7 citations · 13 across the 6 of their papers we have counts for
6 papers
Long-Horizon Dialogue Understanding for Role Identification in the Game of Avalon with Large Language Models
Simon Stepputtis, Joseph Campbell, Yaqi Xie +6
Deception and persuasion play a critical role in long-horizon dialogues between multiple parties, especially when the interests, goals, and motivations of the participants are not…
Explaining Agent Behavior with Large Language Models
Xijia Zhang, Yue Guo, Simon Stepputtis +2
Intelligent agents such as robots are increasingly deployed in real-world, safety-critical settings. It is vital that these agents are able to explain the reasoning behind their de…
Knowledge-Guided Short-Context Action Anticipation in Human-Centric Videos
Sarthak Bhagat, Simon Stepputtis, Joseph Campbell +1
This work focuses on anticipating long-term human actions, particularly using short video segments, which can speed up editing workflows through improved suggestions while fosterin…
Theory of Mind as Intrinsic Motivation for Multi-Agent Reinforcement Learning
Ini Oguntola, Joseph Campbell, Simon Stepputtis +1
The ability to model the mental states of others is crucial to human social intelligence, and can offer similar benefits to artificial agents with respect to the social dynamics in…
Concept Learning for Interpretable Multi-Agent Reinforcement Learning
Renos Zabounidis, Joseph Campbell, Simon Stepputtis +2
Multi-agent robotic systems are increasingly operating in real-world environments in close proximity to humans, yet are largely controlled by policy models with inscrutable deep ne…
A System for Imitation Learning of Contact-Rich Bimanual Manipulation Policies
Simon Stepputtis, Maryam Bandari, Stefan Schaal +1
In this paper, we discuss a framework for teaching bimanual manipulation tasks by imitation. To this end, we present a system and algorithms for learning compliant and contact-rich…