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20172022
most citedPhase Conductor on Multi-layered Attentions for Machine Comprehension

18 citations · 50 across the 13 of their papers we have counts for

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11 papers · 1 filter

cs.CL20225 cited

Automatic Noisy Label Correction for Fine-Grained Entity Typing

Weiran Pan, Wei Wei, Feida Zhu

Fine-grained entity typing (FET) aims to assign proper semantic types to entity mentions according to their context, which is a fundamental task in various entity-leveraging applic…

cs.CL20212 cited

Exploiting Global Contextual Information for Document-level Named Entity Recognition

Zanbo Wang, Wei Wei, Xianling Mao +4

Most existing named entity recognition (NER) approaches are based on sequence labeling models, which focus on capturing the local context dependencies. However, the way of taking o…

cs.CL20213 cited

A Student-Teacher Architecture for Dialog Domain Adaptation under the Meta-Learning Setting

Kun Qian, Wei Wei, Zhou Yu

Numerous new dialog domains are being created every day while collecting data for these domains is extremely costly since it involves human interactions. Therefore, it is essential…

cs.CL20201 cited

Self-attention Comparison Module for Boosting Performance on Retrieval-based Open-Domain Dialog Systems

Tian Lan, Xian-Ling Mao, Zhipeng Zhao +2

Since the pre-trained language models are widely used, retrieval-based open-domain dialog systems, have attracted considerable attention from researchers recently. Most of the prev…

cs.CL202016 cited

A Survey on Recent Advances in Sequence Labeling from Deep Learning Models

Zhiyong He, Zanbo Wang, Wei Wei +3

Sequence labeling (SL) is a fundamental research problem encompassing a variety of tasks, e.g., part-of-speech (POS) tagging, named entity recognition (NER), text chunking, etc. Th…

cs.CL20201 cited

Which Kind Is Better in Open-domain Multi-turn Dialog,Hierarchical or Non-hierarchical Models? An Empirical Study

Tian Lan, Xian-Ling Mao, Wei Wei +1

Currently, open-domain generative dialog systems have attracted considerable attention in academia and industry. Despite the success of single-turn dialog generation, multi-turn di…