Research - Papers
Explore a selection of our published work on a variety of key research challenges in AI.
Faking Fake News for Real Fake News Detection: Propaganda-loaded Training Data Generation
While there has been a lot of research and many recent advances in neural fake news detection, defending against human-written disinformation remains underexplored. Upon analyzing current approaches…
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, healthcare consumers may turn to the research literature. Reading medical papers, however, can be a challenging experience. To…
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…