Hi, I’m Yanru Wu (吓彦儒), a senior undergraduate at Huazhong University of Science and Technology (HUST). I am currently a research intern in the Computational Cognition, Vision, and Learning Lab at Johns Hopkins University, advised by Prof. Alan Yuille and Dr. Jieneng Chen. Previously, I worked with Prof. Yue Wang and Dr. Jiageng Mao in the Physical Superintelligence Lab at the University of Southern California, and with Prof. Yao Wan in ONE Lab at HUST.

My research focuses on building generalizable robot learning systems that connect foundation models with physical feedback and policy adaptation. I am particularly interested in cross-platform robot learning, high-precision and contact-rich manipulation, and learning from visual, force/torque, and tactile signals.

News

  • 2026.07Joined the CCVL Lab at Johns Hopkins University as a research intern.
  • 2026.03Released our Large Reward Models preprint on visual reward generation for robot policy refinement.
  • 2025.05One paper was accepted to Findings of ACL 2025.
  • 2025.01One paper was accepted to ICLR 2025 as a Spotlight.

Publications

Under Review
Overview of Large Reward Models

Large Reward Models: Generalizable Online Robot Reward Generation with Vision-Language Models

Yanru Wu, Weiduo Yuan, Ang Qi, Vitor Guizilini, Jiageng Mao, Yue Wang

Under review; IROS 2026 Workshop on AI Meets Autonomy

A vision-language-model-based framework that generates online visual rewards for robot policy refinement across tasks and environments.

ICLR 2025 Spotlight
Overview of the Interleaved Scene Graph benchmark

Interleaved Scene Graph for Interleaved Text-and-Image Generation Assessment

Dongping Chen*, Ruoxi Chen*, Shu Pu*, Zhaoyi Liu*, Yanru Wu*, Caixi Chen*, Benlin Liu, Yue Huang, Yao Wan, Pan Zhou, Ranjay Krishna

International Conference on Learning Representations (ICLR), 2025 Ā· Spotlight

A benchmark centered on interleaved scene graphs for evaluating models that generate and reason across alternating text and images.

ACL 2025 Findings
Overview of the analysis of LLM influence in academia

The Impact of Large Language Models in Academia: From Writing to Speaking

Mingmeng Geng*, Caixi Chen*, Yanru Wu*, Yao Wan, Pan Zhou, Dongping Chen

Findings of the Association for Computational Linguistics (ACL), 2025

A large-scale analysis of how LLM adoption is changing linguistic patterns in academic papers and conference talks.

Research Experience

Education

Huazhong University of Science and Technology

Sep 2023 – Jun 2027 Wuhan, China
B.Eng. in Electronic and Information Engineering, Honored Class

Service

  • Reviewer, CVPR Workshop on Synthetic Data for Computer Vision (SynData4CV)