Papers by Heejin Kook
Transparent Reference-free Automated Evaluation of Open-Ended User Survey Responses (2025.emnlp-industry)
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| Challenge: | Existing methods to evaluate open-ended survey responses are expensive and lack ground-truth reference for comparison. |
| Approach: | They propose a two-stage evaluation framework specifically designed for human survey responses that uses gibberish filtering to remove nonsensical responses. |
| Outcome: | The proposed evaluation framework outperforms existing metrics on English and Korean datasets and shows strong correlations with expert assessment. |
Empowering Retrieval-based Conversational Recommendation with Contrasting User Preferences (2025.naacl-long)
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| Challenge: | Existing CRSs assume positive and negative user preferences, but assume that the entities in the dialogue history are positive. |
| Approach: | They propose a conversational recommender model that captures user sentiments and uses the reasoning capacity of the LLMs to extract user's hidden preferences. |
| Outcome: | The proposed model outperforms existing methods in three benchmark datasets, improving up to 99.72% in Recall@10. |