30 citations · 31 across the 5 of their papers we have counts for
Showing 2025Show all
3 papers · 1 filter
cs.IR2025
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…
cs.CL2025
GraphLAMA: Enabling Efficient Adaptation of Graph Language Models with Limited Annotations
Junze Chen, Cheng Yang, Shujie Li +4
Large language models (LLMs) have demonstrated their strong capabilities in various domains, and have been recently integrated for graph analysis as graph language models (GLMs). W…
cs.CL2025★ 1 cited
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…