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  • NL SEMINAR Predictor Guided Controlled Generation

    Thu, Jul 22, 2021 @ 11:10 AM - 12:10 PM

    Information Sciences Institute

    Conferences, Lectures, & Seminars

    Speaker: Kevin Yang, UC Berkeley

    Talk Title: Predictor Guided Controlled Generation

    Abstract: REMINDER Meeting hosts only admit guests that they know to the Zoom meeting. Hence, you're highly encouraged to use your USC account to sign into Zoom. If you're an outside visitor, please inform nlg DASH seminar DASH admin2 AT isi.edu beforehand so we'll be aware of your attendance and let you in.


    I will present two works on controlled generation, with a shared theme of using predictors to guide a generator. Future Discriminators for Generation FUDGE is a flexible and modular method for controlled text generation, which learns an attribute predictor operating on a partial sequence, and uses this predictor's outputs to adjust a base generator's original probabilities with no need for re-training or fine-tuning. Switching domains, I will also present Improving Molecular Design by Stochastic Iterative Target Augmentation, a self-training approach for using a strong attribute predictor to guide the training of a generator in a semi-supervised manner. Overall, we find that these predictor-guided approaches to controlled generation substantially outperform prior methods in several text generation tasks, as well as in molecular design and program synthesis.

    Biography: Kevin Yang is a rising third-year PhD student at UC Berkeley advised by Dan Klein within Berkeley NLP and BAIR. He is broadly interested in AI in the context of language and game-playing, particularly in designing more modular and/or language-controllable agents. He is also interested in neural architectures for structured domains such as chemistry. Previously, Kevin worked with Regina Barzilay during his undergrad and M.Eng. at MIT, on natural language processing and chemistry applications of deep learning, especially graph convolutional networks.

    Host: Jon May and Mozhdeh Gheini

    More Info: https://nlg.isi.edu/nl-seminar/

    Webcast: https://youtu.be/3aT3dNLyzec

    Location: Information Science Institute (ISI) - Virtual Only

    WebCast Link: https://youtu.be/3aT3dNLyzec

    Audiences: Everyone Is Invited

    Contact: Petet Zamar

    Event Link: https://nlg.isi.edu/nl-seminar/


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