I am a third-year Master’s student in Data Science at Tsinghua University, advised by Prof. Shao-Lun Huang. Before that, I earned my B.S. in Electronic Engineering from Sun Yat-sen University (SYSU) in 2022, under the guidance of Prof. Yulan Guo. Currently I’m a research intern at Microsoft Research Asia, working with Dr. Yeyun Gong. I also interned at Tencent AI Lab, collaborating with Dr. Pengyu Cheng.

My current research focuses on pre-training strategy and reinforcement learning (RL) for Large Language Models (LLMs), with a long-term aim at AGI. I am excited to apply for Fall 2025 PhD programs and investigate potential collaborations. If you are interested in discussing opportunities or have any questions, please feel free to EMAIL me. I genuinely appreciate your consideration and look forward to connecting with you.

📖Education

• Aug. 2022 - Jun. 2025 (Expected) M.Sc., Data Science and Information Technology, Tsinghua University, Beijing, China.
  GPA: 3.98/4.0, Top 3%

• Sep. 2018 - Jun. 2022 B.Sc., Electronic Information Science and Technology, Sun Yat-sen University, Guangzhou, China.
  GPA: 4.11/5.0, Top 3%

📑Publications

Language Modeling:

	What You See Is What You Get: Entity-Aware Summarization for Reliable Sponsored Search Xiao Liang, Xinyu Hu, Simiao Zuo, Jimi He, Yu Wang, Victor Ye Dong, Yeyun Gong, Kushal S. Dave, Yi Liu, Qiang Lou, Shao-Lun Huang, Jian Jiao NeurIPS 2024 SafeGenAi, [Paper] We introduce a framework for generating reliable AI-driven entity-aware summaries for information retrieval in the sponsored search ads domain.
	Integrative Decoding: Improve Factuality via Implicit Self-consistency Yi Cheng, Xiao Liang, Yeyun Gong, Wen Xiao, Song Wang, Yuji Zhang, Wenjun Hou, Kaishuai Xu, Wenge Liu, Wenjie Li, Jian Jiao, Qi Chen, Peng Cheng, Wayne Xiong Preprint 2024, [Paper] This paper presents a self-consistency based decoding strategy for improving the factual accuracy of large language models, especially in long-form generation tasks.
	Task Oriented In-Domain Data Augmentation Xiao Liang* , Xinyu Hu*, Simiao Zuo, Yeyun Gong, Qiang Lou, Yi Liu, Shao-Lun Huang, Jian Jiao EMNLP 2024, [Paper] We propose a task-oriented in-domain data augmentation framework consisting of in-domain data selection and task-oriented synthetic passage generation.
	SSLCL: An Efficient Model-Agnostic Supervised Contrastive Learning Framework for Emotion Recognition in Conversations Tao Shi*, Xiao Liang*, Yaoyuan Liang, Xinyi Tong, Shao-Lun Huang Preprint 2023, [Paper] [Code] We introduce utilizing label representations by projecting discrete labels into dense embeddings for multimodal emotion classification.
	Chunk, Align, Select: A Simple Long-sequence Processing Method for Transformers Jiawen Xie, Pengyu Cheng, Xiao Liang, Yong Dai, Nan Du ACL 2024, [Paper] [Code] We propose a token selection framework for pre-trained transformers to process long sequences utilizing reinforcement learning.

Multimodal Understanding:

	Exploring Iterative Refinement with Diffusion Models for Video Grounding Xiao Liang*, Tao Shi*, Yaoyuan Liang, Te Tao, Shao-Lun Huang ICME 2024, [Paper] [Code] We propose a novel framework with diffusion models that formulates video grounding as a conditioned generation task, enhancing predictions through iterative refinement.
	CoSTA: End-to-End Comprehensive Space-Time Entanglement for Spatio-Temporal Video Grounding Yaoyuan Liang*, Xiao Liang*, Yansong Tang, Zhao Yang, Ziran Li, Jingang Wang, Wenbo Ding, Shao-Lun Huang AAAI 2024, [Paper] We propose a framework of Comprehensive Space-Time entAnglement to densely entangle space-time multi-modal features for spatio-temporal localization.
	Unleash Region Understanding in Intermediate Layers for MLLM-based Referring Expression Generation Yaoyuan Liang, Zhuojun Cai, Jian Xu, Guanbo Huang, Yiran Wang, Xiao Liang, Jiahao Liu, Ziran Li, Jingang Wang, Shao-Lun Huang NeurIPS 2024, [Paper] [Code] We present to elicit the latent information in intermediate layers adopt a cycle-consistency-based decoding method to alleviate hallucinations in the REG task.

(* indicates equal contribution)

🧑‍💻Experience

• (Nov. 2023 - Present) Reserch Intern, NLC Group, Microsoft Research Asia, Beijing, China.
  Mentor: Yeyun Gong
  Working on large language models, pre-training strategy and model architecture.

• (Mar. 2023 - Sep. 2023) Research Intern, AI Lab, Tencent Inc., Guangdong, China.
  Mentor: Pengyu Cheng, Nan Du
  Working on large language models, long sequence processing.

🏆Honors and Awards

• Second Prize Scholarship, Tsinhua University, Beijing, 2024
• Outstanding Graduate Thesis, Sun Yat-sen University, Guangdong, 2022
• Outstanding Graduate Student, Sun Yat-sen University, Guangdong, 2022
• Second Prize Scholarship, Sun Yat-sen University, Guangdong, 2019~2022
• 1st of the 2022 Tsinghua Open Hack Competition - Multimodal Learning Track, Tsinghua University, Beijing, 2022