1 citations · 1 across the 4 of their papers we have counts for
4 papers
LLM-based Automated Theorem Proving Hinges on Scalable Synthetic Data Generation
Junyu Lai, Jiakun Zhang, Shuo Xu +6
Recent advancements in large language models (LLMs) have sparked considerable interest in automated theorem proving and a prominent line of research integrates stepwise LLM-based p…
Neuro-Symbolic Data Generation for Math Reasoning
Zenan Li, Zhi Zhou, Yuan Yao +5
A critical question about Large Language Models (LLMs) is whether their apparent deficiency in mathematical reasoning is inherent, or merely a result of insufficient exposure to hi…
Executing Arithmetic: Fine-Tuning Large Language Models as Turing Machines
Junyu Lai, Jiahe Xu, Yao Yang +3
Large Language Models (LLMs) have demonstrated remarkable capabilities across a wide range of natural language processing and reasoning tasks. However, their performance in the fou…
Softened Symbol Grounding for Neuro-symbolic Systems
Zenan Li, Yuan Yao, Taolue Chen +4
Neuro-symbolic learning generally consists of two separated worlds, i.e., neural network training and symbolic constraint solving, whose success hinges on symbol grounding, a funda…