4 papers
Breaking Bottlenecks in Solid Electrolyte Discovery with Large Artificial Intelligence Models
Eric Jianfeng Cheng, Min Hong, Zhiquan Zeng +22
Solid electrolytes (SEs) are central to next-generation metal batteries, yet their discovery remains constrained by fragmented data, limited transferability of simulations, and slo…
On Second-Order Methods for Bilevel Optimization
Jiawen Bi, Jiaxiang Li, Mingyi Hong +1
Bilevel optimization is an indispensable modeling tool for modern machine learning and engineering design. However, the theory and practice for finding second order stationary poin…
REVES: REvision and VErification--Augmented Training for Test-Time Scaling
Yuanxin Liu, Ruida Zhou, Xinyan Zhao +6
Test-time scaling via sequential revision has emerged as a powerful paradigm for enhancing Large Language Model (LLM) reasoning. However, standard post-training methods primarily o…
DISPO: Enhancing Training Efficiency and Stability in Reinforcement Learning for Large Language Model Mathematical Reasoning
Batuhan K. Karaman, Aditya Rawal, Suhaila Shakiah +4
Reinforcement learning with verifiable rewards has emerged as a promising paradigm for enhancing the reasoning capabilities of large language models particularly in mathematics. Cu…