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20242026
most citeddebug-gym: A Text-Based Environment for Interactive Debugging

1 citations · 3 across the 15 of their papers we have counts for

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cs.AI2024

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…

cs.CL2024

Can Language Models Serve as Text-Based World Simulators?

Ruoyao Wang, Graham Todd, Ziang Xiao +4

Virtual environments play a key role in benchmarking advances in complex planning and decision-making tasks but are expensive and complicated to build by hand. Can current language…

cs.AI2024★ 1 cited

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…

cs.LG2024

Language-guided Skill Learning with Temporal Variational Inference

Haotian Fu, Pratyusha Sharma, Elias Stengel-Eskin +4

We present an algorithm for skill discovery from expert demonstrations. The algorithm first utilizes Large Language Models (LLMs) to propose an initial segmentation of the trajecto…

cs.LG2024★ 1 cited

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…