University of Illinois

7 Posts

Dataset FOLIO example based on the Wild Turkey Wikipedia page
University of Illinois

Language Models Defy Logic: Large NLP models struggle with logical reasoning.

Who would disagree that, if all people are mortal and Socrates is a person, Socrates must be mortal? GPT-3, for one. Recent work shows that bigger language models are not necessarily better when it comes to logical reasoning.
Animation showing image-to-image style transfer — mapping process
University of Illinois

AI With a Sense of Style: Style Transfer Method Produces Consistent Output in Successive Video Frames

The process known as image-to-image style transfer — mapping, say, the character of a painting’s brushstrokes onto a photo — can render inconsistent results. When they apply the styles of different artists to the same target
Architecture of vision-language tasks
University of Illinois

One Model for Vision-Language: A general purpose AI for vision and language tasks.

Researchers have proposed task-agnostic architectures for image classification tasks and language tasks. New work proposes a single architecture for vision-language tasks.
Protein structures
University of Illinois

What AI Knows About Proteins: NLP systems can be used to code amino acids.

Transformer models trained on sequences of amino acids that form proteins have had success classifying and generating viable sequences. New research shows that they also capture information about protein structure.
Graphs comparing SGD + Momentum, Adam and AdaBelief
University of Illinois

Striding Toward the Minimum: A faster way to optimize the loss function for deep learning.

When you’re training a deep learning model, it can take days for an optimization algorithm to minimize the loss function. A new approach could save time.
Graphs and data related to semi-supervised learning
University of Illinois

All Examples Are Not Equal: An algorithm for improved semi-supervised learning

Semi-supervised learning — a set of training techniques that use a small number of labeled examples and a large number of unlabeled examples — typically treats all unlabeled examples the same way. But some examples are more useful for learning than others.
Information related to a convolutional neural network that predicts corn yields in fields
University of Illinois

AI on the Cob: An AI system predicted crop yields.

Deep learning research is harvesting better ways to manage farms. A convolutional neural network predicted corn yields in fields across the U.S. Midwest.

Subscribe to The Batch

Stay updated with weekly AI News and Insights delivered to your inbox