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20222025
most citedBeyond the Known: Investigating LLMs Performance on Out-of-Domain Intent Detection

5 citations · 15 across the 14 of their papers we have counts for

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Showing 2023Show all

5 papers · 1 filter

cs.CL2023★ 4 cited

APP: Adaptive Prototypical Pseudo-Labeling for Few-shot OOD Detection

Pei Wang, Keqing He, Yutao Mou +6

Detecting out-of-domain (OOD) intents from user queries is essential for a task-oriented dialogue system. Previous OOD detection studies generally work on the assumption that plent…

cs.CL2023

Large Language Models Meet Open-World Intent Discovery and Recognition: An Evaluation of ChatGPT

Xiaoshuai Song, Keqing He, Pei Wang +6

The tasks of out-of-domain (OOD) intent discovery and generalized intent discovery (GID) aim to extend a closed intent classifier to open-world intent sets, which is crucial to tas…

cs.CL2023

Seen to Unseen: Exploring Compositional Generalization of Multi-Attribute Controllable Dialogue Generation

Weihao Zeng, Lulu Zhao, Keqing He +4

Existing controllable dialogue generation work focuses on the single-attribute control and lacks generalization capability to out-of-distribution multiple attribute combinations. I…

cs.CL2023

FutureTOD: Teaching Future Knowledge to Pre-trained Language Model for Task-Oriented Dialogue

Weihao Zeng, Keqing He, Yejie Wang +4

Pre-trained language models based on general text enable huge success in the NLP scenario. But the intrinsical difference of linguistic patterns between general text and task-orien…

cs.CL2023

Decoupling Pseudo Label Disambiguation and Representation Learning for Generalized Intent Discovery

Yutao Mou, Xiaoshuai Song, Keqing He +5

Generalized intent discovery aims to extend a closed-set in-domain intent classifier to an open-world intent set including in-domain and out-of-domain intents. The key challenges l…