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A Scope Sensitive and Result Attentive Model for Multi-Intent Spoken Language Understanding
Result Attention Network effectively utilizes the bidirectional interaction between results of slot filling and intent detection, mitigating the error propagation problem.
Capture Salient Historical Information: A Fast and Accurate Non-Autoregressive Model for Multi-turn Spoken Language Understanding
SHA captures salient historical information for the current dialogue from both historical utterances and results via a well-designed history-attention mechanism.
An Effective Non-Autoregressive Model for Spoken Language Understanding
Spoken Language Understanding (SLU), a core component of the task-oriented dialogue system, expects a shorter inference latency due to the impatience of humans.
A Result based Portable Framework for Spoken Language Understanding
Spoken language understanding (SLU), which is a core component of the task-oriented dialogue system, has made substantial progress in the research of single-turn dialogue.
Iteratively Linearized Reweighted Alternating Direction Method of Multipliers for a Class of Nonconvex Problems
The traditional alternating direction method of multipliers encounters troubles in both mathematics and computations in solving the nonconvex and nonsmooth subproblem.
