Search Results for author:
Found 7 papers, 5 papers with code
Agents: An Open-source Framework for Autonomous Language Agents
Recent advances on large language models (LLMs) enable researchers and developers to build autonomous language agents that can automatically solve various tasks and interact with environments, humans, and other agents using natural language interfaces.
Pre-training Contextualized World Models with In-the-wild Videos for Reinforcement Learning
To tackle this issue, we introduce Contextualized World Models (ContextWM) that explicitly model both the context and dynamics to overcome the complexity and diversity of in-the-wild videos and facilitate knowledge transfer between distinct scenes.
CLIPood: Generalizing CLIP to Out-of-Distributions
This paper aims at generalizing CLIP to out-of-distribution test data on downstream tasks.
Out-of-Dynamics Imitation Learning from Multimodal Demonstrations
Existing imitation learning works mainly assume that the demonstrator who collects demonstrations shares the same dynamics as the imitator.
Real-Time And Robust 3D Object Detection with Roadside LiDARs
This work aims to address the challenges in autonomous driving by focusing on the 3D perception of the environment using roadside LiDARs.
Flowformer: Linearizing Transformers with Conservation Flows
By respectively conserving the incoming flow of sinks for source competition and the outgoing flow of sources for sink allocation, Flow-Attention inherently generates informative attentions without using specific inductive biases.
Supported Policy Optimization for Offline Reinforcement Learning
Policy constraint methods to offline reinforcement learning (RL) typically utilize parameterization or regularization that constrains the policy to perform actions within the support set of the behavior policy.
