2 citations · 5 across the 13 of their papers we have counts for
13 papers
Turning Semantics into Topology: LLM-Driven Attribute Augmentation for Collaborative Filtering
Junjie Meng, Ranxu zhang, Wei Wu +6
Large Language Models (LLMs) have shown great potential for enhancing recommender systems through their extensive world knowledge and reasoning capabilities. However, effectively t…
Enhancing Conversational Recommender Systems with Tree-Structured Knowledge and Pretrained Language Models
Yongwen Ren, Chao Wang, Peng Du +3
Recent advances in pretrained language models (PLMs) have significantly improved conversational recommender systems (CRS), enabling more fluent and context-aware interactions. To f…
Virne: A Comprehensive Benchmark for RL-based Network Resource Allocation in NFV
Tianfu Wang, Liwei Deng, Xi Chen +7
Resource allocation (RA) is critical to efficient service deployment in Network Function Virtualization (NFV), a transformative networking paradigm. Recently, deep Reinforcement Le…
Boosting Knowledge Graph-based Recommendations through Confidence-Aware Augmentation with Large Language Models
Rui Cai, Chao Wang, Qianyi Cai +2
Knowledge Graph-based recommendations have gained significant attention due to their ability to leverage rich semantic relationships. However, constructing and maintaining Knowledg…
Hierarchical Time-Aware Mixture of Experts for Multi-Modal Sequential Recommendation
Shengzhe Zhang, Liyi Chen, Dazhong Shen +2
Multi-modal sequential recommendation (SR) leverages multi-modal data to learn more comprehensive item features and user preferences than traditional SR methods, which has become a…
TokenSelect: Efficient Long-Context Inference and Length Extrapolation for LLMs via Dynamic Token-Level KV Cache Selection
Wei Wu, Zhuoshi Pan, Chao Wang +6
Rapid advances in Large Language Models (LLMs) have spurred demand for processing extended context sequences in contemporary applications. However, this progress faces two challeng…
Towards Constraint-aware Learning for Resource Allocation in NFV Networks
Tianfu Wang, Long Yang, Chao Wang +6
Virtual Network Embedding (VNE) is a fundamental resource allocation challenge that is associated with hard and multifaceted constraints in network function virtualization (NFV). E…
Structure-Enhanced Protein Instruction Tuning: Towards General-Purpose Protein Understanding with LLMs
Wei Wu, Chao Wang, Liyi Chen +6
Proteins, as essential biomolecules, play a central role in biological processes, including metabolic reactions and DNA replication. Accurate prediction of their properties and fun…
COMET: NFT Price Prediction with Wallet Profiling
Tianfu Wang, Liwei Deng, Chao Wang +5
As the non-fungible token (NFT) market flourishes, price prediction emerges as a pivotal direction for investors gaining valuable insight to maximize returns. However, existing wor…
FlagVNE: A Flexible and Generalizable Reinforcement Learning Framework for Network Resource Allocation
Tianfu Wang, Qilin Fan, Chao Wang +4
Virtual network embedding (VNE) is an essential resource allocation task in network virtualization, aiming to map virtual network requests (VNRs) onto physical infrastructure. Rein…
DGR: A General Graph Desmoothing Framework for Recommendation via Global and Local Perspectives
Leilei Ding, Dazhong Shen, Chao Wang +3
Graph Convolutional Networks (GCNs) have become pivotal in recommendation systems for learning user and item embeddings by leveraging the user-item interaction graph's node informa…
AFDGCF: Adaptive Feature De-correlation Graph Collaborative Filtering for Recommendations
Wei Wu, Chao Wang, Dazhong Shen +3
Collaborative filtering methods based on graph neural networks (GNNs) have witnessed significant success in recommender systems (RS), capitalizing on their ability to capture colla…
Graph Signal Diffusion Model for Collaborative Filtering
Yunqin Zhu, Chao Wang, Qi Zhang +1
Collaborative filtering is a critical technique in recommender systems. It has been increasingly viewed as a conditional generative task for user feedback data, where newly develop…