5 citations · 7 across the 5 of their papers we have counts for
6 papers
Understanding Metrics for Paraphrasing
Omkar Patil, Rahul Singh, Tarun Joshi
Paraphrase generation is a difficult problem. This is not only because of the limitations in text generation capabilities but also due that to the lack of a proper definition of wh…
Document Automation Architectures and Technologies: A Survey
Mohammad Ahmadi Achachlouei, Omkar Patil, Tarun Joshi +1
This paper surveys the current state of the art in document automation (DA). The objective of DA is to reduce the manual effort during the generation of documents by automatically…
Self-interpretable Convolutional Neural Networks for Text Classification
Wei Zhao, Rahul Singh, Tarun Joshi +2
Deep learning models for natural language processing (NLP) are inherently complex and often viewed as black box in nature. This paper develops an approach for interpreting convolut…
Robustness Tests of NLP Machine Learning Models: Search and Semantically Replace
Rahul Singh, Karan Jindal, Yufei Yu +4
This paper proposes a strategy to assess the robustness of different machine learning models that involve natural language processing (NLP). The overall approach relies upon a Sear…
Recent Trends in the Use of Deep Learning Models for Grammar Error Handling
Mina Naghshnejad, Tarun Joshi, Vijayan N. Nair
Grammar error handling (GEH) is an important topic in natural language processing (NLP). GEH includes both grammar error detection and grammar error correction. Recent advances in…
Model Robustness with Text Classification: Semantic-preserving adversarial attacks
Rahul Singh, Tarun Joshi, Vijayan N. Nair +1
We propose algorithms to create adversarial attacks to assess model robustness in text classification problems. They can be used to create white box attacks and black box attacks w…