activity
20212023
most citedKnowledge Augmented BERT Mutual Network in Multi-turn Spoken Dialogues

5 citations · 7 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2023

Schema Graph-Guided Prompt for Multi-Domain Dialogue State Tracking

Ruolin Su, Ting-Wei Wu, Biing-Hwang Juang

Tracking dialogue states is an essential topic in task-oriented dialogue systems, which involve filling in the necessary information in pre-defined slots corresponding to a schema.…

cs.CL2023

Data Augmentation for Improving Tail-traffic Robustness in Skill-routing for Dialogue Systems

Ting-Wei Wu, Fatemeh Sheikholeslami, Mohammad Kachuee +2

Large-scale conversational systems typically rely on a skill-routing component to route a user request to an appropriate skill and interpretation to serve the request. In such syst…

cs.CL2023

Choice Fusion as Knowledge for Zero-Shot Dialogue State Tracking

Ruolin Su, Jingfeng Yang, Ting-Wei Wu +1

With the demanding need for deploying dialogue systems in new domains with less cost, zero-shot dialogue state tracking (DST), which tracks user's requirements in task-oriented dia…

cs.CL2022★ 5 cited

Knowledge Augmented BERT Mutual Network in Multi-turn Spoken Dialogues

Ting-Wei Wu, Biing-Hwang Juang

Modern spoken language understanding (SLU) systems rely on sophisticated semantic notions revealed in single utterances to detect intents and slots. However, they lack the capabili…

cs.CL2021★ 2 cited

A Context-Aware Hierarchical BERT Fusion Network for Multi-turn Dialog Act Detection

Ting-Wei Wu, Ruolin Su, Biing-Hwang Juang

The success of interactive dialog systems is usually associated with the quality of the spoken language understanding (SLU) task, which mainly identifies the corresponding dialog a…