Visual choice of plausible alternatives: An Evaluation of Image-based Commonsense Causal Reasoning

Jinyoung Yeo; Gyeongbok Lee; Gengyu Wang; Seungtaek Choi; Hyunsouk Cho; Reinald Kim Amplayo; Seung Won Hwang

Visual choice of plausible alternatives: An Evaluation of Image-based Commonsense Causal Reasoning

Jinyoung Yeo, Gyeongbok Lee, Gengyu Wang, Seungtaek Choi, Hyunsouk Cho, Reinald Kim Amplayo, Seung Won Hwang

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

This paper proposes the task of Visual COPA (VCOPA). Given a premise image and two alternative images, the task is to identify the more plausible alternative with their commonsense causal context. The VCOPA task is designed as its desirable machine system needs a more detailed understanding of the image, commonsense knowledge, and complex causal reasoning than state-of-the-art AI techniques. For that, we generate an evaluation dataset containing 380 VCOPA questions and over 1K images with various topics, which is amenable to automatic evaluation, and present the performance of baseline reasoning approaches as initial benchmarks for future systems.

Original language	English
Title of host publication	LREC 2018 - 11th International Conference on Language Resources and Evaluation
Editors	Hitoshi Isahara, Bente Maegaard, Stelios Piperidis, Christopher Cieri, Thierry Declerck, Koiti Hasida, Helene Mazo, Khalid Choukri, Sara Goggi, Joseph Mariani, Asuncion Moreno, Nicoletta Calzolari, Jan Odijk, Takenobu Tokunaga
Publisher	European Language Resources Association (ELRA)
Pages	2009-2013
Number of pages	5
ISBN (Electronic)	9791095546009
Publication status	Published - 2019
Event	11th International Conference on Language Resources and Evaluation, LREC 2018 - Miyazaki, Japan Duration: 2018 May 7 → 2018 May 12

Publication series

Name	LREC 2018 - 11th International Conference on Language Resources and Evaluation

Other

Other	11th International Conference on Language Resources and Evaluation, LREC 2018
Country/Territory	Japan
City	Miyazaki
Period	18/5/7 → 18/5/12

Bibliographical note

Funding Information:
This work was supported by Microsoft Research, and Institute for Information communications Technology Promotion(IITP) grant funded by the Korea government(MSIT) (No.2017-0-01778,Development of Explainable Human-level Deep Machine Learning Inference Framework). S. Hwang is a corresponding author.

Publisher Copyright:
© LREC 2018 - 11th International Conference on Language Resources and Evaluation. All rights reserved.

All Science Journal Classification (ASJC) codes

Linguistics and Language
Education
Library and Information Sciences
Language and Linguistics

Cite this

Yeo, J., Lee, G., Wang, G., Choi, S., Cho, H., Kim Amplayo, R., & Hwang, S. W. (2019). Visual choice of plausible alternatives: An Evaluation of Image-based Commonsense Causal Reasoning. In H. Isahara, B. Maegaard, S. Piperidis, C. Cieri, T. Declerck, K. Hasida, H. Mazo, K. Choukri, S. Goggi, J. Mariani, A. Moreno, N. Calzolari, J. Odijk, & T. Tokunaga (Eds.), LREC 2018 - 11th International Conference on Language Resources and Evaluation (pp. 2009-2013). (LREC 2018 - 11th International Conference on Language Resources and Evaluation). European Language Resources Association (ELRA).

Yeo, Jinyoung ; Lee, Gyeongbok ; Wang, Gengyu et al. / Visual choice of plausible alternatives : An Evaluation of Image-based Commonsense Causal Reasoning. LREC 2018 - 11th International Conference on Language Resources and Evaluation. editor / Hitoshi Isahara ; Bente Maegaard ; Stelios Piperidis ; Christopher Cieri ; Thierry Declerck ; Koiti Hasida ; Helene Mazo ; Khalid Choukri ; Sara Goggi ; Joseph Mariani ; Asuncion Moreno ; Nicoletta Calzolari ; Jan Odijk ; Takenobu Tokunaga. European Language Resources Association (ELRA), 2019. pp. 2009-2013 (LREC 2018 - 11th International Conference on Language Resources and Evaluation).

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title = "Visual choice of plausible alternatives: An Evaluation of Image-based Commonsense Causal Reasoning",

abstract = "This paper proposes the task of Visual COPA (VCOPA). Given a premise image and two alternative images, the task is to identify the more plausible alternative with their commonsense causal context. The VCOPA task is designed as its desirable machine system needs a more detailed understanding of the image, commonsense knowledge, and complex causal reasoning than state-of-the-art AI techniques. For that, we generate an evaluation dataset containing 380 VCOPA questions and over 1K images with various topics, which is amenable to automatic evaluation, and present the performance of baseline reasoning approaches as initial benchmarks for future systems.",

author = "Jinyoung Yeo and Gyeongbok Lee and Gengyu Wang and Seungtaek Choi and Hyunsouk Cho and {Kim Amplayo}, Reinald and Hwang, {Seung Won}",

note = "Funding Information: This work was supported by Microsoft Research, and Institute for Information communications Technology Promotion(IITP) grant funded by the Korea government(MSIT) (No.2017-0-01778,Development of Explainable Human-level Deep Machine Learning Inference Framework). S. Hwang is a corresponding author. Publisher Copyright: {\textcopyright} LREC 2018 - 11th International Conference on Language Resources and Evaluation. All rights reserved.; 11th International Conference on Language Resources and Evaluation, LREC 2018 ; Conference date: 07-05-2018 Through 12-05-2018",

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series = "LREC 2018 - 11th International Conference on Language Resources and Evaluation",

publisher = "European Language Resources Association (ELRA)",

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editor = "Hitoshi Isahara and Bente Maegaard and Stelios Piperidis and Christopher Cieri and Thierry Declerck and Koiti Hasida and Helene Mazo and Khalid Choukri and Sara Goggi and Joseph Mariani and Asuncion Moreno and Nicoletta Calzolari and Jan Odijk and Takenobu Tokunaga",

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Yeo, J, Lee, G, Wang, G, Choi, S, Cho, H, Kim Amplayo, R & Hwang, SW 2019, Visual choice of plausible alternatives: An Evaluation of Image-based Commonsense Causal Reasoning. in H Isahara, B Maegaard, S Piperidis, C Cieri, T Declerck, K Hasida, H Mazo, K Choukri, S Goggi, J Mariani, A Moreno, N Calzolari, J Odijk & T Tokunaga (eds), LREC 2018 - 11th International Conference on Language Resources and Evaluation. LREC 2018 - 11th International Conference on Language Resources and Evaluation, European Language Resources Association (ELRA), pp. 2009-2013, 11th International Conference on Language Resources and Evaluation, LREC 2018, Miyazaki, Japan, 18/5/7.

Visual choice of plausible alternatives: An Evaluation of Image-based Commonsense Causal Reasoning. / Yeo, Jinyoung; Lee, Gyeongbok; Wang, Gengyu et al.
LREC 2018 - 11th International Conference on Language Resources and Evaluation. ed. / Hitoshi Isahara; Bente Maegaard; Stelios Piperidis; Christopher Cieri; Thierry Declerck; Koiti Hasida; Helene Mazo; Khalid Choukri; Sara Goggi; Joseph Mariani; Asuncion Moreno; Nicoletta Calzolari; Jan Odijk; Takenobu Tokunaga. European Language Resources Association (ELRA), 2019. p. 2009-2013 (LREC 2018 - 11th International Conference on Language Resources and Evaluation).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Visual choice of plausible alternatives

T2 - 11th International Conference on Language Resources and Evaluation, LREC 2018

AU - Yeo, Jinyoung

AU - Lee, Gyeongbok

AU - Wang, Gengyu

AU - Choi, Seungtaek

AU - Cho, Hyunsouk

AU - Kim Amplayo, Reinald

AU - Hwang, Seung Won

N1 - Funding Information: This work was supported by Microsoft Research, and Institute for Information communications Technology Promotion(IITP) grant funded by the Korea government(MSIT) (No.2017-0-01778,Development of Explainable Human-level Deep Machine Learning Inference Framework). S. Hwang is a corresponding author. Publisher Copyright: © LREC 2018 - 11th International Conference on Language Resources and Evaluation. All rights reserved.

PY - 2019

Y1 - 2019

N2 - This paper proposes the task of Visual COPA (VCOPA). Given a premise image and two alternative images, the task is to identify the more plausible alternative with their commonsense causal context. The VCOPA task is designed as its desirable machine system needs a more detailed understanding of the image, commonsense knowledge, and complex causal reasoning than state-of-the-art AI techniques. For that, we generate an evaluation dataset containing 380 VCOPA questions and over 1K images with various topics, which is amenable to automatic evaluation, and present the performance of baseline reasoning approaches as initial benchmarks for future systems.

AB - This paper proposes the task of Visual COPA (VCOPA). Given a premise image and two alternative images, the task is to identify the more plausible alternative with their commonsense causal context. The VCOPA task is designed as its desirable machine system needs a more detailed understanding of the image, commonsense knowledge, and complex causal reasoning than state-of-the-art AI techniques. For that, we generate an evaluation dataset containing 380 VCOPA questions and over 1K images with various topics, which is amenable to automatic evaluation, and present the performance of baseline reasoning approaches as initial benchmarks for future systems.

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M3 - Conference contribution

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SP - 2009

EP - 2013

BT - LREC 2018 - 11th International Conference on Language Resources and Evaluation

A2 - Isahara, Hitoshi

A2 - Maegaard, Bente

A2 - Piperidis, Stelios

A2 - Cieri, Christopher

A2 - Declerck, Thierry

A2 - Hasida, Koiti

A2 - Mazo, Helene

A2 - Choukri, Khalid

A2 - Goggi, Sara

A2 - Mariani, Joseph

A2 - Moreno, Asuncion

A2 - Calzolari, Nicoletta

A2 - Odijk, Jan

A2 - Tokunaga, Takenobu

PB - European Language Resources Association (ELRA)

Y2 - 7 May 2018 through 12 May 2018

ER -

Yeo J, Lee G, Wang G, Choi S, Cho H, Kim Amplayo R et al. Visual choice of plausible alternatives: An Evaluation of Image-based Commonsense Causal Reasoning. In Isahara H, Maegaard B, Piperidis S, Cieri C, Declerck T, Hasida K, Mazo H, Choukri K, Goggi S, Mariani J, Moreno A, Calzolari N, Odijk J, Tokunaga T, editors, LREC 2018 - 11th International Conference on Language Resources and Evaluation. European Language Resources Association (ELRA). 2019. p. 2009-2013. (LREC 2018 - 11th International Conference on Language Resources and Evaluation).

Visual choice of plausible alternatives: An Evaluation of Image-based Commonsense Causal Reasoning

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