16 citations · 26 across the 8 of their papers we have counts for
8 papers
Attention to Mamba: A Recipe for Cross-Architecture Distillation
Abhinav Moudgil, Ningyuan Huang, Eeshan Gunesh Dhekane +3
State Space Models (SSMs) such as Mamba have become a popular alternative to Transformer models, due to their reduced memory consumption and higher throughput at generation compare…
Whispering Experts: Neural Interventions for Toxicity Mitigation in Language Models
Xavier Suau, Pieter Delobelle, Katherine Metcalf +4
An important issue with Large Language Models (LLMs) is their undesired ability to generate toxic language. In this work, we show that the neurons responsible for toxicity can be d…
DeepPCR: Parallelizing Sequential Operations in Neural Networks
Federico Danieli, Miguel Sarabia, Xavier Suau +2
Parallelization techniques have become ubiquitous for accelerating inference and training of deep neural networks. Despite this, several operations are still performed in a sequent…
Interpreting CLIP: Insights on the Robustness to ImageNet Distribution Shifts
Jonathan Crabbé, Pau Rodríguez, Vaishaal Shankar +2
What distinguishes robust models from non-robust ones? While for ImageNet distribution shifts it has been shown that such differences in robustness can be traced back predominantly…
The Role of Entropy and Reconstruction in Multi-View Self-Supervised Learning
Borja Rodríguez-Gálvez, Arno Blaas, Pau Rodríguez +5
The mechanisms behind the success of multi-view self-supervised learning (MVSSL) are not yet fully understood. Contrastive MVSSL methods have been studied through the lens of InfoN…
A novel Machine-Learning method for spin classification of neutron resonances
G. P. A. Nobre, D. A. Brown, S. J. Hollick +2
The performance of nuclear reactors and other nuclear systems depends on a precise understanding of the neutron interaction cross sections for materials used in these systems. Thes…
Continual Learning with Foundation Models: An Empirical Study of Latent Replay
Oleksiy Ostapenko, Timothee Lesort, Pau Rodríguez +4
Rapid development of large-scale pre-training has resulted in foundation models that can act as effective feature extractors on a variety of downstream tasks and domains. Motivated…
SSR: Semi-supervised Soft Rasterizer for single-view 2D to 3D Reconstruction
Issam Laradji, Pau Rodríguez, David Vazquez +1
Recent work has made significant progress in learning object meshes with weak supervision. Soft Rasterization methods have achieved accurate 3D reconstruction from 2D images with v…