3 papers
cs.LG2026
What should post-training optimize? A test-time scaling law perspective
Muheng Li, Jian Qian, Wenlong Mou
Large language models are increasingly deployed with test-time strategies: sample responses, score them with a reward model or verifier, and return the best. This deployment ru…
cs.CV2024
Learning Dual-Level Deformable Implicit Representation for Real-World Scale Arbitrary Super-Resolution
Zhiheng Li, Muheng Li, Jixuan Fan +4
Scale arbitrary super-resolution based on implicit image function gains increasing popularity since it can better represent the visual world in a continuous manner. However, existi…
cs.CV2024
Sine Wave Normalization for Deep Learning-Based Tumor Segmentation in CT/PET Imaging
Jintao Ren, Muheng Li, Stine Sofia Korreman
This report presents a normalization block for automated tumor segmentation in CT/PET scans, developed for the autoPET III Challenge. The key innovation is the introduction of the…