1 citations · 3 across the 9 of their papers we have counts for
9 papers
MTLight: Efficient Multi-Task Reinforcement Learning for Traffic Signal Control
Liwen Zhu, Peixi Peng, Zongqing Lu +1
Traffic signal control has a great impact on alleviating traffic congestion in modern cities. Deep reinforcement learning (RL) has been widely used for this task in recent years, d…
UV Gaussians: Joint Learning of Mesh Deformation and Gaussian Textures for Human Avatar Modeling
Yujiao Jiang, Qingmin Liao, Xiaoyu Li +5
Reconstructing photo-realistic drivable human avatars from multi-view image sequences has been a popular and challenging topic in the field of computer vision and graphics. While e…
UniCode: Learning a Unified Codebook for Multimodal Large Language Models
Sipeng Zheng, Bohan Zhou, Yicheng Feng +2
In this paper, we propose \textbf{UniCode}, a novel approach within the domain of multimodal large language models (MLLMs) that learns a unified codebook to efficiently tokenize vi…
SEABO: A Simple Search-Based Method for Offline Imitation Learning
Jiafei Lyu, Xiaoteng Ma, Le Wan +3
Offline reinforcement learning (RL) has attracted much attention due to its ability in learning from static offline datasets and eliminating the need of interacting with the enviro…
LLaMA Rider: Spurring Large Language Models to Explore the Open World
Yicheng Feng, Yuxuan Wang, Jiazheng Liu +2
Recently, various studies have leveraged Large Language Models (LLMs) to help decision-making and planning in environments, and try to align the LLMs' knowledge with the world cond…
Off-Policy RL Algorithms Can be Sample-Efficient for Continuous Control via Sample Multiple Reuse
Jiafei Lyu, Le Wan, Zongqing Lu +1
Sample efficiency is one of the most critical issues for online reinforcement learning (RL). Existing methods achieve higher sample efficiency by adopting model-based methods, Q-en…