Papers by Xuelian Dong

2 papers
LLM-Enhanced Query Generation and Retrieval Preservation for Task-Oriented Dialogue (2025.findings-acl)

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Challenge: Existing knowledge retrieval methods for task-oriented dialogues are limited by data scarcity and lack of data to annotate.
Approach: They propose an LLM-enhanced model of query-guided knowledge retrieval for task-oriented dialogue . they propose to select the most relevant knowledge from retrieved top-K records and incorporate them as prompts to guide a generator in response generation.
Outcome: The proposed model outperforms state-of-the-art in three benchmarks on three standard benchmarks.
Can Large Language Models Translate Spoken-Only Languages through International Phonetic Transcription? (2025.emnlp-main)

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Challenge: Existing research on spoken-only languages has focused on low-resource languages . spoken- only languages are among the most vulnerable to extinction .
Approach: They propose a unified language understanding framework that learns to translate spoken-only languages via in-context learning.
Outcome: The proposed framework can translate spoken-only languages into high-resource languages using phonetic transcription and automatic dictionary construction and knowledge retrieval.

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