerns about their ethical alignment, particularly in scenarios where human and AI co-exist under the confli…
EmbodiedVSR: Dynamic Scene Graph-Guided Chain-of-Thought Reasoning for Visual Spatial Tasks
Yi Zhang, Qiang Zhang, Xiaozhu Ju +13
While multimodal large language models (MLLMs) have made groundbreaking progress in embodied intelligence, they still face significant challenges in spatial reasoning for complex l…
NeuGPT: Unified multi-modal Neural GPT
Yiqian Yang, Yiqun Duan, Hyejeong Jo +6
This paper introduces NeuGPT, a groundbreaking multi-modal language generation model designed to harmonize the fragmented landscape of neural recording research. Traditionally, stu…
E2H: A Two-Stage Non-Invasive Neural Signal Driven Humanoid Robotic Whole-Body Control Framework
Yiqun Duan, Qiang Zhang, Jinzhao Zhou +9
Recent advancements in humanoid robotics, including the integration of hierarchical reinforcement learning-based control and the utilization of LLM planning, have significantly enh…
Prompting Multi-Modal Tokens to Enhance End-to-End Autonomous Driving Imitation Learning with LLMs
Yiqun Duan, Qiang Zhang, Renjing Xu
The utilization of Large Language Models (LLMs) within the realm of reinforcement learning, particularly as planners, has garnered a significant degree of attention in recent schol…
NeuSpeech: Decode Neural signal as Speech
Yiqian Yang, Yiqun Duan, Qiang Zhang +5
Decoding language from brain dynamics is an important open direction in the realm of brain-computer interface (BCI), especially considering the rapid growth of large language model…
Whole-body Humanoid Robot Locomotion with Human Reference
Qiang Zhang, Peter Cui, David Yan +8
Recently, humanoid robots have made significant advances in their ability to perform challenging tasks due to the deployment of Reinforcement Learning (RL), however, the inherent c…
Prompt, Plan, Perform: LLM-based Humanoid Control via Quantized Imitation Learning
Jingkai Sun, Qiang Zhang, Yiqun Duan +3
In recent years, reinforcement learning and imitation learning have shown great potential for controlling humanoid robots' motion. However, these methods typically create simulatio…