9 citations · 10 across the 6 of their papers we have counts for
6 papers
ORMind: A Cognitive-Inspired End-to-End Reasoning Framework for Operations Research
Zhiyuan Wang, Bokui Chen, Yinya Huang +4
Operations research (OR) is widely deployed to solve critical decision-making problems with complex objectives and constraints, impacting manufacturing, logistics, finance, and hea…
FVEL: Interactive Formal Verification Environment with Large Language Models via Theorem Proving
Xiaohan Lin, Qingxing Cao, Yinya Huang +5
Formal verification (FV) has witnessed growing significance with current emerging program synthesis by the evolving large language models (LLMs). However, current formal verificati…
ATG: Benchmarking Automated Theorem Generation for Generative Language Models
Xiaohan Lin, Qingxing Cao, Yinya Huang +4
Humans can develop new theorems to explore broader and more complex mathematical results. While current generative language models (LMs) have achieved significant improvement in au…
MUSTARD: Mastering Uniform Synthesis of Theorem and Proof Data
Yinya Huang, Xiaohan Lin, Zhengying Liu +6
Recent large language models (LLMs) have witnessed significant advancement in various tasks, including mathematical reasoning and theorem proving. As these two tasks require strict…
LEGO-Prover: Neural Theorem Proving with Growing Libraries
Haiming Wang, Huajian Xin, Chuanyang Zheng +11
Despite the success of large language models (LLMs), the task of theorem proving still remains one of the hardest reasoning tasks that is far from being fully solved. Prior methods…
TRIGO: Benchmarking Formal Mathematical Proof Reduction for Generative Language Models
Jing Xiong, Jianhao Shen, Ye Yuan +11
Automated theorem proving (ATP) has become an appealing domain for exploring the reasoning ability of the recent successful generative language models. However, current ATP benchma…