11 citations · 37 across the 24 of their papers we have counts for
4 papers · 1 filter
ProCrop: Learning Aesthetic Image Cropping from Professional Compositions
Ke Zhang, Tianyu Ding, Jiachen Jiang +4
Image cropping is crucial for enhancing the visual appeal and narrative impact of photographs, yet existing rule-based and data-driven approaches often lack diversity or require an…
Learning Where and What to Restore for Composite Image Restoration
Jiachen Jiang, Tianyu Ding, Ke Zhang +5
Real-world degraded images often contain multiple co-occurring degradation types, making composite image restoration fundamentally different from the single-degradation setting ass…
DistiLLM-2: A Contrastive Approach Boosts the Distillation of LLMs
Jongwoo Ko, Tianyi Chen, Sungnyun Kim +4
Despite the success of distillation in large language models (LLMs), most prior work applies identical loss functions to both teacher- and student-generated data. These strategies…
Automatic Joint Structured Pruning and Quantization for Efficient Neural Network Training and Compression
Xiaoyi Qu, David Aponte, Colby Banbury +5
Structured pruning and quantization are fundamental techniques used to reduce the size of deep neural networks (DNNs) and typically are applied independently. Applying these techni…