Runpeng Yu
Actively Seeking Intern and Visiting Opportunities
I am expected to graduate in the summer of 2026 (approximately one year from now) and am actively seeking internship opportunities, visiting programs, and full-time positions after graduation.
Research Interests
My Research interests lie in the following topics:
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Large Language Model. Large Language Model (LLM) reasoning; Chain-of-Thought (CoT).
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Multimodal Large Language Model. Multimodal Chain-of-Thought; perception process of Multimodal Large Language Model (MLLM).
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Machine Learning. Lineage relationships among pretrained models; pretrained model reuse.
Publications
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Introducing Visual Perception Token into Multimodal Large Language Model
[Paper]
Runpeng Yu
, Xinyin Ma and Xinchao Wang.
Preprint (2025).
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CoT-Valve: Length-Compressible Chain-of-Thought Tuning
[Paper]
Xinyin Ma, Guangnian Wan,
Runpeng Yu
, Gongfan Fang, and Xinchao Wang
Preprint (2025).
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Neural Phylogeny: Fine-Tuning Relationship Detection among Neural Networks
[Paper]
Runpeng Yu
and Xinchao Wang.
Accepted by ICLR (2025).
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Attention Prompting on Image for Large Vision-Language Models
[Paper]
Runpeng Yu
, Weihao Yu and Xinchao Wang.
Accepted by ECCV (2024).
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Neural Lineage
[Paper]
Runpeng Yu
,and Xinchao Wang.
Accepted as CVPR (2024) Oral.
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Generator Born from Classifier
[Paper]
Runpeng Yu
,and Xinchao Wang.
Accepted by NeurIPS (2023).
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Distribution Shift Inversion for Out-of-Distribution Prediction
[Paper]
Runpeng Yu
, Songhua Liu, Xingyi Yang, and Xinchao Wang.
Accepted by CVPR (2023).
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Regularization Penalty Optimization for Addressing Data Quality Variance in OoD
Algorithms
[Paper]
Runpeng Yu
, Hong Zhu, Kaican Li, Lanqing Hong, Rui Zhang, Nanyang Ye, Shao-Lun Huang and
Xiuqiang He.
Accepted by AAAI (2022).
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A Spectral Perspective On Graph Data Augmentation For Graph Classification
[Paper]
Yutong Xia*, Runpeng Yu*
, Yuxuan Liang, Xavier Bresson, Xinchao Wang and Roger Zimmermannand
Accepted by AAAI (2025).
Education
Teaching Experience
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Fall 2024, Spring 2024, Fall 2023, Spring 2023. TA for EE2211 Introduction to Machine Learning at NUS, given by Prof. Xinchao Wang .
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Fall 2021, Spring 2021, Fall 2020. TA for Random Process at TBSI, given by Prof. Ercan Engin Kuruoğlu .
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