Longguang Zhong

About Me

Hello, I’m Longguang Zhong, an M.S. student in Computer Technology at Sun Yat-sen University, where I’m currently studying under the supervision of Prof. Xiaojun Quan. I earned my bachelor’s degree in Software Engineering from Xidian University.

Research Interests

My research focuses on large language models, including pruning, model fusion, and preference alignment.

News

[August 2025] 🔥🔥 ThinkSwitcher, our work on adaptive thinking strategies for language reasoning models, is accepted to EMNLP 2025 Findings! Check out the paper here.

[August 2025] 🔥🔥 FuseChat, our work on knowledge fusion of chat models, is accepted to EMNLP 2025 Main! Check out the paper here and the code on GitHub.

[May 2025] 🔥 BlockPruner, a fine-grained block pruning framework for large language models, is accepted to ACL 2025 Findings! Check out the paper here and the code on GitHub.

[Jan 2025] 🔥 We release FuseO1-Preview, an advanced fusion model that enhances System-II reasoning by integrating multiple O1-like models using SCE merging, excelling in mathematics, coding, and science.

[Dec 2024] 🔥 We release FuseChat-3.0 and Blog Post. FuseChat-3.0 contains a series of models crafted to enhance performance by integrating the strengths of multiple source LLMs into more compact target LLMs.

[Aug 2024] 🔥 We update the FuseChat tech report and release FuseChat-7B-v2.0, which is the fusion of six prominent chat LLMs with diverse architectures and scales. FuseChat-7B-v2.0 achieves an average performance of 7.38 on MT-Bench (GPT-4-0125-Preview as judge LLM), which is comparable to Mixtral-8x7B-Instruct and approaches GPT-3.5-Turbo-1106.

Publications