12 citations · 35 across the 6 of their papers we have counts for
6 papers
Hybrid Rule-Neural Coreference Resolution System based on Actor-Critic Learning
Yu Wang, Hongxia Jin
A coreference resolution system is to cluster all mentions that refer to the same entity in a given context. All coreference resolution systems need to tackle two main tasks: one t…
A Bi-model based RNN Semantic Frame Parsing Model for Intent Detection and Slot Filling
Yu Wang, Yilin Shen, Hongxia Jin
Intent detection and slot filling are two main tasks for building a spoken language understanding(SLU) system. Multiple deep learning based models have demonstrated good results on…
A Neural Transition-based Model for Nested Mention Recognition
Bailin Wang, Wei Lu, Yu Wang +1
It is common that entity mentions can contain other mentions recursively. This paper introduces a scalable transition-based method to model the nested structure of mentions. We fir…
User Information Augmented Semantic Frame Parsing using Coarse-to-Fine Neural Networks
Yilin Shen, Xiangyu Zeng, Yu Wang +1
Semantic frame parsing is a crucial component in spoken language understanding (SLU) to build spoken dialog systems. It has two main tasks: intent detection and slot filling. Altho…
Improving the Speed of Response of Learning Algorithms Using Multiple Models
Kumpati S. Narendra, Snehasis Mukhopadyhay, Yu Wang
This is the first of a series of papers that the authors propose to write on the subject of improving the speed of response of learning systems using multiple models. During the pa…
The Rationale for Second Level Adaptation
Kumpati S. Narendra, Yu Wang, Wei Chen
Recently, a new approach to the adaptive control of linear time-invariant plants with unknown parameters (referred to as second level adaptation), was introduced by Han and Narendr…