Research - Papers
Explore a selection of our published work on a variety of key research challenges in AI.
TREC-COVID: Constructing a Pandemic Information Retrieval Test Collection
TREC-COVID is a community evaluation designed to build a test collection that captures the information needs of biomedical researchers using the scientific literature during a pandemic. One of the…
TREC-COVID: Rationale and Structure of an Information Retrieval Shared Task for COVID-19
TREC-COVID is an information retrieval (IR) shared task initiated to support clinicians and clinical research during the COVID-19 pandemic. IR for pandemics breaks many normal assumptions, which can…
GenericsKB: A Knowledge Base of Generic Statements
We present a new resource for the NLP community, namely a large (3.5M+ sentence) knowledge base of *generic statements*, e.g., "Trees remove carbon dioxide from the atmosphere", collected from…
Abductive Commonsense Reasoning
Abductive reasoning is inference to the most plausible explanation. For example, if Jenny finds her house in a mess when she returns from work, and remembers that she left a window open, she can…
Explain like I am a Scientist: The Linguistic Barriers of Entry to r/science
As an online community for discussing research findings, r/science has the potential to contribute to science outreach and communication with a broad audience. Yet previous work suggests that most…
Evaluating Machines by their Real-World Language Use
There is a fundamental gap between how humans understand and use language – in openended, real-world situations – and today’s NLP benchmarks for language understanding. To narrow this gap, we…
Ranking Significant Discrepancies in Clinical Reports
Medical errors are a major public health concern and a leading cause of death worldwide. Many healthcare centers and hospitals use reporting systems where medical practitioners write a preliminary…
Oscar: Object-Semantics Aligned Pre-training for Vision-Language Tasks
Large-scale pre-training methods of learning cross-modal representations on image-text pairs are becoming popular for vision-language tasks. While existing methods simply concatenate image region…
Longformer: The Long-Document Transformer
Transformer-based models are unable to process long sequences due to their self-attention operation, which scales quadratically with the sequence length. To address this limitation, we introduce the…
TuringAdvice: A Generative and Dynamic Evaluation of Language Use
We propose TuringAdvice, a new challenge task and dataset for language understanding models. Given a written situation that a real person is currently facing, a model must generate helpful advice in…