activity
20182026
collaborators

7 papers

cs.LG2026

Mind the Spike: Mechanisms and Brittleness of Visual Massive Activations in Large Vision-Language Models

Jonas Ngnawé, Yann Pequignot, Sabyasachi Sahoo +3

Large vision-language models (LVLMs) inherit massive activations from their text-only bases: spikes where a few fixed hidden channels receive values thousands of times above the ty…

stat.ML2026

A Stochastic--Geometric Theory of Scaling Laws in Grokking

Róisín Luo, Christian Gagné, Jonas Ngnawé +2

Delayed generalization (\ie~grokking) refers to the phenomenon in which a neural network fits its training data early in training but only begins to generalize after a prolonged de…

cs.LG2026

Reliability-Gated Source Anchoring for Continual Test-Time Adaptation

Vikash Singh, Debargha Ganguly, Weicong Chen +8

Continual test-time adaptation (CTTA) updates a pretrained model online on an unlabeled, non-stationary stream while anchoring it to a frozen source checkpoint. This anchor is usef…

cs.LG2025

Optimization-Induced Dynamics of Lipschitz Continuity in Neural Networks

Róisín Luo, James McDermott, Christian Gagné +2

Lipschitz continuity characterizes the worst-case sensitivity of neural networks to small input perturbations; yet its dynamics (i.e. temporal evolution) during training remains un…

cs.LG2024

A Layer Selection Approach to Test Time Adaptation

Sabyasachi Sahoo, Mostafa ElAraby, Jonas Ngnawe +3

Test Time Adaptation (TTA) addresses the problem of distribution shift by adapting a pretrained model to a new domain during inference. When faced with challenging shifts, most met…

cs.LG2024

Generalizing across Temporal Domains with Koopman Operators

Qiuhao Zeng, Wei Wang, Fan Zhou +7

In the field of domain generalization, the task of constructing a predictive model capable of generalizing to a target domain without access to target data remains challenging. Thi…

stat.ML2018

Accumulating Knowledge for Lifelong Online Learning

Changjian Shui, Ihsen Hedhli, Christian Gagné

Lifelong learning can be viewed as a continuous transfer learning procedure over consecutive tasks, where learning a given task depends on accumulated knowledge --- the so-called k…