ICML 2024 "model pruning" Papers
7 papers found
A Provably Effective Method for Pruning Experts in Fine-tuned Sparse Mixture-of-Experts
Mohammed Nowaz Rabbani Chowdhury, Meng Wang, Kaoutar El Maghraoui et al.
ICML 2024poster
COPAL: Continual Pruning in Large Language Generative Models
Srikanth Malla, Joon Hee Choi, Chiho Choi
ICML 2024poster
How Do Nonlinear Transformers Learn and Generalize in In-Context Learning?
Hongkang Li, Meng Wang, Songtao Lu et al.
ICML 2024poster
Junk DNA Hypothesis: Pruning Small Pre-Trained Weights $\textit{Irreversibly}$ and $\textit{Monotonically}$ Impairs ``Difficult" Downstream Tasks in LLMs
Lu Yin, Ajay Jaiswal, Shiwei Liu et al.
ICML 2024poster
Outlier Weighed Layerwise Sparsity (OWL): A Missing Secret Sauce for Pruning LLMs to High Sparsity
Lu Yin, You Wu, Zhenyu Zhang et al.
ICML 2024poster
Sparsest Models Elude Pruning: An Exposé of Pruning’s Current Capabilities
Stephen Zhang, Vardan Papyan
ICML 2024poster
Unveiling the Dynamics of Information Interplay in Supervised Learning
Kun Song, Zhiquan Tan, Bochao Zou et al.
ICML 2024poster