462 citations · 2.2k across the 15 of their papers we have counts for
5 papers · 1 filter
Learning multi-faceted representations of individuals from heterogeneous evidence using neural networks
Jiwei Li, Alan Ritter, Dan Jurafsky
Inferring latent attributes of people online is an important social computing task, but requires integrating the many heterogeneous sources of information available on the web. We…
A Hierarchical Neural Autoencoder for Paragraphs and Documents
Jiwei Li, Minh-Thang Luong, Dan Jurafsky
Natural language generation of coherent long texts like paragraphs or longer documents is a challenging problem for recurrent networks models. In this paper, we explore an importan…
Do Multi-Sense Embeddings Improve Natural Language Understanding?
Jiwei Li, Dan Jurafsky
Learning a distinct representation for each sense of an ambiguous word could lead to more powerful and fine-grained models of vector-space representations. Yet while `multi-sense'…
Visualizing and Understanding Neural Models in NLP
Jiwei Li, Xinlei Chen, Eduard Hovy +1
While neural networks have been successfully applied to many NLP tasks the resulting vector-based models are very difficult to interpret. For example it's not clear how they achiev…
When Are Tree Structures Necessary for Deep Learning of Representations?
Jiwei Li, Minh-Thang Luong, Dan Jurafsky +1
Recursive neural models, which use syntactic parse trees to recursively generate representations bottom-up, are a popular architecture. But there have not been rigorous evaluations…