Continual Learning for Grounded Instruction Generation by Observing Human Following Behavior

2022/04/06 (Wed) 12:00 (JST)

小島熙之 / Noriyuki Kojima (Cornell University)

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Noriyuki Kojima is a third-year CS Ph.D. student at Cornell University. His research focus is interactive learning for multi-modal systems. His research is supported by the Masason Fellowship.

概要

We study continual learning for natural language instruction generation, by observing human users' instruction execution. We focus on a collaborative scenario, where the system both acts and delegates tasks to human users using natural language. We compare user execution of generated instructions to the original system intent as an indication to the system's success communicating its intent. We show how to use this signal to improve the system's ability to generate instructions via contextual bandit learning. In interaction with real users, our system demonstrates dramatic improvements in its ability to generate language over time.

※トークは英語 (QAは日本語)です。

[動画] [スライド] [論文] (TACL 2021)

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