4 papers · 1 filter
Evidence Inference 2.0: More Data, Better Models
Jay DeYoung, Eric Lehman, Ben Nye +2
How do we most effectively treat a disease or condition? Ideally, we could consult a database of evidence gleaned from clinical trials to answer such questions. Unfortunately, no s…
ERASER: A Benchmark to Evaluate Rationalized NLP Models
Jay DeYoung, Sarthak Jain, Nazneen Fatema Rajani +4
State-of-the-art models in NLP are now predominantly based on deep neural networks that are opaque in terms of how they come to make predictions. This limitation has increased inte…
Inferring Which Medical Treatments Work from Reports of Clinical Trials
Eric Lehman, Jay DeYoung, Regina Barzilay +1
How do we know if a particular medical treatment actually works? Ideally one would consult all available evidence from relevant clinical trials. Unfortunately, such results are pri…
Events Beyond ACE: Curated Training for Events
Ryan Gabbard, Jay DeYoung, Marjorie Freedman
We explore a human-driven approach to annotation, curated training (CT), in which annotation is framed as teaching the system by using interactive search to identify informative sn…