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        <title>Structural and Functional Decomposition for Personality Image Captioning in a Communication Game</title>
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        <namePart type="given">Minh</namePart>
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    <abstract>Personality image captioning (PIC) aims to describe an image with a natural language caption given a personality trait. In this work, we introduce a novel formulation for PIC based on a communication game between a speaker and a listener. The speaker attempts to generate natural language captions while the listener encourages the generated captions to contain discriminative information about the input images and personality traits. In this way, we expect that the generated captions can be improved to naturally represent the images and express the traits. In addition, we propose to adapt the language model GPT2 to perform caption generation for PIC. This enables the speaker and listener to benefit from the language encoding capacity of GPT2. Our experiments show that the proposed model achieves the state-of-the-art performance for PIC.</abstract>
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%0 Conference Proceedings
%T Structural and Functional Decomposition for Personality Image Captioning in a Communication Game
%A Nguyen, Minh Thu
%A Phung, Duy
%A Hoai, Minh
%A Nguyen, Thien Huu
%Y Cohn, Trevor
%Y He, Yulan
%Y Liu, Yang
%S Findings of the Association for Computational Linguistics: EMNLP 2020
%D 2020
%8 November
%I Association for Computational Linguistics
%C Online
%F nguyen-etal-2020-structural
%X Personality image captioning (PIC) aims to describe an image with a natural language caption given a personality trait. In this work, we introduce a novel formulation for PIC based on a communication game between a speaker and a listener. The speaker attempts to generate natural language captions while the listener encourages the generated captions to contain discriminative information about the input images and personality traits. In this way, we expect that the generated captions can be improved to naturally represent the images and express the traits. In addition, we propose to adapt the language model GPT2 to perform caption generation for PIC. This enables the speaker and listener to benefit from the language encoding capacity of GPT2. Our experiments show that the proposed model achieves the state-of-the-art performance for PIC.
%R 10.18653/v1/2020.findings-emnlp.411
%U https://aclanthology.org/2020.findings-emnlp.411/
%U https://doi.org/10.18653/v1/2020.findings-emnlp.411
%P 4587-4593

Markdown (Informal)

[Structural and Functional Decomposition for Personality Image Captioning in a Communication Game](https://aclanthology.org/2020.findings-emnlp.411/) (Nguyen et al., Findings 2020)

• Structural and Functional Decomposition for Personality Image Captioning in a Communication Game (Nguyen et al., Findings 2020)

ACL

• Minh Thu Nguyen, Duy Phung, Minh Hoai, and Thien Huu Nguyen. 2020. Structural and Functional Decomposition for Personality Image Captioning in a Communication Game. In Findings of the Association for Computational Linguistics: EMNLP 2020, pages 4587–4593, Online. Association for Computational Linguistics.