Search Results for author: Goran Topic

Found 2 papers, 1 papers with code

An empirical analysis of existing systems and datasets toward general simple question answering

1 code implementation COLING 2020 Namgi Han, Goran Topic, Hiroshi Noji, Hiroya Takamura, Yusuke Miyao

Our analysis, including shifting of training and test datasets and training on a union of the datasets, suggests that our progress in solving SimpleQuestions dataset does not indicate the success of more general simple question answering.

Natural Language Understanding Question Answering

Generating Racing Game Commentary from Vision, Language, and Structured Data

no code implementations INLG (ACL) 2021 Tatsuya Ishigaki, Goran Topic, Yumi Hamazono, Hiroshi Noji, Ichiro Kobayashi, Yusuke Miyao, Hiroya Takamura

In this study, we introduce a new large-scale dataset that contains aligned video data, structured numerical data, and transcribed commentaries that consist of 129, 226 utterances in 1, 389 races in a game.

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