Research - Papers
Explore a selection of our published work on a variety of key research challenges in AI.
Modelling kidney disease using ontology: insights from the Kidney Precision Medicine Project
An important need exists to better understand and stratify kidney disease according to its underlying pathophysiology in order to develop more precise and effective therapeutic agents. National…
Span-based Semantic Parsing for Compositional Generalization
Despite the success of sequence-tosequence (seq2seq) models in semantic parsing, recent work has shown that they fail in compositional generalization, i.e., the ability to generalize to new…
GFDL SHiELD: A Unified System for Weather-to-Seasonal Prediction
We present the System for High-resolution prediction on Earth-to-Local Domains (SHiELD), an atmosphere model developed by the Geophysical Fluid Dynamics Laboratory (GFDL) coupling the nonhydrostatic…
What Does My QA Model Know? Devising Controlled Probes using Expert Knowledge
Open-domain question answering (QA) is known to involve several underlying knowledge and reasoning challenges, but are models actually learning such knowledge when trained on benchmark tasks? To…
Reading Akkadian cuneiform using natural language processing
In this paper we present a new method for automatic transliteration and segmentation of Unicode cuneiform glyphs using Natural Language Processing (NLP) techniques. Cuneiform is one of the earliest…
AdaWISH: Faster Discrete Integration via Adaptive Quantiles
Discrete integration in a high dimensional space of $n$ variables poses fundamental challenges. The WISH algorithm reduces the intractable discrete integration problem into $n$ optimization queries…
AllenAct: A Framework for Embodied AI Research
The domain of Embodied AI, in which agents learn to complete tasks through interaction with their environment from egocentric observations, has experienced substantial growth with the advent of deep…
VisualCOMET: Reasoning About the Dynamic Context of a Still Image
Even from a single frame of a still image, people can reason about the dynamic story of the image before, after, and beyond the frame. For example, given an image of a man struggling to stay afloat…
Grounded Situation Recognition
We introduce Grounded Situation Recognition (GSR), a task that requires producing structured semantic summaries of images describing: the primary activity, entities engaged in the activity with…
A Cordial Sync: Going Beyond Marginal Policies for Multi-Agent Embodied Tasks
Autonomous agents must learn to collaborate. It is not scalable to develop a new centralized agent every time a task’s difficulty outpaces a single agent’s abilities. While multi-agent collaboration…