Capability Self-Assessment in Large Language Models
This work systematically compares supervised fine-tuning (SFT) and reinforcement learning (RL), evaluating each trained model's self-assessment against its updated capability and measuring how well it retains its solving ability.
Haoyan Yang, Reza Shirkavand, Yu Jin et al.
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