NLP in Practice: Challenges of Language Understanding on Social Platforms
In the last several years, the field of Natural Language Processing has seen tremendous advances. Models like BERT and GPT-3 have completely changed the way practitioners operate and models are used in real-life applications. Still, there is a big gap between state-of-the-art performance on benchmarks and the performance seen on social platforms like Snapchat and Twitter, where the text is short, informal, dynamic, and lacking in context. For this talk, we will introduce some of the challenges and approaches used for text understanding unders these circumstances.
Leonardo Neves is a Principal Research Scientist at Snap Inc where he leads the Computational Social Science group. His research focuses on Natural Language Processing, specifically in leveraging additional modalities and context to improve language and behavior understanding. Leo has more than 20 publications in top-tier conferences like ACL, EMNLP, WWW, and AAAI, among others.
Before joining Snap Inc., Leonardo worked for Pivotal Software Inc., Intel, and Yelp. He earned a Master's in Intelligent Information Systems from Carnegie Mellon University and a BE in Computer and Information Engineering from Rio de Janeiro's Federal University.