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A Two-Stage Prediction-Aware Contrastive Learning Framework for Multi-Intent NLU
May 7, 2024, 4:50 a.m. | Guanhua Chen, Yutong Yao, Derek F. Wong, Lidia S. Chao
cs.CL updates on arXiv.org arxiv.org
Abstract: Multi-intent natural language understanding (NLU) presents a formidable challenge due to the model confusion arising from multiple intents within a single utterance. While previous works train the model contrastively to increase the margin between different multi-intent labels, they are less suited to the nuances of multi-intent NLU. They ignore the rich information between the shared intents, which is beneficial to constructing a better embedding space, especially in low-data scenarios. We introduce a two-stage Prediction-Aware Contrastive …
abstract arxiv challenge cs.cl framework labels language language understanding multiple natural natural language nlu prediction stage train type understanding while
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