collaborators

19 papers

cs.CV2026

The Many Senses of Visual Similarity: A Text-Prompted Image Perceptual Metric

Sheng-Yu Wang, Yotam Nitzan, Aaron Hertzmann +4

Human visual similarity judgments are context-dependent. For example, two images may be similar in shape but distinct in color. Existing perceptual similarity metrics, however, col…

cs.CV2026

Autoregressive Modeling of Film with Applications in Video Montage

Marcelo Sandoval-Castañeda, Fabian Caba Heilbron, Shiry Ginosar +5

FilmGPT is an autoregressive transformer trained on a large movie corpus to learn the statistical patterns of film editing and select existing raw shots to create coherent video mo…

cs.CV2026

The FID Lottery: Quantifying Hidden Randomness in Generative-Model Evaluation

Nicolas Dufour, Alexei A. Efros, Patrick Pérez

The Frechet Inception Distance (FID) is the de facto arbiter of image generation, yet most papers report just a single number from a single trained model using a single sampling se…

cs.LG2026

Neuron Populations Exhibit Divergent Selectivity with Scale

Amil Dravid, Yasaman Bahri, Alexei A. Efros +1

We investigate whether neuron populations within neural networks evolve predictably with scale, extending scaling laws beyond macroscopic observables such as loss. To probe this qu…

cs.CV2026

Back into Plato's Cave: Examining Cross-modal Representational Convergence at Scale

A. Sophia Koepke, Daniil Zverev, Shiry Ginosar +1

The Platonic Representation Hypothesis suggests that neural networks trained on different modalities (e.g., text and images) align and eventually converge toward the same represent…

cs.CV2026

It's Never Too Late: Noise Optimization for Collapse Recovery in Trained Diffusion Models

Anne Harrington, A. Sophia Koepke, Shyamgopal Karthik +2

Contemporary text-to-image models exhibit a surprising degree of mode collapse, as can be seen when sampling several images given the same text prompt. Previous work has attempted…