Research - Papers
Explore a selection of our published work on a variety of key research challenges in AI.
Simplified Data Wrangling with ir_datasets
Managing the data for Information Retrieval (IR) experiments can be challenging. Dataset documentation is scattered across the Internet and once one obtains a copy of the data, there are numerous…
Does the Whole Exceed its Parts? The Effect of AI Explanations on Complementary Team Performance
Many researchers motivate explainable AI with studies showing that human-AI team performance on decision-making tasks improves when the AI explains its recommendations. However, prior studies…
Augmenting Scientific Papers with Just-in-Time, Position-Sensitive Definitions of Terms and Symbols
Despite the central importance of research papers to scientific progress, they can be difficult to read. Comprehension is often stymied when the information needed to understand a passage resides…
What Do We Mean by “Accessibility Research”?: A Literature Survey of Accessibility Papers in CHI and ASSETS from 1994 to 2019
Accessibility research has grown substantially in the past few decades, yet there has been no literature review of the field. To understand current and historical trends, we created and analyzed a…
DExperts: Decoding-Time Controlled Text Generation with Experts and Anti-Experts
Despite recent advances in natural language generation, it remains challenging to control attributes of generated text. We propose DExperts: Decoding-time Experts, a decoding-time method for…
GridTools: A framework for portable weather and climate applications
Weather forecasts and climate projections are of tremendous importance for economical and societal reasons. Software implementing weather and climate models is complex to develop and hard to…
MULTIMODALQA: COMPLEX QUESTION ANSWERING OVER TEXT, TABLES AND IMAGES
When answering complex questions, people can seamlessly combine information from visual, textual and tabular sources. While interest in models that reason over multiple pieces of evidence has surged…
DeLighT: Deep and Light-weight Transformer
We introduce a very deep and light-weight transformer, DeLighT, that delivers similar or better performance than transformer-based models with significantly fewer parameters. DeLighT more…
Pushing it out of the Way: Interactive Visual Navigation
We have observed significant progress in visual navigation for embodied agents. A common assumption in studying visual navigation is that the environments are static; this is a limiting assumption.…
CODE: COMPILER-BASED NEURON-AWARE ENSEMBLE TRAINING
Deep Neural Networks (DNNs) are redefining the state-of-the-art performance in a variety of tasks like speech recognition and image classification. These impressive results are often enabled by…