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, Seungwon Hwang

Research output: Chapter in Book/Report/Conference proceedingConference 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 languageEnglish
Title of host publicationLREC 2018 - 11th International Conference on Language Resources and Evaluation
EditorsHitoshi 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
PublisherEuropean Language Resources Association (ELRA)
Pages2009-2013
Number of pages5
ISBN (Electronic)9791095546009
Publication statusPublished - 2019 Jan 1
Event11th International Conference on Language Resources and Evaluation, LREC 2018 - Miyazaki, Japan
Duration: 2018 May 72018 May 12

Other

Other11th International Conference on Language Resources and Evaluation, LREC 2018
CountryJapan
CityMiyazaki
Period18/5/718/5/12

Fingerprint

evaluation
artificial intelligence
Evaluation
Causal Reasoning
performance
Benchmark
Causal

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. (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). European Language Resources Association (ELRA).
Yeo, Jinyoung ; Lee, Gyeongbok ; Wang, Gengyu ; Choi, Seungtaek ; Cho, Hyunsouk ; Kim Amplayo, Reinald ; Hwang, Seungwon. / 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
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Yeo, J, Lee, G, Wang, G, Choi, S, Cho, H, Kim Amplayo, R & Hwang, S 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. 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; Choi, Seungtaek; Cho, Hyunsouk; Kim Amplayo, Reinald; Hwang, Seungwon.

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.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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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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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