Papers by Bingjin Chen

1 papers
Distributional Clarity: The Hidden Driver of RL-Friendliness in Large Language Models (2026.acl-long)

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Challenge: RL-friendly models exhibit intra-class compactness and inter-class separation in probability assignments . under identical training, Qwen models achieve substantial gains, while others like Llama yield limited improvements.
Approach: They propose a method to quantify distributional clarity in probability space . they show distributional clearness is a trainable property underlying RL-Friendliness .
Outcome: The proposed model families achieve substantial gains under identical training, while others like Llama yield limited improvements.

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