AI & ML interests
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Papers
WideSeek-R1: Exploring Width Scaling for Broad Information Seeking via Multi-Agent Reinforcement Learning
$π_\texttt{RL}$: Online RL Fine-tuning for Flow-based Vision-Language-Action Models
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RLinf/RLinf-OpenVLAOFT-LIBERO-130-Base-Lora
Reinforcement Learning • 8B • Updated • 280 -
RLinf/RLinf-OpenVLAOFT-ManiSkill-Base-Main
8B • Updated • 274 -
RLinf/RLinf-OpenVLAOFT-LIBERO-90-Base-Lora
Reinforcement Learning • 8B • Updated • 72 -
RLinf/RLinf-OpenVLAOFT-LIBERO-130
Reinforcement Learning • 8B • Updated • 64 • 2
WideSeek-R1: Exploring Width Scaling for Broad Information Seeking via Multi-Agent Reinforcement Learning
-
RLinf/RLinf-OpenVLAOFT-LIBERO-130-Base-Lora
Reinforcement Learning • 8B • Updated • 280 -
RLinf/RLinf-OpenVLAOFT-ManiSkill-Base-Main
8B • Updated • 274 -
RLinf/RLinf-OpenVLAOFT-LIBERO-90-Base-Lora
Reinforcement Learning • 8B • Updated • 72 -
RLinf/RLinf-OpenVLAOFT-LIBERO-130
Reinforcement Learning • 8B • Updated • 64 • 2
WideSeek-R1: Exploring Width Scaling for Broad Information Seeking via Multi-Agent Reinforcement Learning