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20222024
most citedImproving Knowledge-aware Recommendation with Multi-level Interactive Contrastive Learning

95 citations · 115 across the 9 of their papers we have counts for

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6 papers · 1 filter

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

Reinforcement Learning with Token-level Feedback for Controllable Text Generation

Wendi Li, Wei Wei, Kaihe Xu +3

To meet the requirements of real-world applications, it is essential to control generations of large language models (LLMs). Prior research has tried to introduce reinforcement lea…

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.CL2023

AttenWalker: Unsupervised Long-Document Question Answering via Attention-based Graph Walking

Yuxiang Nie, Heyan Huang, Wei Wei +1

Annotating long-document question answering (long-document QA) pairs is time-consuming and expensive. To alleviate the problem, it might be possible to generate long-document QA pa…

cs.CL202220 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…