16 citations · 17 across the 5 of their papers we have counts for
6 papers
Scaling Inherently Interpretable Language Models
Guide Labs Team, Andreas Madsen, Aya Abdelsalam Ismail +7
Interpretability is often treated as a tax on capability: language models are trained as opaque systems, then explained after the fact, with methods whose reliability is difficult…
GitChameleon 2.0: Evaluating AI Code Generation Against Python Library Version Incompatibilities
Diganta Misra, Nizar Islah, Victor May +9
The rapid evolution of software libraries poses a considerable hurdle for code generation, necessitating continuous adaptation to frequent version updates while preserving backward…
Channel-Selective Normalization for Label-Shift Robust Test-Time Adaptation
Pedro Vianna, Muawiz Chaudhary, Paria Mehrbod +5
Deep neural networks have useful applications in many different tasks, however their performance can be severely affected by changes in the data distribution. For example, in the b…
Simulated Annealing in Early Layers Leads to Better Generalization
Amirmohammad Sarfi, Zahra Karimpour, Muawiz Chaudhary +4
Recently, a number of iterative learning methods have been introduced to improve generalization. These typically rely on training for longer periods of time in exchange for improve…
Parametric Scattering Networks
Shanel Gauthier, Benjamin Thérien, Laurent Alsène-Racicot +5
The wavelet scattering transform creates geometric invariants and deformation stability. In multiple signal domains, it has been shown to yield more discriminative representations…
Kymatio: Scattering Transforms in Python
Mathieu Andreux, Tomás Angles, Georgios Exarchakis +15
The wavelet scattering transform is an invariant signal representation suitable for many signal processing and machine learning applications. We present the Kymatio software packag…