Papers by Seokjun Seo

2 papers
Meet Your Favorite Character: Open-domain Chatbot Mimicking Fictional Characters with only a Few Utterances (2022.naacl-main)

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Challenge: In this paper, we consider mimicking fictional characters as a promising direction for building engaging conversation models.
Approach: They propose a task where only a few utterances of each fictional character are available to generate responses mimicking them.
Outcome: The proposed method generates responses better reflecting the style of fictional characters than baseline methods.
Distilling the Knowledge of Large-scale Generative Models into Retrieval Models for Efficient Open-domain Conversation (2021.findings-emnlp)

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Challenge: generative models are less practical for building real-time conversation systems due to high latency and large memory footprint.
Approach: They propose a method that preserves the efficiency of a retrieval model while leveraging the conversational ability of generative models.
Outcome: The proposed method preserves the efficiency of a retrieval model while leveraging the conversational ability of generative models.

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