Papers by Beomsu Kim
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. |
Measuring and Improving Semantic Diversity of Dialogue Generation (2022.findings-emnlp)
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| Challenge: | Existing evaluation metrics for response diversity do not capture the semantic diversity of generated responses. |
| Approach: | They propose an automatic evaluation metric to measure the semantic diversity of generated responses . they show that it captures human judgments better than existing diversity metrics . |
| Outcome: | The proposed metric captures human judgments on response diversity better than existing lexical diversity metrics. |
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. |