29 citations · 32 across the 8 of their papers we have counts for
4 papers · 1 filter
Exploring the Limit of Outcome Reward for Learning Mathematical Reasoning
Chengqi Lyu, Songyang Gao, Yuzhe Gu +14
Reasoning abilities, especially those for solving complex math problems, are crucial components of general intelligence. Recent advances by proprietary companies, such as o-series…
Training Language Models to Critique With Multi-agent Feedback
Tian Lan, Wenwei Zhang, Chengqi Lyu +6
Critique ability, a meta-cognitive capability of humans, presents significant challenges for LLMs to improve. Recent works primarily rely on supervised fine-tuning (SFT) using crit…
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…