Linhao Luo

1.3k total citations · 1 hit paper
25 papers, 466 citations indexed

About

Linhao Luo is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Linhao Luo has authored 25 papers receiving a total of 466 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Artificial Intelligence, 8 papers in Information Systems and 4 papers in Computer Vision and Pattern Recognition. Recurrent topics in Linhao Luo's work include Topic Modeling (7 papers), Advanced Graph Neural Networks (7 papers) and Recommender Systems and Techniques (5 papers). Linhao Luo is often cited by papers focused on Topic Modeling (7 papers), Advanced Graph Neural Networks (7 papers) and Recommender Systems and Techniques (5 papers). Linhao Luo collaborates with scholars based in Australia, China and United States. Linhao Luo's co-authors include Shirui Pan, Yufei Wang, Chen Chen, Jiapu Wang, Xindong Wu, Yuan-Fang Li, Gholamreza Haffari, Xiaofeng Zhang, Xiaofei Yang and Dinh Phung and has published in prestigious journals such as Nature Communications, IEEE Transactions on Knowledge and Data Engineering and Neural Computing and Applications.

In The Last Decade

Linhao Luo

19 papers receiving 454 citations

Hit Papers

Unifying Large Language Models and Knowledge Graphs: A Ro... 2024 2026 2025 2024 100 200 300
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Unifying Large Language Models and Knowledge Graphs: A Roadmap
    2024 373 citations Shirui Pan, Linhao Luo et al. IEEE Transactions on Knowledge and Data Engineering profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Linhao Luo Australia 8 298 78 57 53 43 25 466
Mehdi Naseriparsa Australia 8 266 0.9× 76 1.0× 41 0.7× 39 0.7× 32 0.7× 13 413
Dharmveer Singh Rajpoot India 9 343 1.2× 144 1.8× 26 0.5× 72 1.4× 27 0.6× 23 459
Adán José-García France 8 209 0.7× 49 0.6× 19 0.3× 59 1.1× 27 0.6× 16 348
Adila Alfa Krisnadhi Indonesia 11 284 1.0× 113 1.4× 47 0.8× 17 0.3× 49 1.1× 65 390

Countries citing papers authored by Linhao Luo

Since Specialization
Citations

This map shows the geographic impact of Linhao Luo's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Linhao Luo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Linhao Luo more than expected).

Fields of papers citing papers by Linhao Luo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Linhao Luo. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Linhao Luo. The network helps show where Linhao Luo may publish in the future.

Co-authorship network of co-authors of Linhao Luo

This figure shows the co-authorship network connecting the top 25 collaborators of Linhao Luo. A scholar is included among the top collaborators of Linhao Luo based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Linhao Luo. Linhao Luo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Li, Zhao, Linhao Luo, Ming Jin, et al.. (2025). Large lithium-ion battery model for secure shared electric bike battery in smart cities. Nature Communications. 16(1). 8415–8415. 1 indexed citations
2.
Luo, Linhao, Carl Yang, Evgeny Kharlamov, & Shirui Pan. (2025). Integrating Large Language Models and Knowledge Graphs for Next-level AGI. 33–36.
3.
Zhang, Xinni, et al.. (2025). G-Refer: Graph Retrieval-Augmented Large Language Model for Explainable Recommendation. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 240–251. 1 indexed citations
4.
Luo, Linhao, Cao Xiao, Adam Cross, et al.. (2025). A Survey on Unifying Large Language Models and Knowledge Graphs for Biomedicine and Healthcare. PubMed. 2025. 6195–6205. 2 indexed citations
5.
Wu, Tongtong, et al.. (2025). Continual Learning of Large Language Models. 16–17.
6.
Wang, Weiqing, et al.. (2024). Scalable Frame-Based Construction of Sociocultural Norm Bases for Socially Aware Dialogues. ACM Transactions on Multimedia Computing Communications and Applications. 21(11). 1–17.
7.
Pan, Shirui, Linhao Luo, Yufei Wang, et al.. (2024). Unifying Large Language Models and Knowledge Graphs: A Roadmap. IEEE Transactions on Knowledge and Data Engineering. 36(7). 3580–3599. 373 indexed citations breakdown →
8.
9.
Feng, Tao, Lizhen Qu, Yi Ying, et al.. (2024). RENOVI: A Benchmark Towards Remediating Norm Violations in Socio-Cultural Conversations. Monash University Research Portal (Monash University). 3104–3117. 3 indexed citations
10.
Nguyen, Thi Thanh Huong, et al.. (2024). Direct Evaluation of Chain-of-Thought in Multi-hop Reasoning with Knowledge Graphs. 2862–2883. 3 indexed citations
11.
Nayyeri, Mojtaba, et al.. (2024). NestE: Modeling Nested Relational Structures for Knowledge Graph Reasoning. Proceedings of the AAAI Conference on Artificial Intelligence. 38(8). 9205–9213. 4 indexed citations
12.
Luo, Linhao, et al.. (2024). Deep transformer-based heterogeneous spatiotemporal graph learning for geographical traffic forecasting. iScience. 27(7). 110175–110175. 7 indexed citations
13.
Luo, Linhao, et al.. (2023). GSim: A Graph Neural Network Based Relevance Measure for Heterogeneous Graphs. IEEE Transactions on Knowledge and Data Engineering. 35(12). 12693–12707. 7 indexed citations
14.
Luo, Linhao, Yuan-Fang Li, Gholamreza Haffari, & Shirui Pan. (2023). Normalizing Flow-based Neural Process for Few-Shot Knowledge Graph Completion. arXiv (Cornell University). 900–910. 17 indexed citations
15.
Wang, Yufei, Linhao Luo, Tao Feng, et al.. (2023). SocialDial: A Benchmark for Socially-Aware Dialogue Systems. 2712–2722. 8 indexed citations
16.
Chen, Kai, et al.. (2023). MedGraph: malicious edge detection in temporal reciprocal graph via multi-head attention-based GNN. Neural Computing and Applications. 2 indexed citations
17.
Luo, Linhao, et al.. (2022). DCRS: a deep contrast reciprocal recommender system to simultaneously capture user interest and attractiveness for online dating. Neural Computing and Applications. 34(8). 6413–6425. 1 indexed citations
18.
Luo, Linhao, et al.. (2022). Why do Semantically Unrelated Categories Appear in the Same Session?. Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval. 2065–2069. 1 indexed citations
19.
Li, Zhao, et al.. (2022). RMGN: A Regional Mask Guided Network for Parser-free Virtual Try-on. Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence. 1151–1158. 7 indexed citations
20.
Luo, Linhao, et al.. (2020). Deepbot: A Deep Neural Network based approach for Detecting Twitter Bots. IOP Conference Series Materials Science and Engineering. 719(1). 12063–12063. 12 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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