7 citations · 25 across the 24 of their papers we have counts for
4 papers · 1 filter
CAP: Correlation-Aware Pruning for Highly-Accurate Sparse Vision Models
Denis Kuznedelev, Eldar Kurtic, Elias Frantar +1
Driven by significant improvements in architectural design and training pipelines, computer vision has recently experienced dramatic progress in terms of accuracy on classic benchm…
GMP*: Well-Tuned Gradual Magnitude Pruning Can Outperform Most BERT-Pruning Methods
Eldar Kurtic, Dan Alistarh
We revisit the performance of the classic gradual magnitude pruning (GMP) baseline for large language models, focusing on the classic BERT benchmark on various popular tasks. Despi…
Vision for Bosnia and Herzegovina in Artificial Intelligence Age: Global Trends, Potential Opportunities, Selected Use-cases and Realistic Goals
Zlatan Ajanović, Emina Aličković, Aida Branković +7
Artificial Intelligence (AI) is one of the most promising technologies of the 21. century, with an already noticeable impact on society and the economy. With this work, we provide…
The Optimal BERT Surgeon: Scalable and Accurate Second-Order Pruning for Large Language Models
Eldar Kurtic, Daniel Campos, Tuan Nguyen +5
Transformer-based language models have become a key building block for natural language processing. While these models are extremely accurate, they can be too large and computation…