1.4k citations · 5.4k across the 120 of their papers we have counts for
9 papers · 2 filters
Knowledge Representation Learning: A Quantitative Review
Yankai Lin, Xu Han, Ruobing Xie +2
Knowledge representation learning (KRL) aims to represent entities and relations in knowledge graph in low-dimensional semantic space, which have been widely used in massive knowle…
Joint Representation Learning of Cross-lingual Words and Entities via Attentive Distant Supervision
Yixin Cao, Lei Hou, Juanzi Li +4
Joint representation learning of words and entities benefits many NLP tasks, but has not been well explored in cross-lingual settings. In this paper, we propose a novel method for…
Neural Collective Entity Linking
Yixin Cao, Lei Hou, Juanzi Li +1
Entity Linking aims to link entity mentions in texts to knowledge bases, and neural models have achieved recent success in this task. However, most existing methods rely on local c…
Learning to Embed Sentences Using Attentive Recursive Trees
Jiaxin Shi, Lei Hou, Juanzi Li +2
Sentence embedding is an effective feature representation for most deep learning-based NLP tasks. One prevailing line of methods is using recursive latent tree-structured networks…
DeepChannel: Salience Estimation by Contrastive Learning for Extractive Document Summarization
Jiaxin Shi, Chen Liang, Lei Hou +3
We propose DeepChannel, a robust, data-efficient, and interpretable neural model for extractive document summarization. Given any document-summary pair, we estimate a salience scor…
Language Modeling with Sparse Product of Sememe Experts
Yihong Gu, Jun Yan, Hao Zhu +5
Most language modeling methods rely on large-scale data to statistically learn the sequential patterns of words. In this paper, we argue that words are atomic language units but no…
CAIL2018: A Large-Scale Legal Dataset for Judgment Prediction
Chaojun Xiao, Haoxi Zhong, Zhipeng Guo +8
In this paper, we introduce the \textbf{C}hinese \textbf{AI} and \textbf{L}aw challenge dataset (CAIL2018), the first large-scale Chinese legal dataset for judgment prediction. \da…
Incorporating Chinese Characters of Words for Lexical Sememe Prediction
Huiming Jin, Hao Zhu, Zhiyuan Liu +4
Sememes are minimum semantic units of concepts in human languages, such that each word sense is composed of one or multiple sememes. Words are usually manually annotated with their…
Denoising Distant Supervision for Relation Extraction via Instance-Level Adversarial Training
Xu Han, Zhiyuan Liu, Maosong Sun
Existing neural relation extraction (NRE) models rely on distant supervision and suffer from wrong labeling problems. In this paper, we propose a novel adversarial training mechani…