Papers by Byungsoo Ko

2 papers
DialogCC: An Automated Pipeline for Creating High-Quality Multi-Modal Dialogue Dataset (2024.naacl-long)

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Challenge: Existing multi-modal dialogue datasets that focus on image-based dialogues have low quality and limited diversity of images per dialogue.
Approach: They propose to construct a multi-modal dialogue dataset that guarantees both dialogue quality and image diversity without requiring minimum human effort.
Outcome: The proposed dataset outperforms existing datasets in terms of quality and diversity in human evaluation.
Stark: Social Long-Term Multi-Modal Conversation with Persona Commonsense Knowledge (2024.findings-emnlp)

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Challenge: Existing studies focus on image-sharing behavior in singular sessions, leading to limited long-term social interaction.
Approach: They propose a large-scale long-term multi-modal dialogue dataset that generates long-time multi-modity dialogue distilled from ChatGPT and proposed image aligner.
Outcome: The proposed framework generates long-term multi-modal dialogue from ChatGPT and image aligner.

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