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20222024
most citedBeyond the Known: Investigating LLMs Performance on Out-of-Domain Intent Detection

5 citations · 7 across the 10 of their papers we have counts for

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cs.CL20245 cited

Beyond the Known: Investigating LLMs Performance on Out-of-Domain Intent Detection

Pei Wang, Keqing He, Yejie Wang +6

Out-of-domain (OOD) intent detection aims to examine whether the user's query falls outside the predefined domain of the system, which is crucial for the proper functioning of task…

cs.CL2024

DolphCoder: Echo-Locating Code Large Language Models with Diverse and Multi-Objective Instruction Tuning

Yejie Wang, Keqing He, Guanting Dong +8

Code Large Language Models (Code LLMs) have demonstrated outstanding performance in code-related tasks. Several instruction tuning approaches have been proposed to boost the code g…

cs.CL2023

Continual Generalized Intent Discovery: Marching Towards Dynamic and Open-world Intent Recognition

Xiaoshuai Song, Yutao Mou, Keqing He +3

In a practical dialogue system, users may input out-of-domain (OOD) queries. The Generalized Intent Discovery (GID) task aims to discover OOD intents from OOD queries and extend th…

cs.CL20231 cited

GKD: A General Knowledge Distillation Framework for Large-scale Pre-trained Language Model

Shicheng Tan, Weng Lam Tam, Yuanchun Wang +9

Currently, the reduction in the parameter scale of large-scale pre-trained language models (PLMs) through knowledge distillation has greatly facilitated their widespread deployment…

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…

cs.CL20231 cited

Revisit Out-Of-Vocabulary Problem for Slot Filling: A Unified Contrastive Frameword with Multi-level Data Augmentations

Daichi Guo, Guanting Dong, Dayuan Fu +9

In real dialogue scenarios, the existing slot filling model, which tends to memorize entity patterns, has a significantly reduced generalization facing Out-of-Vocabulary (OOV) prob…