activity
20192024
most citedImproving Knowledge-aware Recommendation with Multi-level Interactive Contrastive Learning

95 citations · 198 across the 20 of their papers we have counts for

collaborators

20 papers

cs.CL2024

Position Debiasing Fine-Tuning for Causal Perception in Long-Term Dialogue

Shixuan Fan, Wei Wei, Wendi Li +3

The core of the dialogue system is to generate relevant, informative, and human-like responses based on extensive dialogue history. Recently, dialogue generation domain has seen ma…

cs.CL2024

Personalized Topic Selection Model for Topic-Grounded Dialogue

Shixuan Fan, Wei Wei, Xiaofei Wen +3

Recently, the topic-grounded dialogue (TGD) system has become increasingly popular as its powerful capability to actively guide users to accomplish specific tasks through topic-gui…

cs.CL2024

Joint Multi-Facts Reasoning Network For Complex Temporal Question Answering Over Knowledge Graph

Rikui Huang, Wei Wei, Xiaoye Qu +3

Temporal Knowledge Graph (TKG) is an extension of regular knowledge graph by attaching the time scope. Existing temporal knowledge graph question answering (TKGQA) models solely ap…

cs.CL2023

MIRACLE: Towards Personalized Dialogue Generation with Latent-Space Multiple Personal Attribute Control

Zhenyi Lu, Wei Wei, Xiaoye Qu +3

Personalized dialogue systems aim to endow the chatbot agent with more anthropomorphic traits for human-like interactions. Previous approaches have explored explicitly user profile…

cs.IR2023

Multi-view Hypergraph Contrastive Policy Learning for Conversational Recommendation

Sen Zhao, Wei Wei, Xian-Ling Mao +5

Conversational recommendation systems (CRS) aim to interactively acquire user preferences and accordingly recommend items to users. Accurately learning the dynamic user preferences…

cs.AI2023

TREA: Tree-Structure Reasoning Schema for Conversational Recommendation

Wendi Li, Wei Wei, Xiaoye Qu +4

Conversational recommender systems (CRS) aim to timely trace the dynamic interests of users through dialogues and generate relevant responses for item recommendations. Recently, va…

cs.AI2023★ 4 cited

An Empirical Study on the Language Modal in Visual Question Answering

Daowan Peng, Wei Wei, Xian-Ling Mao +2

Generalization beyond in-domain experience to out-of-distribution data is of paramount significance in the AI domain. Of late, state-of-the-art Visual Question Answering (VQA) mode…

cs.IR2023

Towards Hierarchical Policy Learning for Conversational Recommendation with Hypergraph-based Reinforcement Learning

Sen Zhao, Wei Wei, Yifan Liu +6

Conversational recommendation systems (CRS) aim to timely and proactively acquire user dynamic preferred attributes through conversations for item recommendation. In each turn of C…

cs.CL2023

Gated Mechanism Enhanced Multi-Task Learning for Dialog Routing

Ziming Huang, Zhuoxuan Jiang, Ke Wang +3

Currently, human-bot symbiosis dialog systems, e.g., pre- and after-sales in E-commerce, are ubiquitous, and the dialog routing component is essential to improve the overall effici…

cs.CL2022★ 3 cited

STAGE: Span Tagging and Greedy Inference Scheme for Aspect Sentiment Triplet Extraction

Shuo Liang, Wei Wei, Xian-Ling Mao +3

Aspect Sentiment Triplet Extraction (ASTE) has become an emerging task in sentiment analysis research, aiming to extract triplets of the aspect term, its corresponding opinion term…

cs.CL2022

HCL-TAT: A Hybrid Contrastive Learning Method for Few-shot Event Detection with Task-Adaptive Threshold

Ruihan Zhang, Wei Wei, Xian-Ling Mao +2

Conventional event detection models under supervised learning settings suffer from the inability of transfer to newly-emerged event types owing to lack of sufficient annotations. A…

cs.CL2022

Capturing Global Structural Information in Long Document Question Answering with Compressive Graph Selector Network

Yuxiang Nie, Heyan Huang, Wei Wei +1

Long document question answering is a challenging task due to its demands for complex reasoning over long text. Previous works usually take long documents as non-structured flat te…

cs.CL2022

Sequential Topic Selection Model with Latent Variable for Topic-Grounded Dialogue

Xiaofei Wen, Wei Wei, Xian-Ling Mao

Recently, topic-grounded dialogue system has attracted significant attention due to its effectiveness in predicting the next topic to yield better responses via the historical cont…

cs.CV2022

Unsupervised Hashing with Semantic Concept Mining

Rong-Cheng Tu, Xian-Ling Mao, Kevin Qinghong Lin +5

Recently, to improve the unsupervised image retrieval performance, plenty of unsupervised hashing methods have been proposed by designing a semantic similarity matrix, which is bas…

cs.IR2022★ 43 cited

Multi-level Contrastive Learning Framework for Sequential Recommendation

Ziyang Wang, Huoyu Liu, Wei Wei +5

Sequential recommendation (SR) aims to predict the subsequent behaviors of users by understanding their successive historical behaviors. Recently, some methods for SR are devoted t…

cs.CL2022★ 20 cited

Improving Personality Consistency in Conversation by Persona Extending

Yifan Liu, Wei Wei, Jiayi Liu +3

Endowing chatbots with a consistent personality plays a vital role for agents to deliver human-like interactions. However, existing personalized approaches commonly generate respon…

cs.IR2022★ 95 cited

Improving Knowledge-aware Recommendation with Multi-level Interactive Contrastive Learning

Ding Zou, Wei Wei, Ziyang Wang +4

Incorporating Knowledge Graphs (KG) into recommeder system has attracted considerable attention. Recently, the technical trend of Knowledge-aware Recommendation (KGR) is to develop…

cs.IR2022

Person-job fit estimation from candidate profile and related recruitment history with co-attention neural networks

Ziyang Wang, Wei Wei, Chenwei Xu +2

Existing online recruitment platforms depend on automatic ways of conducting the person-job fit, whose goal is matching appropriate job seekers with job positions. Intuitively, the…

cs.CL2022★ 2 cited

Relational Triple Extraction: One Step is Enough

Yu-Ming Shang, Heyan Huang, Xin Sun +2

Extracting relational triples from unstructured text is an essential task in natural language processing and knowledge graph construction. Existing approaches usually contain two f…

cs.CL2019★ 31 cited

Position-Aware Self-Attention based Neural Sequence Labeling

Wei Wei, Zanbo Wang, Xianling Mao +3

Sequence labeling is a fundamental task in natural language processing and has been widely studied. Recently, RNN-based sequence labeling models have increasingly gained attentions…