554 citations · 1.6k across the 46 of their papers we have counts for
46 papers
Selecting and Merging: Towards Adaptable and Scalable Named Entity Recognition with Large Language Models
Zhuojun Ding, Wei Wei, Chenghao Fan
Supervised fine-tuning (SFT) is widely used to align large language models (LLMs) with information extraction (IE) tasks, such as named entity recognition (NER). However, annotatin…
Multi-Relational Contrastive Learning for Recommendation
Wei Wei, Lianghao Xia, Chao Huang
Personalized recommender systems play a crucial role in capturing users' evolving preferences over time to provide accurate and effective recommendations on various online platform…
HyperBandit: Contextual Bandit with Hypernewtork for Time-Varying User Preferences in Streaming Recommendation
Chenglei Shen, Xiao Zhang, Wei Wei +1
In real-world streaming recommender systems, user preferences often dynamically change over time (e.g., a user may have different preferences during weekdays and weekends). Existin…
Towards Autocomplete Strategies for Visualization Construction
Wei Wei, Samuel Huron, Yvonne Jansen
Constructive visualization uses physical data units - tokens - to enable non-experts to create personalized visualizations engagingly. However, its physical nature limits efficienc…
SSLRec: A Self-Supervised Learning Framework for Recommendation
Xubin Ren, Lianghao Xia, Yuhao Yang +4
Self-supervised learning (SSL) has gained significant interest in recent years as a solution to address the challenges posed by sparse and noisy data in recommender systems. Despit…
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…