4 papers
RL4RLA: Teaching ML to Discover Randomized Linear Algebra Algorithms Through Curriculum Design and Graph-Based Search
Jinglong Xiong, Xiaotian Liu, Ruoxin Wang +4
Randomized linear algebra (RLA) algorithms are a modern class of numerical linear algebra techniques that play an essential role in scientific computing and machine learning, with…
Expression Syntax Information Bottleneck for Math Word Problems
Jing Xiong, Chengming Li, Min Yang +2
Math Word Problems (MWP) aims to automatically solve mathematical questions given in texts. Previous studies tend to design complex models to capture additional information in the…
FormalAlign: Automated Alignment Evaluation for Autoformalization
Jianqiao Lu, Yingjia Wan, Yinya Huang +3
Autoformalization aims to convert informal mathematical proofs into machine-verifiable formats, bridging the gap between natural and formal languages. However, ensuring semantic al…
AlignedCoT: Prompting Large Language Models via Native-Speaking Demonstrations
Zhicheng Yang, Yinya Huang, Jing Xiong +4
Large Language Models prompting, such as using in-context demonstrations, is a mainstream technique for invoking LLMs to perform high-performance and solid complex reasoning (e.g.,…