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Composition-RL: Compose Your Verifiable Prompts for Reinforcement Learning of Large Language Models

Intermediate
Xin Xu, Clive Bai et al.Feb 12arXiv

This paper shows a simple way to turn many 'too-easy' questions into harder, still-checkable ones so that AI keeps learning instead of stalling.

#Reinforcement Learning with Verifiable Rewards#Compositional prompts#Sequential Prompt Composition

Data Repetition Beats Data Scaling in Long-CoT Supervised Fine-Tuning

Intermediate
Dawid J. Kopiczko, Sagar Vaze et al.Feb 11arXiv

The paper shows that, when teaching a reasoning AI with step-by-step examples, repeating a small set many times can beat using a huge set only once.

#Supervised Fine-Tuning#Chain-of-Thought#Data Repetition

Rethinking LLM-as-a-Judge: Representation-as-a-Judge with Small Language Models via Semantic Capacity Asymmetry

Intermediate
Zhuochun Li, Yong Zhang et al.Jan 30arXiv

Big models are often used to grade AI answers, but they are expensive, slow, and depend too much on tricky prompts.

#Representation-as-a-Judge#Semantic Capacity Asymmetry#LLM-as-a-Judge