60 citations · 96 across the 34 of their papers we have counts for
6 papers · 1 filter
Towards Scalable Semantic Representation for Recommendation
Taolin Zhang, Junwei Pan, Jinpeng Wang +9
With recent advances in large language models (LLMs), there has been emerging numbers of research in developing Semantic IDs based on LLMs to enhance the performance of recommendat…
RAT: Retrieval-Augmented Transformer for Click-Through Rate Prediction
Yushen Li, Jinpeng Wang, Tao Dai +4
Predicting click-through rates (CTR) is a fundamental task for Web applications, where a key issue is to devise effective models for feature interactions. Current methodologies pre…
MISSRec: Pre-training and Transferring Multi-modal Interest-aware Sequence Representation for Recommendation
Jinpeng Wang, Ziyun Zeng, Yunxiao Wang +7
The goal of sequential recommendation (SR) is to predict a user's potential interested items based on her/his historical interaction sequences. Most existing sequential recommender…
Keyword-Based Diverse Image Retrieval by Semantics-aware Contrastive Learning and Transformer
Minyi Zhao, Jinpeng Wang, Dongliang Liao +3
In addition to relevance, diversity is an important yet less studied performance metric of cross-modal image retrieval systems, which is critical to user experience. Existing solut…
Hybrid Contrastive Quantization for Efficient Cross-View Video Retrieval
Jinpeng Wang, Bin Chen, Dongliang Liao +4
With the recent boom of video-based social platforms (e.g., YouTube and TikTok), video retrieval using sentence queries has become an important demand and attracts increasing resea…
Cross-Batch Negative Sampling for Training Two-Tower Recommenders
Jinpeng Wang, Jieming Zhu, Xiuqiang He
The two-tower architecture has been widely applied for learning item and user representations, which is important for large-scale recommender systems. Many two-tower models are tra…