Welcome to Xianglong Yan’s (闫相龙) personal website!

I am currently a third-year undergraduate student at Shanghai Jiao Tong University (SJTU), majoring in Computer Science and Technology at the School of Computer Science, SJTU. I am advised by Prof. Yulun Zhang.

My research focuses on efficient large language model (LLM) deployment, with particular emphasis on model compression and long-context inference. I am especially interested in post-training quantization (PTQ), low-bit quantization (e.g., binarization and ternarization), and KV cache compression, aiming to build accurate yet resource-efficient LLM systems that are practical for real-world deployment.

I am always open to collaborations and academic discussions. Feel free to reach out via email at yanxianglong@sjtu.edu.cn, or connect with me on WeChat (ID: yxlsds).

🔥 News

• 2026.03:  🎉🎉 We released Awesome Visual Autoregressive Modeling, a curated list of 60+ papers on the VAR paradigm!
• 2026.01:  🎉🎉 Our papers PT²-LLM and Quant-dLLM have been accepted to ICLR 2026!
• 2025.11:  🎉🎉 Our team was awarded the Grand Prize at the National “Challenge Cup” Competition (挑战杯全国特等奖)!
• 2025.01:  🎉🎉 Our paper ARB-LLM has been accepted to ICLR 2025!

📝 Publications

ICLR 2026

PT²-LLM: Post-Training Ternarization for Large Language Models

Xianglong Yan^†, Chengzhu Bao^†, Zhiteng Li, Tianao Zhang, Kaicheng Yang, Haotong Qin, Ruobing Xie, Xingwu Sun, Yulun Zhang^*

Code

• TL;DR: An efficient post-training ternarization framework for LLMs, incorporating an asymmetric ternary quantizer and column rearrangement strategy.

ICLR 2025

ARB-LLM: Alternating Refined Binarizations for Large Language Models

Zhiteng Li^†, Xianglong Yan^†, Tianao Zhang, Haotong Qin, Dong Xie, Jiang Tian, Zhongchao Shi, Linghe Kong^*, Yulun Zhang^*, Xiaokang Yang

Code

• TL;DR: Proposes alternating refined binarization for LLMs, surpassing FP16 models on the Pareto curve.

ICLR 2026

Quant-dLLM: Post-Training Extreme Low-Bit Quantization for Diffusion Large Language Models

Tianao Zhang^†, Zhiteng Li^†, Xianglong Yan, Haotong Qin, Yong Guo, Yulun Zhang^*

Code

• TL;DR: The first work to explore low-bit quantization for diffusion LLMs, achieving SOTA performance at 2-bit.

🎖 Honors and Awards

• 2024.10: National Scholarship, China (Top 0.2%)
• 2025.09: NSFC Undergraduate Young Scientist Research Grant
• 2025.11: National Grand Prize, “Challenge Cup” Competition (Team Leader)
• 2025.12: SJTU Model Student (Top 10 university-wide, 2025)

📖 Educations

• 2023.09 - now, B.Eng. in Computer Science and Technology, Shanghai Jiao Tong University (SJTU), Shanghai, China.
• 2020.09 - 2023.06, High School, The Experimental High School Attached to Beijing Normal University, Beijing, China.

🤝 Academic Service

• Reviewer, ICLR 2026