Kuntal Kumar Pal

TL;DR: It is shown that the Zero Component Analysis (ZCA) outperforms both the Mean Normalization and Standardization techniques for all the three networks and thus it is the most important preprocessing technique for image classification with Convolutional Neural Networks.

TL;DR: These data support the concept that proper ED evaluation can identify a large body of patients with trivial ingestions who may not require hospital observation and help generalize NLP models to a variety of unseen tasks.

TL;DR: This work introduces N ATURAL -I NSTRUCTIONS v 2, a collection of 1,600+ diverse language tasks and their expert written instructions that covers 70+ distinct task types, such as tagging, in-filling, and rewriting.

TL;DR: The authors combine state-of-the-art language models with abductive information retrieval (IR), information gain based re-ranking, passage selection and weighted scoring to achieve 72.0% accuracy.

TL;DR: This work identifies external knowledge sources, and shows that the performance further improves when a set of facts retrieved through IR is prepended to each MCQ question during both training and test phase, and presents three different modes of passing knowledge and five different models of using knowledge including the standard BERT MCQ model.