Summary of Drop: Distributionally Robust Data Pruning, by Artem Vysogorets et al.
DRoP: Distributionally Robust Data Pruningby Artem Vysogorets, Kartik Ahuja, Julia KempeFirst submitted to arxiv on:…
Summary of What Happens When Small Is Made Smaller? Exploring the Impact Of Compression on Small Data Pretrained Language Models, by Busayo Awobade et al.
What Happens When Small Is Made Smaller? Exploring the Impact of Compression on Small Data…
Summary of Spectral Graph Pruning Against Over-squashing and Over-smoothing, by Adarsh Jamadandi et al.
Spectral Graph Pruning Against Over-Squashing and Over-Smoothingby Adarsh Jamadandi, Celia Rubio-Madrigal, Rebekka BurkholzFirst submitted to…
Summary of Robust Few-shot Ensemble Learning with Focal Diversity-based Pruning, by Selim Furkan Tekin et al.
Robust Few-Shot Ensemble Learning with Focal Diversity-Based Pruningby Selim Furkan Tekin, Fatih Ilhan, Tiansheng Huang,…
Summary of Drive: Dual Gradient-based Rapid Iterative Pruning, by Dhananjay Saikumar et al.
DRIVE: Dual Gradient-Based Rapid Iterative Pruningby Dhananjay Saikumar, Blesson VargheseFirst submitted to arxiv on: 1…
Summary of Rethinking Pruning For Vision-language Models: Strategies For Effective Sparsity and Performance Restoration, by Shwai He et al.
Rethinking Pruning for Vision-Language Models: Strategies for Effective Sparsity and Performance Restorationby Shwai He, Ang…
Summary of Separate, Dynamic and Differentiable (smart) Pruner For Block/output Channel Pruning on Computer Vision Tasks, by Guanhua Ding et al.
Separate, Dynamic and Differentiable (SMART) Pruner for Block/Output Channel Pruning on Computer Vision Tasksby Guanhua…
Summary of Retrieval-enhanced Knowledge Editing in Language Models For Multi-hop Question Answering, by Yucheng Shi et al.
Retrieval-enhanced Knowledge Editing in Language Models for Multi-Hop Question Answeringby Yucheng Shi, Qiaoyu Tan, Xuansheng…
Summary of Structurally Prune Anything: Any Architecture, Any Framework, Any Time, by Xun Wang et al.
Structurally Prune Anything: Any Architecture, Any Framework, Any Timeby Xun Wang, John Rachwan, Stephan Günnemann,…
Summary of The Need For Speed: Pruning Transformers with One Recipe, by Samir Khaki and Konstantinos N. Plataniotis
The Need for Speed: Pruning Transformers with One Recipeby Samir Khaki, Konstantinos N. PlataniotisFirst submitted…