468 citations · 476 across the 4 of their papers we have counts for
7 papers
Cheap and Good? Simple and Effective Data Augmentation for Low Resource Machine Reading
Hoang Van, Vikas Yadav, Mihai Surdeanu
We propose a simple and effective strategy for data augmentation for low-resource machine reading comprehension (MRC). Our approach first pretrains the answer extraction components…
Towards Robust Neural Retrieval Models with Synthetic Pre-Training
Revanth Gangi Reddy, Vikas Yadav, Md Arafat Sultan +4
Recent work has shown that commonly available machine reading comprehension (MRC) datasets can be used to train high-performance neural information retrieval (IR) systems. However,…
Unsupervised Alignment-based Iterative Evidence Retrieval for Multi-hop Question Answering
Vikas Yadav, Steven Bethard, Mihai Surdeanu
Evidence retrieval is a critical stage of question answering (QA), necessary not only to improve performance, but also to explain the decisions of the corresponding QA method. We i…
Quick and (not so) Dirty: Unsupervised Selection of Justification Sentences for Multi-hop Question Answering
Vikas Yadav, Steven Bethard, Mihai Surdeanu
We propose an unsupervised strategy for the selection of justification sentences for multi-hop question answering (QA) that (a) maximizes the relevance of the selected sentences, (…
A Survey on Recent Advances in Named Entity Recognition from Deep Learning models
Vikas Yadav, Steven Bethard
Named Entity Recognition (NER) is a key component in NLP systems for question answering, information retrieval, relation extraction, etc. NER systems have been studied and develope…
Multi-class Hierarchical Question Classification for Multiple Choice Science Exams
Dongfang Xu, Peter Jansen, Jaycie Martin +5
Prior work has demonstrated that question classification (QC), recognizing the problem domain of a question, can help answer it more accurately. However, developing strong QC algor…