@inproceedings{shavrina-etal-2020-humans,
title = "Humans Keep It One Hundred: an Overview of {AI} Journey",
author = "Shavrina, Tatiana and
Emelyanov, Anton and
Fenogenova, Alena and
Fomin, Vadim and
Mikhailov, Vladislav and
Evlampiev, Andrey and
Malykh, Valentin and
Larin, Vladimir and
Natekin, Alex and
Vatulin, Aleksandr and
Romov, Peter and
Anastasiev, Daniil and
Zinov, Nikolai and
Chertok, Andrey",
booktitle = "Proceedings of the 12th Language Resources and Evaluation Conference",
month = may,
year = "2020",
address = "Marseille, France",
publisher = "European Language Resources Association",
url = "https://aclanthology.org/2020.lrec-1.277",
pages = "2276--2284",
abstract = "Artificial General Intelligence (AGI) is showing growing performance in numerous applications - beating human performance in Chess and Go, using knowledge bases and text sources to answer questions (SQuAD) and even pass human examination (Aristo project). In this paper, we describe the results of AI Journey, a competition of AI-systems aimed to improve AI performance on knowledge bases, reasoning and text generation. Competing systems pass the final native language exam (in Russian), including versatile grammar tasks (test and open questions) and an essay, achieving a high score of 69{\%}, with 68{\%} being an average human result. During the competition, a baseline for the task and essay parts was proposed, and 80+ systems were submitted, showing different approaches to task understanding and reasoning. All the data and solutions can be found on github https://github.com/sberbank-ai/combined{\_}solution{\_}aij2019",
language = "English",
ISBN = "979-10-95546-34-4",
}
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<abstract>Artificial General Intelligence (AGI) is showing growing performance in numerous applications - beating human performance in Chess and Go, using knowledge bases and text sources to answer questions (SQuAD) and even pass human examination (Aristo project). In this paper, we describe the results of AI Journey, a competition of AI-systems aimed to improve AI performance on knowledge bases, reasoning and text generation. Competing systems pass the final native language exam (in Russian), including versatile grammar tasks (test and open questions) and an essay, achieving a high score of 69%, with 68% being an average human result. During the competition, a baseline for the task and essay parts was proposed, and 80+ systems were submitted, showing different approaches to task understanding and reasoning. All the data and solutions can be found on github https://github.com/sberbank-ai/combined_solution_aij2019</abstract>
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%0 Conference Proceedings
%T Humans Keep It One Hundred: an Overview of AI Journey
%A Shavrina, Tatiana
%A Emelyanov, Anton
%A Fenogenova, Alena
%A Fomin, Vadim
%A Mikhailov, Vladislav
%A Evlampiev, Andrey
%A Malykh, Valentin
%A Larin, Vladimir
%A Natekin, Alex
%A Vatulin, Aleksandr
%A Romov, Peter
%A Anastasiev, Daniil
%A Zinov, Nikolai
%A Chertok, Andrey
%S Proceedings of the 12th Language Resources and Evaluation Conference
%D 2020
%8 may
%I European Language Resources Association
%C Marseille, France
%@ 979-10-95546-34-4
%G English
%F shavrina-etal-2020-humans
%X Artificial General Intelligence (AGI) is showing growing performance in numerous applications - beating human performance in Chess and Go, using knowledge bases and text sources to answer questions (SQuAD) and even pass human examination (Aristo project). In this paper, we describe the results of AI Journey, a competition of AI-systems aimed to improve AI performance on knowledge bases, reasoning and text generation. Competing systems pass the final native language exam (in Russian), including versatile grammar tasks (test and open questions) and an essay, achieving a high score of 69%, with 68% being an average human result. During the competition, a baseline for the task and essay parts was proposed, and 80+ systems were submitted, showing different approaches to task understanding and reasoning. All the data and solutions can be found on github https://github.com/sberbank-ai/combined_solution_aij2019
%U https://aclanthology.org/2020.lrec-1.277
%P 2276-2284
Markdown (Informal)
[Humans Keep It One Hundred: an Overview of AI Journey](https://aclanthology.org/2020.lrec-1.277) (Shavrina et al., LREC 2020)
ACL
- Tatiana Shavrina, Anton Emelyanov, Alena Fenogenova, Vadim Fomin, Vladislav Mikhailov, Andrey Evlampiev, Valentin Malykh, Vladimir Larin, Alex Natekin, Aleksandr Vatulin, Peter Romov, Daniil Anastasiev, Nikolai Zinov, and Andrey Chertok. 2020. Humans Keep It One Hundred: an Overview of AI Journey. In Proceedings of the 12th Language Resources and Evaluation Conference, pages 2276–2284, Marseille, France. European Language Resources Association.