activity
20202023
most citedRelational Reflection Entity Alignment

119 citations · 252 across the 17 of their papers we have counts for

collaborators

17 papers

cs.CL2023★ 9 cited

CodeIE: Large Code Generation Models are Better Few-Shot Information Extractors

Peng Li, Tianxiang Sun, Qiong Tang +4

Large language models (LLMs) pre-trained on massive corpora have demonstrated impressive few-shot learning ability on many NLP tasks. A common practice is to recast the task into a…

cs.CL2023★ 3 cited

HIORE: Leveraging High-order Interactions for Unified Entity Relation Extraction

Yijun Wang, Changzhi Sun, Yuanbin Wu +3

Entity relation extraction consists of two sub-tasks: entity recognition and relation extraction. Existing methods either tackle these two tasks separately or unify them with word-…

cs.CL2023

A Confidence-based Partial Label Learning Model for Crowd-Annotated Named Entity Recognition

Limao Xiong, Jie Zhou, Qunxi Zhu +7

Existing models for named entity recognition (NER) are mainly based on large-scale labeled datasets, which always obtain using crowdsourcing. However, it is hard to obtain a unifie…

cs.AI2022★ 1 cited

LightEA: A Scalable, Robust, and Interpretable Entity Alignment Framework via Three-view Label Propagation

Xin Mao, Wenting Wang, Yuanbin Wu +1

Entity Alignment (EA) aims to find equivalent entity pairs between KGs, which is the core step of bridging and integrating multi-source KGs. In this paper, we argue that existing G…

cs.CL2022

Prompt-based Connective Prediction Method for Fine-grained Implicit Discourse Relation Recognition

Hao Zhou, Man Lan, Yuanbin Wu +2

Due to the absence of connectives, implicit discourse relation recognition (IDRR) is still a challenging and crucial task in discourse analysis. Most of the current work adopted mu…

cs.CL2022

Few Clean Instances Help Denoising Distant Supervision

Yufang Liu, Ziyin Huang, Yijun Wang +5

Existing distantly supervised relation extractors usually rely on noisy data for both model training and evaluation, which may lead to garbage-in-garbage-out systems. To alleviate…

cs.CL2021

A Dual-Attention Neural Network for Pun Location and Using Pun-Gloss Pairs for Interpretation

Shen Liu, Meirong Ma, Hao Yuan +3

Pun location is to identify the punning word (usually a word or a phrase that makes the text ambiguous) in a given short text, and pun interpretation is to find out two different m…

cs.CL2021

From Alignment to Assignment: Frustratingly Simple Unsupervised Entity Alignment

Xin Mao, Wenting Wang, Yuanbin Wu +1

Cross-lingual entity alignment (EA) aims to find the equivalent entities between crosslingual KGs, which is a crucial step for integrating KGs. Recently, many GNN-based EA methods…

cs.AI2021★ 4 cited

Are Negative Samples Necessary in Entity Alignment? An Approach with High Performance, Scalability and Robustness

Xin Mao, Wenting Wang, Yuanbin Wu +1

Entity alignment (EA) aims to find the equivalent entities in different KGs, which is a crucial step in integrating multiple KGs. However, most existing EA methods have poor scalab…

cs.CL2021

UniRE: A Unified Label Space for Entity Relation Extraction

Yijun Wang, Changzhi Sun, Yuanbin Wu +3

Many joint entity relation extraction models setup two separated label spaces for the two sub-tasks (i.e., entity detection and relation classification). We argue that this setting…

cs.CL2021

Probabilistic Graph Reasoning for Natural Proof Generation

Changzhi Sun, Xinbo Zhang, Jiangjie Chen +5

In this paper, we investigate the problem of reasoning over natural language statements. Prior neural based approaches do not explicitly consider the inter-dependency among answers…

cs.AI2021★ 113 cited

Boosting the Speed of Entity Alignment 10*: Dual Attention Matching Network with Normalized Hard Sample Mining

Xin Mao, Wenting Wang, Yuanbin Wu +1

Seeking the equivalent entities among multi-source Knowledge Graphs (KGs) is the pivotal step to KGs integration, also known as \emph{entity alignment} (EA). However, most existing…

cs.CL2021★ 1 cited

Generating CCG Categories

Yufang Liu, Tao Ji, Yuanbin Wu +1

Previous CCG supertaggers usually predict categories using multi-class classification. Despite their simplicity, internal structures of categories are usually ignored. The rich sem…

cs.CL2021

In-Order Chart-Based Constituent Parsing

Yang Wei, Yuanbin Wu, Man Lan

We propose a novel in-order chart-based model for constituent parsing. Compared with previous CKY-style and top-down models, our model gains advantages from in-order traversal of a…

cs.IR2020★ 119 cited

Relational Reflection Entity Alignment

Xin Mao, Wenting Wang, Huimin Xu +2

Entity alignment aims to identify equivalent entity pairs from different Knowledge Graphs (KGs), which is essential in integrating multi-source KGs. Recently, with the introduction…

cs.CV2020★ 1 cited

Visual Attack and Defense on Text

Shengjun Liu, Ningkang Jiang, Yuanbin Wu

Modifying characters of a piece of text to their visual similar ones often ap-pear in spam in order to fool inspection systems and other conditions, which we regard as a kind of ad…

cs.CL2020★ 1 cited

A Span-based Linearization for Constituent Trees

Yang Wei, Yuanbin Wu, Man Lan

We propose a novel linearization of a constituent tree, together with a new locally normalized model. For each split point in a sentence, our model computes the normalizer on all s…