Papers by Seong-Bae Park

3 papers
Korean Morphological Analysis with Tied Sequence-to-Sequence Multi-Task Model (D19-1)

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Challenge: Korean morphological analysis is a sequence of morpheme processing and POS tagging.
Approach: They propose a tied sequence-to-sequence multi-task model for training the two tasks simultaneously without any explicit regularization.
Outcome: The proposed model achieves state-of-the-art performance without any explicit regularization.
MIDAS: Multi-level Intent, Domain, And Slot Knowledge Distillation for Multi-turn NLU (2025.findings-naacl)

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Challenge: Existing Large Language Models (LLMs) can generate coherent text, but they struggle to recognise user intent behind queries.
Approach: They propose a novel approach leveraging multi-level intent, domain, and slot knowledge distillation for multi-turn NLU.
Outcome: The proposed model improves multi-turn conversation understanding by integrating teacher teachers into a student model.
Post-Training with Interrogative Sentences for Enhancing BART-based Korean Question Generator (2022.aacl-short)

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Challenge: Existing pre-trained language models fail to generate perfect interrogative sentences in Korean question generation.
Approach: They propose to add question infilling objective to KoBART to enhance it for Korean question generation.
Outcome: The proposed post-training improves KoBART for Korean question generation.

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