activity
20162026
most citedERNIE: Enhanced Language Representation with Informative Entities

135 citations · 868 across the 76 of their papers we have counts for

collaborators
Showing 2020Show all

7 papers · 1 filter

cs.CL2020★ 22 cited

CPM: A Large-scale Generative Chinese Pre-trained Language Model

Zhengyan Zhang, Xu Han, Hao Zhou +22

Pre-trained Language Models (PLMs) have proven to be beneficial for various downstream NLP tasks. Recently, GPT-3, with 175 billion parameters and 570GB training data, drew a lot o…

cs.CL2020★ 18 cited

Learning from Context or Names? An Empirical Study on Neural Relation Extraction

Hao Peng, Tianyu Gao, Xu Han +5

Neural models have achieved remarkable success on relation extraction (RE) benchmarks. However, there is no clear understanding which type of information affects existing RE models…

cs.CL2020★ 2 cited

Denoising Relation Extraction from Document-level Distant Supervision

Chaojun Xiao, Yuan Yao, Ruobing Xie +5

Distant supervision (DS) has been widely used to generate auto-labeled data for sentence-level relation extraction (RE), which improves RE performance. However, the existing succes…

cs.CL2020★ 5 cited

Dynamic Anticipation and Completion for Multi-Hop Reasoning over Sparse Knowledge Graph

Xin Lv, Xu Han, Lei Hou +6

Multi-hop reasoning has been widely studied in recent years to seek an effective and interpretable method for knowledge graph (KG) completion. Most previous reasoning methods are d…

cs.CL2020★ 38 cited

CokeBERT: Contextual Knowledge Selection and Embedding towards Enhanced Pre-Trained Language Models

Yusheng Su, Xu Han, Zhengyan Zhang +5

Several recent efforts have been devoted to enhancing pre-trained language models (PLMs) by utilizing extra heterogeneous knowledge in knowledge graphs (KGs) and achieved consisten…

cs.CL2020★ 5 cited

MAVEN: A Massive General Domain Event Detection Dataset

Xiaozhi Wang, Ziqi Wang, Xu Han +7

Event detection (ED), which means identifying event trigger words and classifying event types, is the first and most fundamental step for extracting event knowledge from plain text…

cs.CL2020★ 40 cited

More Data, More Relations, More Context and More Openness: A Review and Outlook for Relation Extraction

Xu Han, Tianyu Gao, Yankai Lin +7

Relational facts are an important component of human knowledge, which are hidden in vast amounts of text. In order to extract these facts from text, people have been working on rel…