Papers by Gao Qixiang

2 papers
Exploiting domain-slot related keywords description for Few-Shot Cross-Domain Dialogue State Tracking (2022.emnlp-main)

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Challenge: Existing frameworks for dialogue state tracking with domain-slot-value labels are expensive . current models are limited due to high cost of data annotation and lack of data in some domains .
Approach: They propose a framework based on domain-slot related description to tackle the challenge of few-shot cross-domain DST.
Outcome: The proposed framework outperforms existing methods on MultiWOZ and gains strong slot accuracy compared to existing models.
Value type: the bridge to a better DST model (2023.findings-acl)

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Challenge: Value type of the slots can provide lots of useful information for DST tasks. however, it has been ignored in most previous works.
Approach: They propose a new framework for DST task based on slot value type . they propose to extract the type of token from each turn and train a Ner model to extract corresponding type-entity from each conversation according to the token.
Outcome: The proposed framework is effective on two multi-domain task-oriented conversation datasets.

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