3 papers
cs.CL2026
LatentRAG: Latent Reasoning and Retrieval for Efficient Agentic RAG
Yijia Zheng, Marcel Worring
Single-step retrieval-augmented generation (RAG) provides an efficient way to incorporate external information for simple question answering tasks but struggles with complex questi…
cs.LG2025
Modeling Edge-Specific Node Features through Co-Representation Neural Hypergraph Diffusion
Yijia Zheng, Marcel Worring
Hypergraphs are widely being employed to represent complex higher-order relations in real-world applications. Most existing research on hypergraph learning focuses on node-level or…
cs.LG2025
A Survey of Large Language Models for Data Challenges in Graphs
Mengran Li, Pengyu Zhang, Wenbin Xing +11
Graphs are a widely used paradigm for representing non-Euclidean data, with applications ranging from social network analysis to biomolecular prediction. While graph learning has a…