17 citations · 34 across the 5 of their papers we have counts for
5 papers
Bridging the Data Provenance Gap Across Text, Speech and Video
Shayne Longpre, Nikhil Singh, Manuel Cherep +40
Progress in AI is driven largely by the scale and quality of training data. Despite this, there is a deficit of empirical analysis examining the attributes of well-established data…
From Text to Pose to Image: Improving Diffusion Model Control and Quality
Clément Bonnet, Ariel N. Lee, Franck Wertel +3
In the last two years, text-to-image diffusion models have become extremely popular. As their quality and usage increase, a major concern has been the need for better output contro…
Consent in Crisis: The Rapid Decline of the AI Data Commons
Shayne Longpre, Robert Mahari, Ariel Lee +46
General-purpose artificial intelligence (AI) systems are built on massive swathes of public web data, assembled into corpora such as C4, RefinedWeb, and Dolma. To our knowledge, we…
Platypus: Quick, Cheap, and Powerful Refinement of LLMs
Ariel N. Lee, Cole J. Hunter, Nataniel Ruiz
We present , a family of fine-tuned and merged Large Language Models (LLMs) that achieves the strongest performance and currently stands at first place in Huggin…
Hardwiring ViT Patch Selectivity into CNNs using Patch Mixing
Ariel N. Lee, Sarah Adel Bargal, Janavi Kasera +3
Vision transformers (ViTs) have significantly changed the computer vision landscape and have periodically exhibited superior performance in vision tasks compared to convolutional n…