4 citations · 5 across the 4 of their papers we have counts for
5 papers · 1 filter
IDAT: A Multi-Modal Dataset and Toolkit for Building and Evaluating Interactive Task-Solving Agents
Shrestha Mohanty, Negar Arabzadeh, Andrea Tupini +5
Seamless interaction between AI agents and humans using natural language remains a key goal in AI research. This paper addresses the challenges of developing interactive agents cap…
OPEx: A Component-Wise Analysis of LLM-Centric Agents in Embodied Instruction Following
Haochen Shi, Zhiyuan Sun, Xingdi Yuan +2
Embodied Instruction Following (EIF) is a crucial task in embodied learning, requiring agents to interact with their environment through egocentric observations to fulfill natural…
Augmenting Autotelic Agents with Large Language Models
Cédric Colas, Laetitia Teodorescu, Pierre-Yves Oudeyer +2
Humans learn to master open-ended repertoires of skills by imagining and practicing their own goals. This autotelic learning process, literally the pursuit of self-generated (auto)…
A Song of Ice and Fire: Analyzing Textual Autotelic Agents in ScienceWorld
Laetitia Teodorescu, Xingdi Yuan, Marc-Alexandre Côté +1
Building open-ended agents that can autonomously discover a diversity of behaviours is one of the long-standing goals of artificial intelligence. This challenge can be studied in t…
Automatic Exploration of Textual Environments with Language-Conditioned Autotelic Agents
Laetitia Teodorescu, Eric Yuan, Marc-Alexandre Côté +1
In this extended abstract we discuss the opportunities and challenges of studying intrinsically-motivated agents for exploration in textual environments. We argue that there is imp…