Training GUI agents with augmented reasoning data and a tailored post-training recipe
Rui Yang PRO
Ray2333
AI & ML interests
Deep Reinforcement Learning
Recent Activity
liked a model about 14 hours ago
game2player/Game2Player-9B liked a model about 14 hours ago
game2player/Game2Player-4B upvoted a paper 9 days ago
Agent World Model in the Wild: Computer-Use Agent Environment SynthesisOrganizations
Generalizable Reward Models
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Ray2333/GRM-llama3-8B-sftreg
Text Classification • 8B • Updated • 100 • 5 -
Ray2333/GRM-llama3-8B-distill
Text Classification • 8B • Updated • 260 • 6 -
Ray2333/GRM-Gemma-2B-sftreg
Text Classification • 3B • Updated • 7.24k • 3 -
Regularizing Hidden States Enables Learning Generalizable Reward Model for LLMs
Paper • 2406.10216 • Published • 3
Training GUI agents with augmented reasoning data and a tailored post-training recipe
Generalizable Reward Models
-
Ray2333/GRM-llama3-8B-sftreg
Text Classification • 8B • Updated • 100 • 5 -
Ray2333/GRM-llama3-8B-distill
Text Classification • 8B • Updated • 260 • 6 -
Ray2333/GRM-Gemma-2B-sftreg
Text Classification • 3B • Updated • 7.24k • 3 -
Regularizing Hidden States Enables Learning Generalizable Reward Model for LLMs
Paper • 2406.10216 • Published • 3