FLIN: A Flexible Natural Language Interface for Web Navigation

Sahisnu Mazumder, Oriana Riva


Abstract
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.
Anthology ID:
2021.naacl-main.222
Volume:
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Month:
June
Year:
2021
Address:
Online
Editors:
Kristina Toutanova, Anna Rumshisky, Luke Zettlemoyer, Dilek Hakkani-Tur, Iz Beltagy, Steven Bethard, Ryan Cotterell, Tanmoy Chakraborty, Yichao Zhou
Venue:
NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
2777–2788
Language:
URL:
https://aclanthology.org/2021.naacl-main.222
DOI:
10.18653/v1/2021.naacl-main.222
Bibkey:
Cite (ACL):
Sahisnu Mazumder and Oriana Riva. 2021. FLIN: A Flexible Natural Language Interface for Web Navigation. In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 2777–2788, Online. Association for Computational Linguistics.
Cite (Informal):
FLIN: A Flexible Natural Language Interface for Web Navigation (Mazumder & Riva, NAACL 2021)
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