Papers by Dmitriy Lukashevskiy

1 papers
Self-Guided Plan Extraction for Instruction-Following Tasks with Goal-Conditional Reinforcement Learning (2026.findings-acl)

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Challenge: a framework for instruction-following tasks is proposed for instruction following tasks . previous methods rely on expert trajectories and learn directly from the agent's own interactions with the environment without expert supervision.
Approach: They propose a framework for instruction-following tasks that enables a language model to generate and refine high-level plans through a self-learning mechanism.
Outcome: The proposed framework adheres to instructions more strictly than baseline methods while showing strong generalization to previously unseen instructions.

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