Research - Papers
Explore a selection of our published work on a variety of key research challenges in AI.
Information to Wisdom: Commonsense Knowledge Extraction and Compilation
Commonsense knowledge is a foundational cornerstone of artificial intelligence applications. Whereas information extraction and knowledge base construction for instance-oriented assertions, such as…
What Can You Learn from Your Muscles? Learning Visual Representation from Human Interactions
Learning effective representations of visual data that generalize to a variety of downstream tasks has been a long quest for computer vision. Most representation learning approaches rely solely on…
Formalizing Trust in Artificial Intelligence: Prerequisites, Causes and Goals of Human Trust in AI
Trust is a central component of the interaction between people and AI, in that 'incorrect' levels of trust may cause misuse, abuse or disuse of the technology. But what, precisely, is the nature of…
Gender trends in computer science authorship
A comprehensive and up-to-date analysis of Computer Science literature (2.87 million papers through 2018) reveals that, if current trends continue, parity between the number of male and female…
Learning Generalizable Visual Representations via Interactive Gameplay
A growing body of research suggests that embodied gameplay, prevalent not just in human cultures but across a variety of animal species including turtles and ravens, is critical in developing the…
Think you have Solved Direct-Answer Question Answering? Try ARC-DA, the Direct-Answer AI2 Reasoning Challenge
We present the ARC-DA dataset, a direct-answer (“open response”, “freeform”) version of the ARC (AI2 Reasoning Challenge) multiple-choice dataset. While ARC has been influential in the community,…
Paragraph-Level Commonsense Transformers with Recurrent Memory
Human understanding of narrative texts requires making commonsense inferences beyond what is stated in the text explicitly. A recent model, COMeT, can generate such inferences along several…
COMET-ATOMIC 2020: On Symbolic and Neural Commonsense Knowledge Graphs
Recent years have brought about a renewed interest in commonsense representation and reasoning in the field of natural language understanding. The development of new commonsense knowledge graphs…
Dynamic Neuro-Symbolic Knowledge Graph Construction for Zero-shot Commonsense Question Answering
Understanding narratives requires reasoning about implicit world knowledge related to the causes, effects, and states of situations described in text. At the core of this challenge is how to access…
Optimizing AI for Teamwork
In many high-stakes domains such as criminal justice, finance, and healthcare, AI systems may recommend actions to a human expert responsible for final decisions, a context known as AI-advised…