Hi there! I am Tianyu Liu, a fourth-year joint Ph.D. student at USTC and Shanghai AI Laboratory, supervised by Sun Xiao.

My research interests mainly lie in efficient inference for LLMs. I am working on speculative decoding, a promising technique for accelerating LLM inference, and I am open to collaborations on related inference topics.

🔥 News

• 2025.10:  Released nano-PEARL, an engineering follow-up to PEARL with multi-GPU draft-target disaggregation.
• 2025.07:  Preprint LogitSpec to Arxiv, a training-free retrieval-based speculative decoding method!
• 2025.01:  PEARL is accepted to ICLR 2025!
• 2025.01:  One paper accepted to NAACL 2025. Thanks for the carry of Qitan!
• 2023.09:  REST is accepted to NeurIPS 2023!

📝 Selected Publications

^†: corresponding author; ^*: equal contribution

ICLR 2025

Featured PEARL: Parallel Speculative Decoding with Adaptive Draft Length

Tianyu Liu, Yun Li^†, Qitan Lv, Kai Liu, Jianchen Zhu, Winston Hu, Xiao Sun^†

[Paper]  [Project]  [Code]

🚀 Introduce nano-PEARL: a Draft-Target Disaggregation LLM Serving System via Parallel Speculative Decoding!

Preprint

LogitSpec: Accelerating Retrieval-based Speculative Decoding via Next Next Token Speculation

Tianyu Liu^*, Qitan Lv^*, Hao Li, Xing Gao, Xiao Sun^†

[Paper]  [Code]

NeurIPS 2023

Learning Rule-Induced Subgraph Representations for Inductive Relation Prediction

Tianyu Liu, Qitan Lv, Jie Wang^†, Shuling Yang, Hanzhu Chen

[Paper]  [Code]

🗂 Other Publications

📖 Educations

• 2022.09 - Present, Ph.D. in Department of Electronic Engineering and Information Science, University of Science and Technology of China.
• 2018.09 - 2022.06, B.Sc. in Computer Science and Technology, Central University of Finance and Economics.

🖥️ Professional Services

• Conference reviewer for ICLR'25, ICLR'26, WWW'25, NeurIPS'25.