SFT induces pseudo-reasoning paths that undermine RL in LVLMs, while RL with GRPO and mixed perception-cognition rewards on the new VLAA-Thinking dataset produces more genuine reasoning and top leaderboard performance.
How many objects are left? •Original Answer: 3 Input Image <think> Okay, let's see
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SFT or RL? An Early Investigation into Training R1-Like Reasoning Large Vision-Language Models
SFT induces pseudo-reasoning paths that undermine RL in LVLMs, while RL with GRPO and mixed perception-cognition rewards on the new VLAA-Thinking dataset produces more genuine reasoning and top leaderboard performance.