Degree
Master of Science in Computer Science
Department
Department of Computer Science
Faculty / School
Faculty of Computer Sciences (FCS)
Date of Submission
2020-06-30
Supervisor
Dr. Sajjad Haider, Professor, Department of Computer Science
Document type
MSCS Survey Report
Keywords
Commonsense, Natural language Processing, Artificial Intelligence, Machine learning, Coreference resolution, Event explanation, Reasoning, Rationalization, Multiple-choice question
Abstract
Commonsense reasoning is an active area of research in Natural Language Processing (NLP). Tasks and datasets involved in this problem are designed to ensure that the corresponding models go beyond pattern recognition and incorporate commonsense knowledge. This research survey presents five commonsense tasks: Winograd Schema Challenge, Winograd NLI (WNLI), Situations with Adversarial Generations (SWAG), CommonsenseQA (CQA), and Event2Mind. The survey examines nine papers, including models, experiments, results, and datasets. The survey also compares the models in terms of performance on the relevant tasks and recommends future direction. This work aims to provide readers a profound understanding of commonsense tasks in NLP and the relevant models which solve them.
Recommended Citation
Qureshi, M. F. (2020). Commonsense reasoning in NLP (Unpublished MSCS survey report). Institute of Business Administration, Pakistan. Retrieved from https://ir.iba.edu.pk/survey-reports-mscs/14
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