29 citations · 35 across the 5 of their papers we have counts for
5 papers
Seed-Prover: Deep and Broad Reasoning for Automated Theorem Proving
Luoxin Chen, Jinming Gu, Liankai Huang +33
LLMs have demonstrated strong mathematical reasoning abilities by leveraging reinforcement learning with long chain-of-thought, yet they continue to struggle with theorem proving d…
InternLM2.5-StepProver: Advancing Automated Theorem Proving via Critic-Guided Search
Zijian Wu, Suozhi Huang, Zhejian Zhou +5
Large Language Models (LLMs) have emerged as powerful tools in mathematical theorem proving, particularly when utilizing formal languages such as LEAN. A prevalent proof method inv…
Lean Workbook: A large-scale Lean problem set formalized from natural language math problems
Huaiyuan Ying, Zijian Wu, Yihan Geng +3
Large language models have demonstrated impressive capabilities across various natural language processing tasks, especially in solving mathematical problems. However, large langua…
InternLM2 Technical Report
Zheng Cai, Maosong Cao, Haojiong Chen +97
The evolution of Large Language Models (LLMs) like ChatGPT and GPT-4 has sparked discussions on the advent of Artificial General Intelligence (AGI). However, replicating such advan…
InternLM-Math: Open Math Large Language Models Toward Verifiable Reasoning
Huaiyuan Ying, Shuo Zhang, Linyang Li +19
The math abilities of large language models can represent their abstract reasoning ability. In this paper, we introduce and open-source our math reasoning LLMs InternLM-Math which…