Is a Video worth n n Images? A Highly Efficient Approach to Transformer-based Video Question Answering - ACL Anthology

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Is a Video worth n n Images? A Highly Efficient Approach to Transformer-based Video Question Answering

Chenyang Lyu, Tianbo Ji, Yvette Graham, Jennifer Foster

Anthology ID:: 2023.sustainlp-1.12
Volume:: Proceedings of The Fourth Workshop on Simple and Efficient Natural Language Processing (SustaiNLP)
Month:: July
Year:: 2023
Address:: Toronto, Canada (Hybrid)
Editors:: Nafise Sadat Moosavi, Iryna Gurevych, Yufang Hou, Gyuwan Kim, Young Jin Kim, Tal Schuster, Ameeta Agrawal
Venue:: sustainlp
SIG:
Publisher:: Association for Computational Linguistics
Note:
Pages:: 183–189
Language:
URL:: https://preview.aclanthology.org/build-pipeline-with-new-library/2023.sustainlp-1.12/
DOI:: 10.18653/v1/2023.sustainlp-1.12
Bibkey:
Cite (ACL):: Chenyang Lyu, Tianbo Ji, Yvette Graham, and Jennifer Foster. 2023. Is a Video worth n n Images? A Highly Efficient Approach to Transformer-based Video Question Answering. In Proceedings of The Fourth Workshop on Simple and Efficient Natural Language Processing (SustaiNLP), pages 183–189, Toronto, Canada (Hybrid). Association for Computational Linguistics.
Cite (Informal):: Is a Video worth n n Images? A Highly Efficient Approach to Transformer-based Video Question Answering (Lyu et al., sustainlp 2023)
Copy Citation:
PDF:: https://preview.aclanthology.org/build-pipeline-with-new-library/2023.sustainlp-1.12.pdf
Video:: https://preview.aclanthology.org/build-pipeline-with-new-library/2023.sustainlp-1.12.mp4

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