37 citations · 40 across the 5 of their papers we have counts for
5 papers
How much do language models memorize?
John X. Morris, Chawin Sitawarin, Chuan Guo +5
We propose a new method for estimating how much a model knows about a datapoint and use it to measure the capacity of modern language models. Prior studies of language model memori…
Measuring Déjà vu Memorization Efficiently
Narine Kokhlikyan, Bargav Jayaraman, Florian Bordes +2
Recent research has shown that representation learning models may accidentally memorize their training data. For example, the déjà vu method shows that for certain representation l…
An Introduction to Vision-Language Modeling
Florian Bordes, Richard Yuanzhe Pang, Anurag Ajay +38
Following the recent popularity of Large Language Models (LLMs), several attempts have been made to extend them to the visual domain. From having a visual assistant that could guid…
Déjà Vu Memorization in Vision-Language Models
Bargav Jayaraman, Chuan Guo, Kamalika Chaudhuri
Vision-Language Models (VLMs) have emerged as the state-of-the-art representation learning solution, with myriads of downstream applications such as image classification, retrieval…
Do SSL Models Have Déjà Vu? A Case of Unintended Memorization in Self-supervised Learning
Casey Meehan, Florian Bordes, Pascal Vincent +2
Self-supervised learning (SSL) algorithms can produce useful image representations by learning to associate different parts of natural images with one another. However, when taken…