I am Heming Xia (夏鹤明), a Ph.D. student in the NLP Group at The Hong Kong Polytechnic University, supervised by Prof. Wenjie Li. I earned my master’s degree from the MOE Key Lab of Computational Linguistics at Peking University, advised by Prof. Zhifang Sui. Prior to that, I completed my bachelor’s degree from the School of Physics at Peking University in 2020. I have also worked as a Research Intern at the NLC Group @ Microsoft Research Asia, where I had the privilege of collaborating with Dr. Tao Ge. Currently, I am an intern at SEA AI Lab, working closely with Dr. Cunxiao Du. For more details, please see my CV.

📬 I am open to collaborating with highly motivated students on research related to (but not limited to) the topics below. If interested, please feel free to reach out via email.

Research

My research focuses on efficient and effective NLP, with the goal of making LLMs faster, more scalable, and broadly applicable. Specifically, my work centers on the following directions:

• Speculative Decoding: Exploring inference acceleration techniques that maintain output fidelity. This includes our pioneering work on Speculative Decoding [EMNLP’23-findings, ICLR’25] and the first comprehensive survey [ACL’24-findings] on this paradigm.
• Efficient Reasoning: Developing advanced algorithms to enhance the efficiency of reasoning models, spanning efficient training strategies, inference acceleration [EMNLP’25], and novel reasoning representations such as latent CoT [arXiv’25].
• Applications (Efficiency + X): I am interested in how efficiency-oriented techniques can benefit broader applications, with recent focus on tool-augmented agents and multimodal models [EMNLP’25].

In addition, I am actively working on tool learning [e.g., EMNLP’24, ACL’25-findings] and vision-language understanding [e.g., ACL’22, EMNLP’23-findings, EMNLP’25-findings].