168 citations · 639 across the 30 of their papers we have counts for
10 papers · 1 filter
AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts
Taylor Shin, Yasaman Razeghi, Robert L. Logan +2
The remarkable success of pretrained language models has motivated the study of what kinds of knowledge these models learn during pretraining. Reformulating tasks as fill-in-the-bl…
MOCHA: A Dataset for Training and Evaluating Generative Reading Comprehension Metrics
Anthony Chen, Gabriel Stanovsky, Sameer Singh +1
Posing reading comprehension as a generation problem provides a great deal of flexibility, allowing for open-ended questions with few restrictions on possible answers. However, pro…
MedICaT: A Dataset of Medical Images, Captions, and Textual References
Sanjay Subramanian, Lucy Lu Wang, Sachin Mehta +6
Understanding the relationship between figures and text is key to scientific document understanding. Medical figures in particular are quite complex, often consisting of several su…
Gradient-based Analysis of NLP Models is Manipulable
Junlin Wang, Jens Tuyls, Eric Wallace +1
Gradient-based analysis methods, such as saliency map visualizations and adversarial input perturbations, have found widespread use in interpreting neural NLP models due to their s…
Concealed Data Poisoning Attacks on NLP Models
Eric Wallace, Tony Z. Zhao, Shi Feng +1
Adversarial attacks alter NLP model predictions by perturbing test-time inputs. However, it is much less understood whether, and how, predictions can be manipulated with small, con…
Image Augmentations for GAN Training
Zhengli Zhao, Zizhao Zhang, Ting Chen +2
Data augmentations have been widely studied to improve the accuracy and robustness of classifiers. However, the potential of image augmentation in improving GAN models for image sy…