Presented By: Michigan Institute for Data Science
MIDAS Seminar Series and Michigan AI Initiative Co-Present: Mona Diab, Computer Science, George Washington University
FAITHFULNESS IN NATURAL LANGUAGE GENERATION IN AN ERA OF HEIGHTENED ETHICAL AI AWARENESS: OPPORTUNITIES FOR MT
Advances in machine learning have led to quite fluent natural language generation technologies. Most of our current optimizations and evaluations focus on accuracy in output. Faithful generation is considered a nice to have, a luxury. In this talk I make the argument that faithful generation is crucial to our generation technologies especially given the scale and impact NLP technologies have on people’s lives.
Mona Diab is a Full Professor of Computer Science at the George Washington University where she directs the Care4Lang NLP lab. She is also Research Scientist with Facebook AI. She conducts research in Statistical Natural Language Processing (NLP) is a rapidly growing, exciting field of research in artificial intelligence and computer science. Interdisciplinarity is inherent to NLP, drawing on the fields of computer algorithms, software engineering, statistics, machine learning, linguistics, pragmatics, information technology, etc. In NLP, researchers model language and its use, and build both analytical models and predictive ones. In Professor Diab’s NLP lab, they address problems in social media processing, building robust enabling technologies such as syntactic and semantic processing tools for written texts in different languages, information extraction tools for large data, multilingual processing, machine translation, and computational sociolinguistic processing. Professor Diab has a special interest in Arabic NLP, where the emphasis has been on investigating Arabic dialect processing where there are very few available automated resources.
Mona Diab is a Full Professor of Computer Science at the George Washington University where she directs the Care4Lang NLP lab. She is also Research Scientist with Facebook AI. She conducts research in Statistical Natural Language Processing (NLP) is a rapidly growing, exciting field of research in artificial intelligence and computer science. Interdisciplinarity is inherent to NLP, drawing on the fields of computer algorithms, software engineering, statistics, machine learning, linguistics, pragmatics, information technology, etc. In NLP, researchers model language and its use, and build both analytical models and predictive ones. In Professor Diab’s NLP lab, they address problems in social media processing, building robust enabling technologies such as syntactic and semantic processing tools for written texts in different languages, information extraction tools for large data, multilingual processing, machine translation, and computational sociolinguistic processing. Professor Diab has a special interest in Arabic NLP, where the emphasis has been on investigating Arabic dialect processing where there are very few available automated resources.
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