text: Arya McCarthy gave a hybrid talk at the NLP Seminar on Friday, Sep 30 from 11am-12pm PST. This talk was held in person in South Hall 202.
  Title: Kilolanguage Learning, Projection, and Translation
  Abstract: The breadth of information digitized in the world’s languages gives opportunities for linguistic insights and computational tools with pan-lingual perspective. We can achieve this by projecting lexical information across language, either at the type or token level. First, we project information between thousands of languages at the type level to investigate the classic color word hypotheses of Berlin and Kay. Applying fourteen computational linguistic measures of color word basicness/secondariness, we find cross-linguistic credence and shed additional nuance. Second, we project information between thousands of languages at the token level to create fine-grained morphological analyzers and generators. We show applications to pronoun clusivity and multilingual MT. Finally, we produce morphological tools grounded in UniMorph that improve on strong initial models and generalize across languages.
  Bio: Arya McCarthy is a Ph.D. candidate at Johns Hopkins University, working on massively multilingual natural language processing. He is advised by David Yarowsky in the Center for Language and Speech Processing; his work is funded by DARPA LORELEI, the International Olympic Committee, and the American Political Science Association (APSA). His work focuses on improving translation and computational modeling of rare languages. Primarily, he approaches this through weakly supervised natural language processing at the scale of 1000s of languages. Previously, Arya has spent time at Google, Duolingo, Facebook, Harvard University, and the University of Edinburgh. Arya is the PI for an APSA grant geared toward better integrating computational and social sciences. In this effort, he is partnering with Tom Lippincott, Kathy McKeown, David Mimno, Philip Resnik, and Noah Smith.
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  Recent Meetings
  Oct 21, Jeff Wu, Training models to critique themselves
  Oct 14, Alex Tamkin, Self-Supervised Learning for the Real World
  Sept 30, Arya McCarthy, Kilolanguage Learning, Projection, and Translation
  Fall 2022 Speaker Schedule
  April 29, Ethan Perez, Aligning Language Models with Human Preferences
  May 6, Katie Stasaski, Diversity in Dialogue Generation
  April 8, Divyansh Kaushik, Robustifying NLP with Humans in the Loop
  April 1, Gašper Beguš, Cognitive modeling, neural network interpretability, and GANs
  March 4, Nasrin Mostafazadeh, “How far have we come in giving our NLU systems common sense?”
  Dec 14: Dora Demszky, Using Natural Language Processing to Support Equitable and Student-Centered Education
  Dec 3: Maria Antoniak, Modeling Personal Experiences Shared in Online Communities
  Aug 20: Ashique KhudaBukhsh, Novel Frameworks for Quantifying Political Polarization and Mitigating Hate Speech