11 papers
A Unifying Framework for Concept-Based Representational Similarity
Grégoire Dhimoïla, Victor Boutin, Agustin Martin Picard +2
Learned representations across models and modalities often exhibit striking structural similarities, suggesting shared underlying concept decompositions. However, concept alignment…
Not Too Generative, Not Too Discriminative: The Human Alignment Sweet Spot
Jorge Chang Ortega, Bastien Le Lan, Thomas Serre +1
A central question in computational vision is whether human-like visual representations are better explained by discriminative or generative learning. Existing comparisons, however…
Object-Level Explanations for Image Geolocation Models: a GeoGuessr use-case
Emilie Durrieu, Christophe Hurter, Philippe Muller +1
When humans play geolocation games such as GeoGuessr, they rely on concrete visual cues, such as road markings, vegetation, or architectural details, to infer where an image was ca…
Choosing the right basis for interpretability: Psychophysical comparison between neuron-based and dictionary-based representations
Julien Colin, Lore Goetschalckx, Thomas Fel +3
Interpretability research often adopts a neuron-centric lens, treating individual neurons as the fundamental units of explanation. However, neuron-level explanations can be undermi…
Cross-Modal Redundancy and the Geometry of Vision-Language Embeddings
Grégoire Dhimoïla, Thomas Fel, Victor Boutin +1
Vision-language models (VLMs) align images and text with remarkable success, yet the geometry of their shared embedding space remains poorly understood. To probe this geometry, we…
Follow the Energy, Find the Path: Riemannian Metrics from Energy-Based Models
Louis Béthune, David Vigouroux, Yilun Du +3
What is the shortest path between two data points lying in a high-dimensional space? While the answer is trivial in Euclidean geometry, it becomes significantly more complex when t…