Visually Grounded Follow-up Questions: a Dataset of Spatial Questions Which Require Dialogue History

Tianai Dong, Alberto Testoni, Luciana Benotti, Raffaella Bernardi


Abstract
In this paper, we define and evaluate a methodology for extracting history-dependent spatial questions from visual dialogues. We say that a question is history-dependent if it requires (parts of) its dialogue history to be interpreted. We argue that some kinds of visual questions define a context upon which a follow-up spatial question relies. We call the question that restricts the context: trigger, and we call the spatial question that requires the trigger question to be answered: zoomer. We automatically extract different trigger and zoomer pairs based on the visual property that the questions rely on (e.g. color, number). We manually annotate the automatically extracted trigger and zoomer pairs to verify which zoomers require their trigger. We implement a simple baseline architecture based on a SOTA multimodal encoder. Our results reveal that there is much room for improvement for answering history-dependent questions.
Anthology ID:
2021.splurobonlp-1.3
Volume:
Proceedings of Second International Combined Workshop on Spatial Language Understanding and Grounded Communication for Robotics
Month:
August
Year:
2021
Address:
Online
Venue:
splurobonlp
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
22–31
Language:
URL:
https://aclanthology.org/2021.splurobonlp-1.3
DOI:
10.18653/v1/2021.splurobonlp-1.3
Bibkey:
Cite (ACL):
Tianai Dong, Alberto Testoni, Luciana Benotti, and Raffaella Bernardi. 2021. Visually Grounded Follow-up Questions: a Dataset of Spatial Questions Which Require Dialogue History. In Proceedings of Second International Combined Workshop on Spatial Language Understanding and Grounded Communication for Robotics, pages 22–31, Online. Association for Computational Linguistics.
Cite (Informal):
Visually Grounded Follow-up Questions: a Dataset of Spatial Questions Which Require Dialogue History (Dong et al., splurobonlp 2021)
Copy Citation:
PDF:
https://preview.aclanthology.org/ingestion-script-update/2021.splurobonlp-1.3.pdf
Video:
 https://preview.aclanthology.org/ingestion-script-update/2021.splurobonlp-1.3.mp4
Code
 tianaidong/2021splu-robonlp-vispa
Data
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