1 citations · 1 across the 3 of their papers we have counts for
4 papers
Capability Self-Assessment: Teaching LLMs to Know Their Limits
Haoyan Yang, Reza Shirkavand, Yukai Jin +3
The ability to recognize one's own limitations and decide whether to solve a problem or delegate is fundamental for reliable intelligent systems. Yet we show that modern large lang…
Jointly Training and Pruning CNNs via Learnable Agent Guidance and Alignment
Alireza Ganjdanesh, Shangqian Gao, Heng Huang
Structural model pruning is a prominent approach used for reducing the computational cost of Convolutional Neural Networks (CNNs) before their deployment on resource-constrained de…
Auto-Train-Once: Controller Network Guided Automatic Network Pruning from Scratch
Xidong Wu, Shangqian Gao, Zeyu Zhang +5
Current techniques for deep neural network (DNN) pruning often involve intricate multi-step processes that require domain-specific expertise, making their widespread adoption chall…
Compressing Image-to-Image Translation GANs Using Local Density Structures on Their Learned Manifold
Alireza Ganjdanesh, Shangqian Gao, Hirad Alipanah +1
Generative Adversarial Networks (GANs) have shown remarkable success in modeling complex data distributions for image-to-image translation. Still, their high computational demands…