Interactive Grounded Language Understanding in a Collaborative Environment: IGLU 2021

Julia Kiseleva, Ziming Li, Mohammad Aliannejadi, Shrestha Mohanty, Maartje ter Hoeve, Mikhail Burtsev, Alexey Skrynnik, Artem Zholus, Aleksandr Panov, Kavya Srinet, Arthur Szlam, Yuxuan Sun, Katja Hofmann, Marc-Alexandre Côté, Ahmed Awadallah, Linar Abdrazakov, Igor Churin, Putra Manggala, Kata Naszadi, Michiel van der Meer, Taewoon Kim
Proceedings of the NeurIPS 2021 Competitions and Demonstrations Track, PMLR 176:146-161, 2022.

Abstract

Human intelligence has the remarkable ability to quickly adapt to new tasks and environments. Starting from a very young age, humans acquire new skills and learn how to solve new tasks either by imitating the behavior of others or by following provided natural language instructions. To facilitate research in this direction, we propose IGLU: Interactive Grounded Language Understanding in a Collaborative Environment. The primary goal of the competition is to approach the problem of how to build interactive agents that learn to solve a task while provided with grounded natural language instructions in a collaborative environment. Understanding the complexity of the challenge, we split it into sub-tasks to make it feasible for participants.

Cite this Paper

BibTeX
@InProceedings{pmlr-v176-kiseleva22a, title = {Interactive Grounded Language Understanding in a Collaborative Environment: IGLU 2021}, author = {Kiseleva, Julia and Li, Ziming and Aliannejadi, Mohammad and Mohanty, Shrestha and ter Hoeve, Maartje and Burtsev, Mikhail and Skrynnik, Alexey and Zholus, Artem and Panov, Aleksandr and Srinet, Kavya and Szlam, Arthur and Sun, Yuxuan and Hofmann, Katja and C{\^o}t{\'e}, Marc-Alexandre and Awadallah, Ahmed and Abdrazakov, Linar and Churin, Igor and Manggala, Putra and Naszadi, Kata and van der Meer, Michiel and Kim, Taewoon}, booktitle = {Proceedings of the NeurIPS 2021 Competitions and Demonstrations Track}, pages = {146--161}, year = {2022}, editor = {Kiela, Douwe and Ciccone, Marco and Caputo, Barbara}, volume = {176}, series = {Proceedings of Machine Learning Research}, month = {06--14 Dec}, publisher = {PMLR}, pdf = {https://proceedings.mlr.press/v176/kiseleva22a/kiseleva22a.pdf}, url = {https://proceedings.mlr.press/v176/kiseleva22a.html}, abstract = {Human intelligence has the remarkable ability to quickly adapt to new tasks and environments. Starting from a very young age, humans acquire new skills and learn how to solve new tasks either by imitating the behavior of others or by following provided natural language instructions. To facilitate research in this direction, we propose IGLU: Interactive Grounded Language Understanding in a Collaborative Environment. The primary goal of the competition is to approach the problem of how to build interactive agents that learn to solve a task while provided with grounded natural language instructions in a collaborative environment. Understanding the complexity of the challenge, we split it into sub-tasks to make it feasible for participants.} }
Endnote
%0 Conference Paper %T Interactive Grounded Language Understanding in a Collaborative Environment: IGLU 2021 %A Julia Kiseleva %A Ziming Li %A Mohammad Aliannejadi %A Shrestha Mohanty %A Maartje ter Hoeve %A Mikhail Burtsev %A Alexey Skrynnik %A Artem Zholus %A Aleksandr Panov %A Kavya Srinet %A Arthur Szlam %A Yuxuan Sun %A Katja Hofmann %A Marc-Alexandre Côté %A Ahmed Awadallah %A Linar Abdrazakov %A Igor Churin %A Putra Manggala %A Kata Naszadi %A Michiel van der Meer %A Taewoon Kim %B Proceedings of the NeurIPS 2021 Competitions and Demonstrations Track %C Proceedings of Machine Learning Research %D 2022 %E Douwe Kiela %E Marco Ciccone %E Barbara Caputo %F pmlr-v176-kiseleva22a %I PMLR %P 146--161 %U https://proceedings.mlr.press/v176/kiseleva22a.html %V 176 %X Human intelligence has the remarkable ability to quickly adapt to new tasks and environments. Starting from a very young age, humans acquire new skills and learn how to solve new tasks either by imitating the behavior of others or by following provided natural language instructions. To facilitate research in this direction, we propose IGLU: Interactive Grounded Language Understanding in a Collaborative Environment. The primary goal of the competition is to approach the problem of how to build interactive agents that learn to solve a task while provided with grounded natural language instructions in a collaborative environment. Understanding the complexity of the challenge, we split it into sub-tasks to make it feasible for participants.
APA
Kiseleva, J., Li, Z., Aliannejadi, M., Mohanty, S., ter Hoeve, M., Burtsev, M., Skrynnik, A., Zholus, A., Panov, A., Srinet, K., Szlam, A., Sun, Y., Hofmann, K., Côté, M., Awadallah, A., Abdrazakov, L., Churin, I., Manggala, P., Naszadi, K., van der Meer, M. & Kim, T.. (2022). Interactive Grounded Language Understanding in a Collaborative Environment: IGLU 2021. Proceedings of the NeurIPS 2021 Competitions and Demonstrations Track, in Proceedings of Machine Learning Research 176:146-161 Available from https://proceedings.mlr.press/v176/kiseleva22a.html.

Related Material