activity
20192025
most citedGlobal Context Enhanced Graph Neural Networks for Session-based Recommendation

554 citations · 1.6k across the 46 of their papers we have counts for

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Showing 2021Show all

6 papers · 1 filter

cs.CL2021★ 2 cited

Context-aware Entity Typing in Knowledge Graphs

Weiran Pan, Wei Wei, Xian-Ling Mao

Knowledge graph entity typing aims to infer entities' missing types in knowledge graphs which is an important but under-explored issue. This paper proposes a novel method for this…

cs.CL2021

Multi-granularity Textual Adversarial Attack with Behavior Cloning

Yangyi Chen, Jin Su, Wei Wei

Recently, the textual adversarial attack models become increasingly popular due to their successful in estimating the robustness of NLP models. However, existing works have obvious…

cs.IR2021★ 554 cited

Global Context Enhanced Graph Neural Networks for Session-based Recommendation

Ziyang Wang, Wei Wei, Gao Cong +3

Session-based recommendation (SBR) is a challenging task, which aims at recommending items based on anonymous behavior sequences. Almost all the existing solutions for SBR model us…

cs.CL2021★ 17 cited

Emotion-aware Chat Machine: Automatic Emotional Response Generation for Human-like Emotional Interaction

Wei Wei, Jiayi Liu, Xianling Mao +4

The consistency of a response to a given post at semantic-level and emotional-level is essential for a dialogue system to deliver human-like interactions. However, this challenge i…

cs.CV2021★ 15 cited

Context-aware Biaffine Localizing Network for Temporal Sentence Grounding

Daizong Liu, Xiaoye Qu, Jianfeng Dong +5

This paper addresses the problem of temporal sentence grounding (TSG), which aims to identify the temporal boundary of a specific segment from an untrimmed video by a sentence quer…

cs.CL2021★ 10 cited

A Robust and Domain-Adaptive Approach for Low-Resource Named Entity Recognition

Houjin Yu, Xian-Ling Mao, Zewen Chi +2

Recently, it has attracted much attention to build reliable named entity recognition (NER) systems using limited annotated data. Nearly all existing works heavily rely on domain-sp…