224 citations · 3.2k across the 170 of their papers we have counts for
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Cross-Lingual Contextual Word Embeddings Mapping With Multi-Sense Words In Mind
Zheng Zhang, Ruiqing Yin, Jun Zhu +1
Recent work in cross-lingual contextual word embedding learning cannot handle multi-sense words well. In this work, we explore the characteristics of contextual word embeddings and…
PSDVec: a Toolbox for Incremental and Scalable Word Embedding
Shaohua Li, Jun Zhu, Chunyan Miao
PSDVec is a Python/Perl toolbox that learns word embeddings, i.e. the mapping of words in a natural language to continuous vectors which encode the semantic/syntactic regularities…
Generative Topic Embedding: a Continuous Representation of Documents (Extended Version with Proofs)
Shaohua Li, Tat-Seng Chua, Jun Zhu +1
Word embedding maps words into a low-dimensional continuous embedding space by exploiting the local word collocation patterns in a small context window. On the other hand, topic mo…
Jointly Modeling Topics and Intents with Global Order Structure
Bei Chen, Jun Zhu, Nan Yang +3
Modeling document structure is of great importance for discourse analysis and related applications. The goal of this research is to capture the document intent structure by modelin…
Building Memory with Concept Learning Capabilities from Large-scale Knowledge Base
Jiaxin Shi, Jun Zhu
We present a new perspective on neural knowledge base (KB) embeddings, from which we build a framework that can model symbolic knowledge in the KB together with its learning proces…
A Generative Word Embedding Model and its Low Rank Positive Semidefinite Solution
Shaohua Li, Jun Zhu, Chunyan Miao
Most existing word embedding methods can be categorized into Neural Embedding Models and Matrix Factorization (MF)-based methods. However some models are opaque to probabilistic in…