Wenlong Deng

Open to Collaboration and Internship
My name is Deng Wenlong (邓文龙), I am a Ph.D. student in the Electrical and Computer Engineering department at the University of British Columbia, co-supervised by Prof. Xiaoxiao Li and Prof. Christos Thrampoulidis. I am broadly interested in machine learning and its application in healthcare. I have conducted research on LLM efficiency, deep learning-based medical image analysis and now I am working on improving model reasoning abilities on medical diagnosis and math solving.
Previously: I obtained my master’s degree in Electrical Engineering at EPFL in 2019, where I was fortunated been supervised by Prof. Alexandre Alahi on stereo vision. I received my bachelor’s degree in Electronic and Information Engineering (Honors) at UESTC in 2017.
news
Jun 03, 2025 | Check out our latest findings in On the Effect of Negative Gradient in Group Relative Deep Reinforcement Optimization, where we delve into the learning dynamics of GRPO and conduct an in-depth analysis of negative gradients. |
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Jun 02, 2025 | Delighted to share that I will be interning as a Research Scientist at Meta this summer. |
Apr 01, 2025 | Our paper MedReason: Eliciting Factual Medical Reasoning Steps in LLMs via Knowledge Graphs is online! We use Knowledge Graph(KG)as structured knowledge source to provide fact guidence on medical reasoning data generation. |
Feb 07, 2025 | Our work DARE the Extreme: Revisiting Delta-Parameter Pruning For Fine-Tuned Models is selected as Spotlight at ICLR, you can drop more than 99% of your delta parameters without hurt finetuned model performance! Code will be released soon. |
selected publications
- ReasoningOn the Effect of Negative Gradient in Group Relative Deep Reinforcement OptimizationarXiv preprint arXiv:2505.18830, 2025
- ReasoningMedReason: Eliciting Factual Medical Reasoning Steps in LLMs via Knowledge Graphs2025* Equal Contribution
- ICLRDARE the Extreme: Revisiting Delta-Parameter Pruning For Fine-Tuned ModelsInternational Conference on Learning Representations (spotlight 5%), 2025
- ICLRGMValuator: Similarity-based Data Valuation for Generative ModelsInternational Conference on Learning Representations, 2025* Equal Contribution
- Unlocking the Potential of Prompt-Tuning in Bridging Generalized and Personalized Federated LearningThe IEEE Conference on Computer Vision and Pattern Recognition, 2024
- MedicalLESS: Label-efficient Multi-scale Learning for Cytological Whole Slide Image ScreeningMedical Image Analysis , 2024
- MedicalOn Fairness of Medical Image Classification with Multiple Sensitive Attributes via Learning Orthogonal RepresentationsIn Information Processing in Medical Imaging (Accept rate 25%) , 2023