most citedKnapsack RL: Unlocking Exploration of LLMs via Optimizing Budget Allocation

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cs.AI2026

VeRA: Verified Reasoning Data Augmentation at Scale

Zerui Cheng, Jiashuo Liu, Chunjie Wu +4

The main issue with most evaluation schemes today is their "static" nature: the same problems are reused repeatedly, allowing for memorization, format exploitation, and eventual sa…

cs.AI2025

RLoop: An Self-Improving Framework for Reinforcement Learning with Iterative Policy Initialization

Zeng Zhiyuan, Jiashuo Liu, Zhangyue Yin +3

While Reinforcement Learning for Verifiable Rewards (RLVR) is powerful for training large reasoning models, its training dynamics harbor a critical challenge: RL overfitting, where…