4 papers
Multimodal Generative Retrieval Model with Staged Pretraining for Food Delivery on Meituan
Boyu Chen, Tai Guo, Weiyu Cui +4
Multimodal retrieval models are becoming increasingly important in scenarios such as food delivery, where rich multimodal features can meet diverse user needs and enable precise re…
CORONA: A Coarse-to-Fine Framework for Graph-based Recommendation with Large Language Models
Junze Chen, Xinjie Yang, Cheng Yang +4
Recommender systems (RSs) are designed to retrieve candidate items a user might be interested in from a large pool. A common approach is using graph neural networks (GNNs) to captu…
PathRAG: Pruning Graph-based Retrieval Augmented Generation with Relational Paths
Boyu Chen, Zirui Guo, Zidan Yang +5
Retrieval-augmented generation (RAG) improves the response quality of large language models (LLMs) by retrieving knowledge from external databases. Typical RAG approaches split the…
Invariant debiasing learning for recommendation via biased imputation
Ting Bai, Weijie Chen, Cheng Yang +1
Previous debiasing studies utilize unbiased data to make supervision of model training. They suffer from the high trial risks and experimental costs to obtain unbiased data. Recent…