508 citations · 748 across the 20 of their papers we have counts for
21 papers
A deeper look at depth pruning of LLMs
Shoaib Ahmed Siddiqui, Xin Dong, Greg Heinrich +4
Large Language Models (LLMs) are not only resource-intensive to train but even more costly to deploy in production. Therefore, recent work has attempted to prune blocks of LLMs bas…
Identifying Layers Susceptible to Adversarial Attacks
Shoaib Ahmed Siddiqui, Thomas Breuel
In this paper, we investigate the use of pretraining with adversarial networks, with the objective of discovering the relationship between network depth and robustness. For this pu…
IamNN: Iterative and Adaptive Mobile Neural Network for Efficient Image Classification
Sam Leroux, Pavlo Molchanov, Pieter Simoens +3
Deep residual networks (ResNets) made a recent breakthrough in deep learning. The core idea of ResNets is to have shortcut connections between layers that allow the network to be m…
Hand Pose Estimation via Latent 2.5D Heatmap Regression
Umar Iqbal, Pavlo Molchanov, Thomas Breuel +2
Estimating the 3D pose of a hand is an essential part of human-computer interaction. Estimating 3D pose using depth or multi-view sensors has become easier with recent advances in…
Unsupervised Image-to-Image Translation Networks
Ming-Yu Liu, Thomas Breuel, Jan Kautz
Unsupervised image-to-image translation aims at learning a joint distribution of images in different domains by using images from the marginal distributions in individual domains.…
Sequence-to-sequence neural network models for transliteration
Mihaela Rosca, Thomas Breuel
Transliteration is a key component of machine translation systems and software internationalization. This paper demonstrates that neural sequence-to-sequence models obtain state of…