10 citations · 63 across the 40 of their papers we have counts for
8 papers · 1 filter
VaLiDRec: Variable-Length LLM-Aligned Semantic IDs for Generative Recommendation
Shutong Qiao, Wei Yuan, Tong Chen +3
Generative recommendation commonly represents items using fixed-length semantic identifiers (SIDs) constructed through clustering and quantization. However, these artificial codes…
Self-Gating Attention for Efficient Time Series Forecasting
Dezheng Wang, Tong Chen, Wei Yuan +3
Transformer architectures have shown strong potential in time series forecasting, where multi-head self-attention is widely used to capture temporal dependencies across historical…
Federated Learning and Unlearning for Recommendation with Personalized Data Sharing
Liang Qu, Jianxin Li, Wei Yuan +4
Federated recommender systems (FedRS) have emerged as a paradigm for protecting user privacy by keeping interaction data on local devices while coordinating model training through…
Agentic Mixed-Source Multi-Modal Misinformation Detection with Adaptive Test-Time Scaling
Wei Jiang, Tong Chen, Wei Yuan +2
Vision-language models (VLMs) have been proven effective for detecting multi-modal misinformation on social platforms, especially in zero-shot settings with unavailable or delayed…
SDFed: Bridging Local Global Discrepancy via Subspace Refinement and Divergence Control in Federated Prompt Learning
Yicheng Di, Wei Yuan, Tieke He +2
Vision-language pretrained models offer strong transferable representations, yet adapting them in privacy-sensitive multi-party settings is challenging due to the high communicatio…
When Text-as-Vision Meets Semantic IDs in Generative Recommendation: An Empirical Study
Shutong Qiao, Wei Yuan, Tong Chen +3
Semantic ID learning is a key interface in Generative Recommendation (GR) models, mapping items to discrete identifiers grounded in side information, most commonly via a pretrained…
Integrating Vision-Centric Text Understanding for Conversational Recommender Systems
Wei Yuan, Shutong Qiao, Tong Chen +3
Conversational Recommender Systems (CRSs) have attracted growing attention for their ability to deliver personalized recommendations through natural language interactions. To more…
QA-Merging: Query-Adaptive Reasoning via Layer Selective Model Merging
Zhaofeng Zhong, Wei Yuan, Tong Chen +4
Recent large reasoning models (LRMs) have achieved strong performance on complex reasoning tasks by generating a long chain-of-thought (Long-CoT). However, such lengthy reasoning i…