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20182025
most citedA Simple Regularization-based Algorithm for Learning Cross-Domain Word Embeddings

42 citations · 185 across the 46 of their papers we have counts for

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Showing 2018 · cs.CLShow all

9 papers · 2 filters

cs.CL2018

Labeling Gaps Between Words: Recognizing Overlapping Mentions with Mention Separators

Aldrian Obaja Muis, Wei Lu

In this paper, we propose a new model that is capable of recognizing overlapping mentions. We introduce a novel notion of mention separators that can be effectively used to capture…

cs.CL2018

Efficient Dependency-Guided Named Entity Recognition

Zhanming Jie, Aldrian Obaja Muis, Wei Lu

Named entity recognition (NER), which focuses on the extraction of semantically meaningful named entities and their semantic classes from text, serves as an indispensable component…

cs.CL2018

Weak Semi-Markov CRFs for NP Chunking in Informal Text

Aldrian Obaja Muis, Wei Lu

This paper introduces a new annotated corpus based on an existing informal text corpus: the NUS SMS Corpus (Chen and Kan, 2013). The new corpus includes 76,490 noun phrases from 26…

cs.CL2018

Neural Adaptation Layers for Cross-domain Named Entity Recognition

Bill Yuchen Lin, Wei Lu

Recent research efforts have shown that neural architectures can be effective in conventional information extraction tasks such as named entity recognition, yielding state-of-the-a…

cs.CL2018

Neural Segmental Hypergraphs for Overlapping Mention Recognition

Bailin Wang, Wei Lu

In this work, we propose a novel segmental hypergraph representation to model overlapping entity mentions that are prevalent in many practical datasets. We show that our model buil…

cs.CL2018

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…