Papers with Markov Decision Processes

2 papers
lilGym: Natural Language Visual Reasoning with Reinforcement Learning (2023.acl-long)

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Challenge: Existing approaches to language-conditioned reinforcement learning in visual environments are limited by language semantics.
Approach: They propose a new benchmark for language-conditioned reinforcement learning in visual environments . they annotate 2,661 highly-compositional human-written natural language statements .
Outcome: The proposed approach is based on 2,661 highly-compositional human-written natural language statements grounded in an interactive visual environment.
NaviMaster: Learning a Unified Policy for GUI and Embodied Navigation Tasks (2026.acl-long)

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Challenge: Recent advances in Graphical User Interface (GUI) and embodied navigation have driven progress, yet these domains have largely evolved in isolation, with disparate datasets and training paradigms.
Approach: They propose a visual-target trajectory collection pipeline that generates trajectories for GUI and embodied tasks using a single formulation.
Outcome: The proposed agent outperforms state-of-the-art agents in GUI navigation, spatial affordance prediction, and embodied navigation.

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