activity
20192021
most citedRelation-Aware Entity Alignment for Heterogeneous Knowledge Graphs

238 citations · 292 across the 16 of their papers we have counts for

collaborators

16 papers

cs.CL2021

Exploring Distantly-Labeled Rationales in Neural Network Models

Quzhe Huang, Shengqi Zhu, Yansong Feng +1

Recent studies strive to incorporate various human rationales into neural networks to improve model performance, but few pay attention to the quality of the rationales. Most existi…

cs.CL2021★ 5 cited

Three Sentences Are All You Need: Local Path Enhanced Document Relation Extraction

Quzhe Huang, Shengqi Zhu, Yansong Feng +3

Document-level Relation Extraction (RE) is a more challenging task than sentence RE as it often requires reasoning over multiple sentences. Yet, human annotators usually use a smal…

cs.CL2021★ 4 cited

Why Machine Reading Comprehension Models Learn Shortcuts?

Yuxuan Lai, Chen Zhang, Yansong Feng +2

Recent studies report that many machine reading comprehension (MRC) models can perform closely to or even better than humans on benchmark datasets. However, existing works indicate…

cs.CL2021★ 3 cited

Lattice-BERT: Leveraging Multi-Granularity Representations in Chinese Pre-trained Language Models

Yuxuan Lai, Yijia Liu, Yansong Feng +2

Chinese pre-trained language models usually process text as a sequence of characters, while ignoring more coarse granularity, e.g., words. In this work, we propose a novel pre-trai…

cs.CL2021★ 3 cited

Everything Has a Cause: Leveraging Causal Inference in Legal Text Analysis

Xiao Liu, Da Yin, Yansong Feng +2

Causal inference is the process of capturing cause-effect relationship among variables. Most existing works focus on dealing with structured data, while mining causal relationship…

cs.CL2021★ 3 cited

Dialogue History Matters! Personalized Response Selectionin Multi-turn Retrieval-based Chatbots

Juntao Li, Chang Liu, Chongyang Tao +4

Existing multi-turn context-response matching methods mainly concentrate on obtaining multi-level and multi-dimension representations and better interactions between context uttera…

cs.CL2020★ 7 cited

Meaningful Answer Generation of E-Commerce Question-Answering

Shen Gao, Xiuying Chen, Zhaochun Ren +2

In e-commerce portals, generating answers for product-related questions has become a crucial task. In this paper, we focus on the task of product-aware answer generation, which lea…

cs.CL2020★ 9 cited

Learning to Respond with Your Favorite Stickers: A Framework of Unifying Multi-Modality and User Preference in Multi-Turn Dialog

Shen Gao, Xiuying Chen, Li Liu +2

Stickers with vivid and engaging expressions are becoming increasingly popular in online messaging apps, and some works are dedicated to automatically select sticker response by ma…

cs.CL2020★ 5 cited

Knowledge-Grounded Dialogue Generation with Pre-trained Language Models

Xueliang Zhao, Wei Wu, Can Xu +3

We study knowledge-grounded dialogue generation with pre-trained language models. To leverage the redundant external knowledge under capacity constraint, we propose equipping respo…

cs.CL2020

Cross-Lingual Low-Resource Set-to-Description Retrieval for Global E-Commerce

Juntao Li, Chang Liu, Jian Wang +5

With the prosperous of cross-border e-commerce, there is an urgent demand for designing intelligent approaches for assisting e-commerce sellers to offer local products for consumer…

cs.CL2020★ 12 cited

Neighborhood Matching Network for Entity Alignment

Yuting Wu, Xiao Liu, Yansong Feng +2

Structural heterogeneity between knowledge graphs is an outstanding challenge for entity alignment. This paper presents Neighborhood Matching Network (NMN), a novel entity alignmen…

cs.CL2019★ 1 cited

Integrating Relation Constraints with Neural Relation Extractors

Yuan Ye, Yansong Feng, Bingfeng Luo +2

Recent years have seen rapid progress in identifying predefined relationship between entity pairs using neural networks NNs. However, such models often make predictions for each en…

cs.CL2019★ 1 cited

Transformation of Dense and Sparse Text Representations

Wenpeng Hu, Mengyu Wang, Bing Liu +5

Sparsity is regarded as a desirable property of representations, especially in terms of explanation. However, its usage has been limited due to the gap with dense representations.…

cs.DM2019

Effects of Some Operations on Domination Chromatic Number in Graphs

Yangyang Zhou, Dongyang Zhao

For a simple graph , a domination coloring of is a proper vertex coloring such that every vertex of dominates at least one color class, and every color class is dominate…

cs.CL2019★ 238 cited

Relation-Aware Entity Alignment for Heterogeneous Knowledge Graphs

Yuting Wu, Xiao Liu, Yansong Feng +3

Entity alignment is the task of linking entities with the same real-world identity from different knowledge graphs (KGs), which has been recently dominated by embedding-based metho…

cs.LG2019★ 1 cited

Deep Hierarchical Reinforcement Learning Based Recommendations via Multi-goals Abstraction

Dongyang Zhao, Liang Zhang, Bo Zhang +3

The recommender system is an important form of intelligent application, which assists users to alleviate from information redundancy. Among the metrics used to evaluate a recommend…