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cs.CL2025
RIDE: Difficulty Evolving Perturbation with Item Response Theory for Mathematical Reasoning
Xinyuan Li, Murong Xu, Wenbiao Tao +4
Large language models (LLMs) achieve high performance on mathematical reasoning, but these results can be inflated by training data leakage or superficial pattern matching rather t…
cs.CL2025
More Data or Better Data? A Critical Analysis of Data Selection and Synthesis for Mathematical Reasoning
Yike Zhao, Simin Guo, Ziqing Yang +3
The reasoning capabilities of Large Language Models (LLMs) play a critical role in many downstream tasks, yet depend strongly on the quality of training data. Despite various propo…
cs.MA2025
Diffusion Stochastic Learning Over Adaptive Competing Networks
Yike Zhao, Haoyuan Cai, Ali H. Sayed
This paper studies a stochastic dynamic game between two competing teams, each consisting of a network of collaborating agents. Unlike fully cooperative settings, where all agents…