Xuyang Liu (刘旭洋)

🌈 I am a second-year Master’s student at Sichuan University, supervised by Prof. Honggang Chen. I will soon join Ant Group as a research intern in Hangzhou, focusing on GUI Agent. Previously, I completed an 8-month internship at Taobao & Tmall Group in Beijing, working on Efficient MLLM. I’ve also spent half a year visiting MiLAB at Westlake University, supervised by Prof. Donglin Wang. I am very glad to be supervised and collaborated with Dr. Siteng Huang from DAMO Academy and Asst. Prof. Linfeng Zhang from SJTU.

📌 My research interests span Efficient Vision-Language Models, including:

• Efficient Inference: GlobalCom², FiCoCo, ToCa, Sparse-Tuning
• Efficient Transfer: M2IST, V-PETL Bench, VGDiffZero, DARA, Sparse-Tuning, AutoGnothi

📢 Recently, I am mainly focusing on Token Reduction for Model Compression. Feel free to reach out to me via Email liuxuyang@stu.scu.edu.cn, if you are interested in collaborating with me. 🙋 I’m actively seeking Ph.D. position in 2026 Fall!

🔥 News

• 2025.03.11 🎊🎊 One first author paper (M2IST) about parameter-, memory-, and time-efficient fine-tuning for referring expression comprehension has been accepted by IEEE Transactions on Circuits and Systems for Video Technology (TCSVT)!
• 2025.02.22: 🎊🎊 Two papers (ToCa and AutoGnothi) have been accepted by ICLR 2025! Congratulations to all collaborators!
• 2025.01.10: 🤗🤗 We release GlobalCom², a “global-to-local” approach for training-free acceleration of high-resolution LVLMs with dynamic tiling strategy. Code is available!
• 2024.11.17: We release FiCoCo which proposes a unified paradigm to demystify the popular works and guide the future designs of training-free token reduction for MLLMs. Code is available!
• 2024.09.26: 🎊🎊 One co-first author paper (V-PETL) about unified visual parameter-efficient transfer learning benchmark has been accepted by NeurIPS 2024!
• 2024.07.22: ⛵⛵ I begin my research internship at Taobao & Tmall Group, focusing on multi-modal large language models (MLLM).
• 2024.03.13: One co-first author paper (DARA) about parameter-efficient tuning for visual grounding has been by ICME 2024, and selected as Oral!
• 2023.12.13: 🎊🎊 One first author paper (VGDiffZero) about zero-shot visual grounding has been accepted by ICASSP 2024, which is my first work during during master’s studies!

📝 Publications

Please find my full publications on my Google Scholar profile.

Conference Papers

Chang Zou^*, Xuyang Liu^*, Ting Liu, Siteng Huang, Linfeng Zhang, "Accelerating Diffusion Transformers with Token-wise Feature Caching". In International Conference on Learning Representations (ICLR), 2025. [paper] [OpenReview] [page] [code] [量子位]

Shaobo Wang, Hongxuan Tang, Mingyang Wang, Hongrui Zhang, Xuyang Liu, Weiya Li, Xuming Hu, Linfeng Zhang, "Gnothi Seauton: Empowering Faithful Self-Interpretability in Black-Box Models". In International Conference on Learning Representations (ICLR), 2025. [paper] [OpenReview] [code]

Yi Xin^*, Siqi Luo^*, Xuyang Liu^*, Yuntao Du^*, Haodi Zhou, Xinyu Cheng, Christina Lee, and 10 more authors, "V-PETL Bench: A Unified Visual Parameter-Efficient Transfer Learning Benchmark". In Neural Information Processing Systems Datasets and Benchmarks Track (NeurlPS D&B Track), 2024. [paper][page] [code] [poster]

Xuyang Liu^*, Siteng Huang^*, Yachen Kang, Honggang Chen, Donglin Wang, "VGDiffZero: Text-to-image Diffusion Models Can Be Zero-shot Visual Grounders". In IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2024. [paper] [code] [poster]

Ting Liu^*, Xuyang Liu^*, Siteng Huang, Honggang Chen, Quanjun Yin, Long Qin, Donglin Wang, Yue Hu, "DARA: Domain- and Relation-aware Adapters Make Parameter-efficient Tuning for Visual Grounding". In IEEE International Conference on Multimedia & Expo (ICME), 2024. (Oral) [paper] [code] [poster]

Journal Papers

Xuyang Liu^*, Ting Liu^*, Siteng Huang, Yi Xin, Yue Hu, Quanjun Yin, Donglin Wang, Yuanyuan Wu, Honggang Chen "M2IST: Multi-Modal Interactive Side-Tuning for Efficient Referring Expression Comprehension". IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2025. [paper] [code]

Xinying Lin, Xuyang Liu, Hong Yang, Xiaohai He, Honggang Chen, "Perception- and Fidelity-aware Reduced-Reference Super-Resolution Image Quality Assessment". IEEE Transactions on Broadcasting (TBC), 2024. [paper] [code]

Xuyang Liu, "GLMLP-TRANS: A transportation mode detection model using lightweight sensors integrated in smartphones". Computer Communications, 2022. [paper] [code]

Preprints & Under Submission

Xuyang Liu, Ziming Wang, Yuhang Han, Yingyao Wang, Jiale Yuan, Jun Song, Bo Zheng, Linfeng Zhang, Siteng Huang, Honggang Chen, "Global Compression Commander: Plug-and-Play Inference Acceleration for High-Resolution Large Vision-Language Models". arXiv preprint arXiv:2501.05179. [paper] [code]

Yuhang Han^*, Xuyang Liu^*, Pengxiang Ding, Donglin Wang, Honggang Chen, Qingsen Yan, Siteng Huang "Filter, Correlate, Compress: Training-Free Token Reduction for MLLM Acceleration". arXiv preprint arXiv:2411.17686. [paper] [page] [code]

Ting Liu^*, Xuyang Liu^*, Siteng Huang, Liangtao Shi, Zunnan Xu , Yi Xin, Quanjun Yin, Xiaohong Liu "Dense-Tuning: Densely Adapting Vision Transformers with Efficient Fine-tuning and Inference". arXiv preprint arXiv:2405.14700. [paper] [github] [Chinese intro (Zhihu)]

🤗 Resources

Please find my full repositories on my GitHub profile.

• Awesome Generation Acceleration
  • Duty: Owner.
  • Description: An open-source repository that curates a collection of recent awesome papers on AIGC acceleration.
• Awesome Token Reduction for Model Compression
  • Duty: Owner.
  • Description: An open-source repository that curates a collection of recent awesome papers on token reduction for model compression.

💻 Internships

• Research Intern - Taobao & Tmall Group, Alibaba Group, Beijing
  • Time: Jul 2024 - Mar 2025.
  • Thesis: Efficient Multi-modal Large Language Models.
• Research Intern - Machine Intelligence Laboratory, Westlake University, Hangzhou
  • Time: Mar 2023 - Sep 2023.
  • Thesis: Efficient Transfer of Vision-language Models.
  • Supervisers: Dr. Siteng Huang and Prof. Donglin Wang.

🎖️ Honors

• Suzhou Industrial Park Scholarship, 2024 (12 Students in Sichuan University).

📠 Services

Conference Reviewer

• ACM International Conference on Multimedia (MM)