MRQA 2019 shared task: Evaluating generalization in reading comprehension
We present the results of the Machine Reading for Question Answering (MRQA) 2019
shared task on evaluating the generalization capabilities of reading comprehension …
shared task on evaluating the generalization capabilities of reading comprehension …
MOCHA: A dataset for training and evaluating generative reading comprehension metrics
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 …
allowing for open-ended questions with few restrictions on possible answers. However …
Generalizing question answering system with pre-trained language model fine-tuning
With a large number of datasets being released and new techniques being proposed,
Question answering (QA) systems have witnessed great breakthroughs in reading …
Question answering (QA) systems have witnessed great breakthroughs in reading …
DROP: A reading comprehension benchmark requiring discrete reasoning over paragraphs
Reading comprehension has recently seen rapid progress, with systems matching humans
on the most popular datasets for the task. However, a large body of work has highlighted the …
on the most popular datasets for the task. However, a large body of work has highlighted the …
A multi-type multi-span network for reading comprehension that requires discrete reasoning
Rapid progress has been made in the field of reading comprehension and question
answering, where several systems have achieved human parity in some simplified settings …
answering, where several systems have achieved human parity in some simplified settings …
R4C: A benchmark for evaluating RC systems to get the right answer for the right reason
Recent studies have revealed that reading comprehension (RC) systems learn to exploit
annotation artifacts and other biases in current datasets. This prevents the community from …
annotation artifacts and other biases in current datasets. This prevents the community from …
Learning to ask unanswerable questions for machine reading comprehension
Machine reading comprehension with unanswerable questions is a challenging task. In this
work, we propose a data augmentation technique by automatically generating relevant …
work, we propose a data augmentation technique by automatically generating relevant …
Improving machine reading comprehension with general reading strategies
Reading strategies have been shown to improve comprehension levels, especially for
readers lacking adequate prior knowledge. Just as the process of knowledge accumulation …
readers lacking adequate prior knowledge. Just as the process of knowledge accumulation …
MultiQA: An empirical investigation of generalization and transfer in reading comprehension
A large number of reading comprehension (RC) datasets has been created recently, but little
analysis has been done on whether they generalize to one another, and the extent to which …
analysis has been done on whether they generalize to one another, and the extent to which …
Qanet: Combining local convolution with global self-attention for reading comprehension
Current end-to-end machine reading and question answering (Q\&A) models are primarily
based on recurrent neural networks (RNNs) with attention. Despite their success, these …
based on recurrent neural networks (RNNs) with attention. Despite their success, these …