Research - Papers
Explore a selection of our published work on a variety of key research challenges in AI.
LIMEADE: From AI Explanations to Advice Taking
Research in human-centered AI has shown the benefits of systems that can explain their predictions. Methods that allow an AI to take advice from humans in response to explanations are similarly…
Text-based NP Enrichment
Understanding the relations between entities denoted by NPs in text is a critical part of human-like natural language understanding. However, only a fraction of such relations is covered by NLP…
Hallett‐Mossop Rime Splintering Dims Cumulus Clouds Over the Southern Ocean: New Insight From Nudged Global Storm‐Resolving Simulations
In clouds containing both liquid and ice with temperatures between −3°C and −8°C, liquid droplets collide with large ice crystals, freeze, and shatter, producing a plethora of small ice splinters.…
Paper Plain: Making Medical Research Papers Approachable to Healthcare Consumers with Natural Language Processing
When seeking information not covered in patient-friendly documents, like medical pamphlets, healthcare consumers may turn to the research literature. Reading medical papers, however, can be a…
One-Shot Labeling for Automatic Relevance Estimation
Dealing with unjudged documents ("holes") in relevance assessments is a perennial problem when evaluating search systems with offline experiments. Holes can reduce the apparent effectiveness of…
A Search Engine for Discovery of Scientific Challenges and Directions
Keeping track of scientific challenges, advances and emerging directions is a fundamental part of research. However, researchers face a flood of papers that hinders discovery of important knowledge.…
Knowledge is Power: Symbolic Knowledge Distillation, Commonsense Morality, & Multimodal Script Knowledge
Scale appears to be the winning recipe in today's AI leaderboards. And yet, extreme-scale neural models are still brittle to make errors that are often nonsensical and even counterintuitive. In this…
A Controllable Model of Grounded Response Generation
Current end-to-end neural conversation models inherently lack the flexibility to impose semantic control in the response generation process. This control is essential to ensure that users' semantic…
Multi-Modal Answer Validation for Knowledge-Based VQA
The problem of knowledge-based visual question answering involves answering questions that require external knowledge in addition to the content of the image. Such knowledge typically comes in a…
Pushing the Limits of Rule Reasoning in Transformers through Natural Language Satisfiability
Investigating the reasoning abilities of transformer models, and discovering new challenging tasks for them, has been a topic of much interest. Recent studies have found these models to be…