Xinyu Zhu | PhD student at UVA

Ph.D. Student

Email: [email protected] or [email protected]

Now I’m working on:

LLM Reasoning

Hi!👋 I’m Xinyu (/ʃɪn.ju:/) Zhu, ****a first-year computer science Ph.D. student at the University of Virginia, advised by Prof. ****Yu Meng. I am broadly interested in NLP and ML, especially in solving complex reasoning problems with LLMs, improving generation quality and reducing hallucination of LLMs. My long-term research goal is to enable human expert level reasoning, decision-making and cognitive intelligence for neural models and systems. I received my master degree at Tsinghua University, advised by Prof. ****Yujiu Yang.

✨News

[06/2025] Our AdaDecode is accepted at ICML 2025! 🎉
[05/2025] I moved to Cupertino and started my internship at Apple AIML, looking forward to meeting new friends in the Bay Area! 🚀
[03/2025] One survey on the honesty of LLMs is accepted at TMLR! 🎉
[01/2025] One paper on evaluating LMM's reasoning via chart-to-code generation ****is accepted at ICLR 2025! 🎉
[10/2024] Check out our comprehensive survey on the honesty of LLMs! 🎉 Also checkout our accompanied github repo! PRs welcome!
[09/2024] One paper on improving MoE models' reasoning via self-contrast has been accepted at NeurIPS 2024, congrats to all the co-authors🎉! See you in Vancouver!
Old news

👨‍🎓Education

University of Virginia 2024 -- Present Ph.D. in Computer Science
Tsinghua University 2021 -- 2024 Master in Electronic and Information Engineering
Xidian University 2017 -- 2021 Bachelor in Electronic Science and Technology

📝Selected Works (* indicates equal contribution)

The Surprising Effectiveness of Negative Reinforcement in LLM Reasoning

Preprint

Xinyu Zhu, Mengzhou Xia, Zhepei Wei, Wei-Lin Chen, Danqi Chen, Yu Meng

[paper][code][X thread]

Unchosen Experts Can Contribute Too: Unleashing MoE Models' Power by Self-Contrast

NeurIPS 2024

Chufan Shi, Cheng Yang*, Xinyu Zhu*, Jiahao Wang*, Taiqiang Wu, Siheng Li, Deng Cai, Yujiu Yang, Yu Meng*

[paper][code]