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FLIN: A Flexible Natural Language Interface for Web Navigation

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arxiv 2010.12844 v2 pith:4UQP2RXK submitted 2020-10-24 cs.CL cs.AI

classification cs.CLcs.AI
keywords flinwebsitesadaptnavigationableactionsdifferentflexibly
verification ladder T0 review T1 audit T2 compute T3 formal

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AI assistants can now carry out tasks for users by directly interacting with website UIs. Current semantic parsing and slot-filling techniques cannot flexibly adapt to many different websites without being constantly re-trained. We propose FLIN, a natural language interface for web navigation that maps user commands to concept-level actions (rather than low-level UI actions), thus being able to flexibly adapt to different websites and handle their transient nature. We frame this as a ranking problem: given a user command and a webpage, FLIN learns to score the most relevant navigation instruction (involving action and parameter values). To train and evaluate FLIN, we collect a dataset using nine popular websites from three domains. Our results show that FLIN was able to adapt to new websites in a given domain.

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