55 citations · 69 across the 7 of their papers we have counts for
7 papers
Bidirectional Context Self-Distillation for Reinforcement Learning of Skill-Based LLM Agents
Tianjun Pan, Yuan Li, Hongda Wang +8
External natural-language skills provide large language model (LLM) agents with reusable and editable guidance for solving complex tasks. Yet their effectiveness depends not only o…
Good Actions Succeed, Bad Actions Generalize: A Case Study on Why RL Generalizes Better
Meng Song
Supervised learning (SL) and reinforcement learning (RL) are both widely used to train general-purpose agents for complex tasks, yet their generalization capabilities and underlyin…
A Minimalist Prompt for Zero-Shot Policy Learning
Meng Song, Xuezhi Wang, Tanay Biradar +2
Transformer-based methods have exhibited significant generalization ability when prompted with target-domain demonstrations or example solutions during inference. Although demonstr…
Probabilistic World Modeling with Asymmetric Distance Measure
Meng Song
Representation learning is a fundamental task in machine learning, aiming at uncovering structures from data to facilitate subsequent tasks. However, what is a good representation…
Learning to Rearrange with Physics-Inspired Risk Awareness
Meng Song, Yuhan Liu, Zhengqin Li +1
Real-world applications require a robot operating in the physical world with awareness of potential risks besides accomplishing the task. A large part of risky behaviors arises fro…
RLPrompt: Optimizing Discrete Text Prompts with Reinforcement Learning
Mingkai Deng, Jianyu Wang, Cheng-Ping Hsieh +6
Prompting has shown impressive success in enabling large pretrained language models (LMs) to perform diverse NLP tasks, especially when only few downstream data are available. Auto…
S4G: Amodal Single-view Single-Shot SE(3) Grasp Detection in Cluttered Scenes
Yuzhe Qin, Rui Chen, Hao Zhu +3
Grasping is among the most fundamental and long-lasting problems in robotics study. This paper studies the problem of 6-DoF(degree of freedom) grasping by a parallel gripper in a c…