10 citations · 15 across the 10 of their papers we have counts for
10 papers · 1 filter
Simply Stabilizing the Loop via Fully Looped Transformer
Rao Fu, Zixuan Yang, Jiankun Zhang +4
Scaling model performance typically requires increasing model size. Looped Transformer offers a compelling alternative by iteratively reusing the same Transformer blocks, trading a…
Decision Flow Policy Optimization
Jifeng Hu, Sili Huang, Siyuan Guo +6
In recent years, generative models have shown remarkable capabilities across diverse fields, including images, videos, language, and decision-making. By applying powerful generativ…
Analytic Energy-Guided Policy Optimization for Offline Reinforcement Learning
Jifeng Hu, Sili Huang, Zhejian Yang +6
Conditional decision generation with diffusion models has shown powerful competitiveness in reinforcement learning (RL). Recent studies reveal the relation between energy-function-…
Solving Continual Offline RL through Selective Weights Activation on Aligned Spaces
Jifeng Hu, Sili Huang, Li Shen +7
Continual offline reinforcement learning (CORL) has shown impressive ability in diffusion-based lifelong learning systems by modeling the joint distributions of trajectories. Howev…
Continual Diffuser (CoD): Mastering Continual Offline Reinforcement Learning with Experience Rehearsal
Jifeng Hu, Li Shen, Sili Huang +5
Artificial neural networks, especially recent diffusion-based models, have shown remarkable superiority in gaming, control, and QA systems, where the training tasks' datasets are u…
DS-Agent: Automated Data Science by Empowering Large Language Models with Case-Based Reasoning
Siyuan Guo, Cheng Deng, Ying Wen +3
In this work, we investigate the potential of large language models (LLMs) based agents to automate data science tasks, with the goal of comprehending task requirements, then build…