1 code implementation • 6 May 2024 • Guoxin Chen, Minpeng Liao, Chengxi Li, Kai Fan
The experimental results on both in-domain and out-of-domain datasets demonstrate that even without GPT-4 or human-annotated process supervision, our AlphaMath framework achieves comparable or superior results to previous state-of-the-art methods.
no code implementations • 24 Jan 2024 • Guoxin Chen, Kexin Tang, Chao Yang, Fuying Ye, Yu Qiao, Yiming Qian
Moreover, existing reinforcement learning (RL) based methods overlook the structured relationships, underutilizing the potential of RL in structured reasoning.
1 code implementation • 27 Oct 2023 • Guoxin Chen, Yiming Qian, Bowen Wang, Liangzhi Li
The large language models have achieved superior performance on various natural language tasks.
1 code implementation • 14 Oct 2023 • Guoxin Chen, Yongqing Wang, Fangda Guo, Qinglang Guo, Jiangli Shao, HuaWei Shen, Xueqi Cheng
Most existing methods that address out-of-distribution (OOD) generalization for node classification on graphs primarily focus on a specific type of data biases, such as label selection bias or structural bias.