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We propose the reasoning MLLM, Vision-R1, to improve multimodal reasoning capability. Specifically, we first construct a high-quality multimodal CoT dataset ...

This work introduces a transparent, from-scratch framework for RL in VLMs, offering a minimal yet functional four-step pipeline validated across multiple ...

In this article, we apply interpretability techniques to a reinforcement learning (RL) model trained to play the video game CoinRun.

This is a collection of research papers on Visual Reinforcement Learning (Visual RL) and other vision-related reinforcement learning.

This is the first paper to explore how to effectively use RL for MLLMs and introduce Vision-R1, a reasoning MLLM that leverages cold-start initialization and ...

In this paper, we apply Reinforcement Learning (RL) to control a manipulator using camera images. Basically, RL algorithm helps the agent to choose actions ...

Generalizing vision-based reinforcement learning (RL) agents to novel environments remains a difficult and open challenge.

Proceedings of the 41st International Conference on Machine Learning, PMLR 235:51484-51501, 2024. Abstract. Reward engineering has long been a challenge in ...

Find & Replace on steroids! This versatile automation utility processes each line according to rules you set. Works on text files and Word/Excel docs. More ...