39 citations · 67 across the 8 of their papers we have counts for
10 papers
WeFair: Fidelity-Aware Alignment from Human Feedback for Personalized Query Rewriting in Short-Video Search
Yingtao Ren, Aolin Li, Cheng Cheng +6
Short-video search requires compact query rewriters that infer personalized intent from brief, ambiguous queries under strict latency constraints. The challenge is to decide when p…
Efficient Multimodal Generative Recommendation with Latent Narrative Reasoning
Chenxing Wang, Nantao Zheng, Hao Miao +5
Generative recommendation reformulates item prediction as semantic identifier generation, yet episodic content introduces a fundamentally different setting where the target is dete…
HeadRank: Decoding-Free Passage Reranking via Preference-Aligned Attention Heads
Juyuan Wang, Chenxing Wang, Yuchen Fang +8
Decoding-free reranking methods that read relevance signals directly from LLM attention weights offer significant latency advantages over autoregressive approaches, yet suffer from…
When & How to Write for Personalized Demand-aware Query Rewriting in Video Search
Cheng cheng, Chenxing Wang, Aolin Li +3
In video search systems, user historical behaviors provide rich context for identifying search intent and resolving ambiguity. However, traditional methods utilizing implicit histo…
Towards Effective Fusion and Forecasting of Multimodal Spatio-temporal Data for Smart Mobility
Chenxing Wang
With the rapid development of location based services, multimodal spatio-temporal (ST) data including trajectories, transportation modes, traffic flow and social check-ins are bein…
Fine-Grained Trajectory-based Travel Time Estimation for Multi-city Scenarios Based on Deep Meta-Learning
Chenxing Wang, Fang Zhao, Haichao Zhang +3
Travel Time Estimation (TTE) is indispensable in intelligent transportation system (ITS). It is significant to achieve the fine-grained Trajectory-based Travel Time Estimation (TTT…
Spatio-Temporal meets Wavelet: Disentangled Traffic Flow Forecasting via Efficient Spectral Graph Attention Network
Yuchen Fang, Yanjun Qin, Haiyong Luo +4
Traffic forecasting is crucial for public safety and resource optimization, yet is very challenging due to three aspects: i) current existing works mostly exploit intricate tempora…
CDGNet: A Cross-Time Dynamic Graph-based Deep Learning Model for Traffic Forecasting
Yuchen Fang, Yanjun Qin, Haiyong Luo +4
Traffic forecasting is important in intelligent transportation systems of webs and beneficial to traffic safety, yet is very challenging because of the complex and dynamic spatio-t…
DMGCRN: Dynamic Multi-Graph Convolution Recurrent Network for Traffic Forecasting
Yanjun Qin, Yuchen Fang, Haiyong Luo +2
Traffic forecasting is a problem of intelligent transportation systems (ITS) and crucial for individuals and public agencies. Therefore, researches pay great attention to deal with…
STJLA: A Multi-Context Aware Spatio-Temporal Joint Linear Attention Network for Traffic Forecasting
Yuchen Fang, Yanjun Qin, Haiyong Luo +2
Traffic prediction has gradually attracted the attention of researchers because of the increase in traffic big data. Therefore, how to mine the complex spatio-temporal correlations…