@inproceedings{suhr-etal-2019-executing,
title = "Executing Instructions in Situated Collaborative Interactions",
author = "Suhr, Alane and
Yan, Claudia and
Schluger, Jack and
Yu, Stanley and
Khader, Hadi and
Mouallem, Marwa and
Zhang, Iris and
Artzi, Yoav",
editor = "Inui, Kentaro and
Jiang, Jing and
Ng, Vincent and
Wan, Xiaojun",
booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)",
month = nov,
year = "2019",
address = "Hong Kong, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/D19-1218",
doi = "10.18653/v1/D19-1218",
pages = "2119--2130",
abstract = "We study a collaborative scenario where a user not only instructs a system to complete tasks, but also acts alongside it. This allows the user to adapt to the system abilities by changing their language or deciding to simply accomplish some tasks themselves, and requires the system to effectively recover from errors as the user strategically assigns it new goals. We build a game environment to study this scenario, and learn to map user instructions to system actions. We introduce a learning approach focused on recovery from cascading errors between instructions, and modeling methods to explicitly reason about instructions with multiple goals. We evaluate with a new evaluation protocol using recorded interactions and online games with human users, and observe how users adapt to the system abilities.",
}
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%0 Conference Proceedings
%T Executing Instructions in Situated Collaborative Interactions
%A Suhr, Alane
%A Yan, Claudia
%A Schluger, Jack
%A Yu, Stanley
%A Khader, Hadi
%A Mouallem, Marwa
%A Zhang, Iris
%A Artzi, Yoav
%Y Inui, Kentaro
%Y Jiang, Jing
%Y Ng, Vincent
%Y Wan, Xiaojun
%S Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
%D 2019
%8 November
%I Association for Computational Linguistics
%C Hong Kong, China
%F suhr-etal-2019-executing
%X We study a collaborative scenario where a user not only instructs a system to complete tasks, but also acts alongside it. This allows the user to adapt to the system abilities by changing their language or deciding to simply accomplish some tasks themselves, and requires the system to effectively recover from errors as the user strategically assigns it new goals. We build a game environment to study this scenario, and learn to map user instructions to system actions. We introduce a learning approach focused on recovery from cascading errors between instructions, and modeling methods to explicitly reason about instructions with multiple goals. We evaluate with a new evaluation protocol using recorded interactions and online games with human users, and observe how users adapt to the system abilities.
%R 10.18653/v1/D19-1218
%U https://aclanthology.org/D19-1218
%U https://doi.org/10.18653/v1/D19-1218
%P 2119-2130
Markdown (Informal)
[Executing Instructions in Situated Collaborative Interactions](https://aclanthology.org/D19-1218) (Suhr et al., EMNLP-IJCNLP 2019)
ACL
- Alane Suhr, Claudia Yan, Jack Schluger, Stanley Yu, Hadi Khader, Marwa Mouallem, Iris Zhang, and Yoav Artzi. 2019. Executing Instructions in Situated Collaborative Interactions. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), pages 2119–2130, Hong Kong, China. Association for Computational Linguistics.