Papers with conversational dialogue

3 papers
Zero-shot Slot Filling in the Age of LLMs for Dialogue Systems (2025.coling-industry)

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Challenge: Existing methods for zero-shot slot filling focus on text data, overlooking conversational data.
Approach: They propose a method for automatic data annotation with slot induction and black-box knowledge distillation from a teacher LLM to a smaller model.
Outcome: The proposed method outperforms existing models on internal datasets by 26% relative increase in F1 score.
JESC: Japanese-English Subtitle Corpus (L18-1)

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Challenge: Existing data on Japanese-English subtitles are limited due to the high cost of manual construction.
Approach: They describe the Japanese-English Subtitle Corpus by crawling and aligning subtitles found on the web.
Outcome: The JESC dataset covers the underrepresented domain of conversational dialogue.
More Diverse Dialogue Datasets via Diversity-Informed Data Collection (2020.acl-main)

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Challenge: Existing approaches to generate conversational dialogue produce uninteresting, predictable responses.
Approach: They propose a method to collect and determine more diverse data from conversational participants . they use dynamically computed corpus-level statistics to determine which conversational participant to collect data from .
Outcome: The proposed method produces significantly more diverse data than baseline methods and better results on emotion classification and dialogue generation tasks.

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