Yingli Zhou

Orcid: 0009-0008-5630-6822

According to our database1, Yingli Zhou authored at least 14 papers between 2022 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2025
CUE-RAG: Towards Accurate and Cost-Efficient Graph-Based RAG via Multi-Partite Graph and Query-Driven Iterative Retrieval.
CoRR, July, 2025

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora.
CoRR, June, 2025

Scalable Approximate Biclique Counting over Large Bipartite Graphs.
CoRR, May, 2025

In-depth Analysis of Graph-based RAG in a Unified Framework.
CoRR, March, 2025

Efficient Historical Butterfly Counting in Large Temporal Bipartite Networks via Graph Structure-aware Index.
Proc. VLDB Endow., February, 2025

ArchRAG: Attributed Community-based Hierarchical Retrieval-Augmented Generation.
CoRR, February, 2025

UTCS: Effective Unsupervised Temporal Community Search with Pre-training of Temporal Dynamics and Subgraph Knowledge.
Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2025

2024
In-depth Analysis of Densest Subgraph Discovery in a Unified Framework.
Proc. VLDB Endow., December, 2024

Efficient Maximal Motif-Clique Enumeration over Large Heterogeneous Information Networks.
Proc. VLDB Endow., July, 2024

Efficient Parallel D-core Decomposition at Scale.
Proc. VLDB Endow., June, 2024

A Counting-based Approach for Efficient k-Clique Densest Subgraph Discovery.
Proc. ACM Manag. Data, 2024

Efficient Historical Butterfly Counting in Large Temporal Bipartite Networks via Graph Structure-aware Index.
CoRR, 2024

2023
Influential Community Search over Large Heterogeneous Information Networks.
Proc. VLDB Endow., 2023

2022
Understanding users' requirements precisely: a double Bi-LSTM-CRF joint model for detecting user's intentions and slot tags.
Neural Comput. Appl., 2022


  Loading...