Challenging the Boundaries of Reasoning: An Olympiad-Level Math Benchmark for Large Language Models

2 code implementations • 27 Mar 2025 • Haoxiang Sun, Yingqian Min, Zhipeng Chen, Wayne Xin Zhao, Lei Fang, Zheng Liu, Zhongyuan Wang, Ji-Rong Wen

In recent years, the rapid development of large reasoning models has resulted in the saturation of existing benchmarks for evaluating mathematical reasoning, highlighting the urgent need for more challenging and rigorous evaluation frameworks.

Math Mathematical Reasoning

Enhancing LLM Reasoning with Reward-guided Tree Search

2 code implementations • 18 Nov 2024 • Jinhao Jiang, Zhipeng Chen, Yingqian Min, Jie Chen, Xiaoxue Cheng, Jiapeng Wang, Yiru Tang, Haoxiang Sun, Jia Deng, Wayne Xin Zhao, Zheng Liu, Dong Yan, Jian Xie, Zhongyuan Wang, Ji-Rong Wen

This framework is implemented by integrating the policy model, reward model, and search algorithm.

Mathematical Reasoning

$p$SVM: Soft-margin SVMs with $p$-norm Hinge Loss

1 code implementation • 19 Aug 2024 • Haoxiang Sun

Support Vector Machines (SVMs) based on hinge loss have been extensively discussed and applied to various binary classification tasks.

Binary Classification Multi-class Classification

LLMBox: A Comprehensive Library for Large Language Models

1 code implementation • 8 Jul 2024 • Tianyi Tang, Yiwen Hu, Bingqian Li, Wenyang Luo, Zijing Qin, Haoxiang Sun, Jiapeng Wang, Shiyi Xu, Xiaoxue Cheng, Geyang Guo, Han Peng, Bowen Zheng, Yiru Tang, Yingqian Min, Yushuo Chen, Jie Chen, Yuanqian Zhao, Luran Ding, Yuhao Wang, Zican Dong, Chunxuan Xia, Junyi Li, Kun Zhou, Wayne Xin Zhao, Ji-Rong Wen

To facilitate the research on large language models (LLMs), this paper presents a comprehensive and unified library, LLMBox, to ease the development, use, and evaluation of LLMs.