Jiayi Yuan

About me

I’m Jiayi Yuan ([dʒa-ˈi:], 袁加熠), a Ph.D. candidate from the Department of Computer Science at Rice University, advised by Dr. Xia “Ben” Hu. I aim to build efficient machine learning algorithms and systems (MLSys) through methods like quantization, sparsity and re-parameterization while enhancing system robustness and security. My research applications span language, vision, time series, graph, and healthcare domains. Recently, I’ve been working on:

• Efficiency problems of long-context LLMs. [KIVI] [KVBench] [Stop Overthinking] [AutoL2S]

• LLM post-training: finetune, RL, and evaluation. [Give Me FP32] [The Science] [DHP]

• LLM Agent, LLM Routing, LLM safety. [Honeypot] [LTSM] [Taylor Unswift] [LoRATK]

Previously, I received my bachelor’s degree in computer science from Tsinghua University, where I also studied statistics as a minor.

I lived in Beijing for 22 years and in Houston for $YEAR-2022 year(s).

I am seeking full-time research scientist/engineer positions. Please feel free to contact me regarding any opportunities!

Education & Experience

• Internship, 2025, NVIDIA

• Internship, 2024, Amazon

• Ph.D. in Computer Science, 2022 - 2026 (expected). Rice University

• B.Eng. in Computer Science and Technology, 2017 - 2021. Tsinghua University

Highlights

• “Give me FP32” studies nondeterminism, which has become a heated topic; e.g., it was recently featured in a blog post by Thinking Machines Lab.

• KIVI largely inspires KV Cache quantization in Huggingface and is integrated into Transformers. Full code is available here.

• Rice News: Large language models could be the key to better patient-trial matching - Rice CS Ph.D. student wins AMIA Best Student Paper Award.

• Rice News: Rice CS’ Xia Ben Hu investigates LLMs and likely applications.

News

• “Give Me FP32 or Give Me Death” got accepted to NeurIPS 2025 as an Oral (77 out of 21575 submissions) — numerical precision errors have become a hot topic! Code & Talk

• I got three papers at NAACL, ACL, and EMNLP 2025 each, wish I got to visit Albuquerque, Vienna, and Suzhou this year

• One survey on efficient LLM reasoning has been accepted by TMLR! Feel free to UPVOTE

• Check out our recent insights and discussions on LLM evaluation

• Two papers accepted by EMNLP 2024 (Main + Finding). See you in Miami!

• Check out our recent benchmarking works on KV Cache compression, time series foundation models and LLM evaluation!

• KIVI and SEED-GNN got accepted by ICML 2024. See you in Vienna!

• Our LLM-PTM paper is selected as a best student paper at AMIA 2023

• One paper accepted by NeurIPS 2023

• Joined Microsoft Accelerating Foundation Models Research program

• …

Publications

Please refer to publications or Google Scholar.