Multi-agent interactions, such as communication, teaching, and bluffing,...
Policies often fail due to distribution shift – changes in the state and...
Large Language Models (LLMs) have demonstrated impressive planning abili...
While large language models (LMs) have shown remarkable capabilities acr...
In this work, we study how to build socially intelligent robots to assis...
In this work, we consider one-shot imitation learning for object
rearran...
In cooperative multi-agent reinforcement learning, a team of agents work...
Prompting has shown impressive success in enabling large pretrained lang...
In Multi-Agent Reinforcement Learning (MARL), specialized channels are o...
Much of what we do as humans is engage socially with other agents, a ski...
Aligning humans' assessment of what a robot can do with its true capabil...
The ability to perceive and reason about social interactions in the cont...
For machine agents to successfully interact with humans in real-world
se...
In this paper, we introduce Watch-And-Help (WAH), a challenge for testin...
Human collaborators can effectively communicate with their partners to f...
Vision-language navigation (VLN) is the task of entailing an agent to ca...
One of the main challenges of advancing task-oriented learning such as v...
The ability of modeling the other agents, such as understanding their
in...
Most of the prior work on multi-agent reinforcement learning (MARL) achi...
Learning policies for complex tasks that require multiple different skil...
This work is about recognizing human activities occurring in videos at
d...
In this paper, we present a general framework for learning social afford...
This paper is about detecting functional objects and inferring human
int...
In this paper, we present an approach for robot learning of social affor...