37 citations · 113 across the 18 of their papers we have counts for
6 papers · 1 filter
CinePile: A Long Video Question Answering Dataset and Benchmark
Ruchit Rawal, Khalid Saifullah, Miquel Farré +4
Current datasets for long-form video understanding often fall short of providing genuine long-form comprehension challenges, as many tasks derived from these datasets can be succes…
Measuring Style Similarity in Diffusion Models
Gowthami Somepalli, Anubhav Gupta, Kamal Gupta +5
Generative models are now widely used by graphic designers and artists. Prior works have shown that these models remember and often replicate content from their training data durin…
What do we learn from inverting CLIP models?
Hamid Kazemi, Atoosa Chegini, Jonas Geiping +2
We employ an inversion-based approach to examine CLIP models. Our examination reveals that inverting CLIP models results in the generation of images that exhibit semantic alignment…
Object Recognition as Next Token Prediction
Kaiyu Yue, Bor-Chun Chen, Jonas Geiping +3
We present an approach to pose object recognition as next token prediction. The idea is to apply a language decoder that auto-regressively predicts the text tokens from image embed…
Battle of the Backbones: A Large-Scale Comparison of Pretrained Models across Computer Vision Tasks
Micah Goldblum, Hossein Souri, Renkun Ni +10
Neural network based computer vision systems are typically built on a backbone, a pretrained or randomly initialized feature extractor. Several years ago, the default option was an…
A Simple and Efficient Baseline for Data Attribution on Images
Vasu Singla, Pedro Sandoval-Segura, Micah Goldblum +2
Data attribution methods play a crucial role in understanding machine learning models, providing insight into which training data points are most responsible for model outputs duri…