Structured Prediction in NLP -- A survey
Computation and Language
2021-10-06 v1 Artificial Intelligence
Machine Learning
Abstract
Over the last several years, the field of Structured prediction in NLP has had seen huge advancements with sophisticated probabilistic graphical models, energy-based networks, and its combination with deep learning-based approaches. This survey provides a brief of major techniques in structured prediction and its applications in the NLP domains like parsing, sequence labeling, text generation, and sequence to sequence tasks. We also deep-dived into energy-based and attention-based techniques in structured prediction, identified some relevant open issues and gaps in the current state-of-the-art research, and have come up with some detailed ideas for future research in these fields.
Keywords
Cite
@article{arxiv.2110.02057,
title = {Structured Prediction in NLP -- A survey},
author = {Chauhan Dev and Naman Biyani and Nirmal P. Suthar and Prashant Kumar and Priyanshu Agarwal},
journal= {arXiv preprint arXiv:2110.02057},
year = {2021}
}
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6 pages, 0 figures