5 papers
TALES: Text Adventure Learning Environment Suite
Christopher Zhang Cui, Xingdi Yuan, Ziang Xiao +2
Reasoning is an essential skill to enable Large Language Models (LLMs) to interact with the world. As tasks become more complex, they demand increasingly sophisticated and diverse…
debug-gym: A Text-Based Environment for Interactive Debugging
Xingdi Yuan, Morgane M Moss, Charbel El Feghali +8
Large Language Models (LLMs) are increasingly relied upon for coding tasks, yet in most scenarios it is assumed that all relevant information can be either accessed in context or m…
Enhancing Agent Learning through World Dynamics Modeling
Zhiyuan Sun, Haochen Shi, Marc-Alexandre Côté +3
Large language models (LLMs) have been increasingly applied to tasks in language understanding and interactive decision-making, with their impressive performance largely attributed…
Policy Improvement using Language Feedback Models
Victor Zhong, Dipendra Misra, Xingdi Yuan +1
We introduce Language Feedback Models (LFMs) that identify desirable behaviour - actions that help achieve tasks specified in the instruction - for imitation learning in instructio…
DISCOVERYWORLD: A Virtual Environment for Developing and Evaluating Automated Scientific Discovery Agents
Peter Jansen, Marc-Alexandre Côté, Tushar Khot +5
Automated scientific discovery promises to accelerate progress across scientific domains. However, developing and evaluating an AI agent's capacity for end-to-end scientific reason…