Da Luo

582 total citations · 1 hit paper
12 papers, 307 citations indexed

About

Da Luo is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Da Luo has authored 12 papers receiving a total of 307 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 4 papers in Information Systems and 3 papers in Computer Vision and Pattern Recognition. Recurrent topics in Da Luo's work include Topic Modeling (5 papers), Recommender Systems and Techniques (4 papers) and Natural Language Processing Techniques (3 papers). Da Luo is often cited by papers focused on Topic Modeling (5 papers), Recommender Systems and Techniques (4 papers) and Natural Language Processing Techniques (3 papers). Da Luo collaborates with scholars based in China, Hong Kong and United States. Da Luo's co-authors include Kangyi Lin, Chao Huang, Lianghao Xia, Yuhao Yang, Kenneth D. Westover, Weiguo Lu, Hak Choy, Zohaib Iqbal, Yulong Yan and Dan Nguyen and has published in prestigious journals such as PLoS ONE, IEEE Access and Measurement.

In The Last Decade

Da Luo

12 papers receiving 293 citations

Hit Papers

Debiased Contrastive Learning for Sequential Recommendation 2023 2026 2024 2025 2023 25 50 75
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. Debiased Contrastive Learning for Sequential Recommendation
    2023 78 citations Yuhao Yang, Chao Huang et al. arXiv (Cornell University) profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Da Luo China 8 211 122 46 41 31 12 307
Xuejie Zhang China 9 292 1.4× 93 0.8× 37 0.8× 21 0.5× 57 1.8× 22 423
Li Jin China 10 284 1.3× 61 0.5× 30 0.7× 12 0.3× 19 0.6× 58 356
Darsana Josyula United States 9 162 0.8× 42 0.3× 21 0.5× 26 0.6× 36 1.2× 40 239
Bo Shen China 9 211 1.0× 93 0.8× 29 0.6× 16 0.4× 42 1.4× 37 371
Yizhen Zheng Australia 11 217 1.0× 90 0.7× 44 1.0× 6 0.1× 22 0.7× 20 294
Xiaoying Zhang China 8 85 0.4× 82 0.7× 22 0.5× 31 0.8× 18 0.6× 29 191
Wenke Huang China 10 352 1.7× 43 0.4× 54 1.2× 29 0.7× 40 1.3× 25 442
Qiang Cui China 8 169 0.8× 264 2.2× 57 1.2× 11 0.3× 41 1.3× 13 343

Countries citing papers authored by Da Luo

Since Specialization
Citations

This map shows the geographic impact of Da 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 Da Luo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Da Luo more than expected).

Fields of papers citing papers by Da Luo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Da 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 Da Luo. The network helps show where Da Luo may publish in the future.

Co-authorship network of co-authors of Da Luo

This figure shows the co-authorship network connecting the top 25 collaborators of Da Luo. A scholar is included among the top collaborators of Da 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 Da Luo. Da Luo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

12 of 12 papers shown
1.
Luo, Da, et al.. (2024). Synergistic Anchored Contrastive Pre-training for Few-Shot Relation Extraction. Proceedings of the AAAI Conference on Artificial Intelligence. 38(17). 18742–18750. 2 indexed citations
2.
Xia, Lianghao, et al.. (2024). DiffMM: Multi-Modal Diffusion Model for Recommendation. The HKU Scholars Hub (University of Hong Kong). 7591–7599. 16 indexed citations
3.
Yang, Yuhao, Lianghao Xia, Da Luo, Kangyi Lin, & Chao Huang. (2024). GraphPro: Graph Pre-training and Prompt Learning for Recommendation. The HKU Scholars Hub (University of Hong Kong). 3690–3699. 8 indexed citations
4.
5.
Yang, Yuhao, et al.. (2023). Debiased Contrastive Learning for Sequential Recommendation. arXiv (Cornell University). 1063–1073. 78 indexed citations breakdown →
6.
Min, Erxue, et al.. (2023). Scenario-Adaptive Feature Interaction for Click-Through Rate Prediction. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 4661–4672. 4 indexed citations
7.
8.
Luo, Da, et al.. (2020). Enhancing Aspect-Based Sentiment Analysis With Capsule Network. IEEE Access. 8. 100551–100561. 32 indexed citations
9.
Li, Lin, et al.. (2019). Automated groove identification and measurement using long short-term memory unit. Measurement. 141. 152–161. 4 indexed citations
10.
Luo, Da, et al.. (2019). Multi-Turn Response Selection for Chatbots With Hierarchical Aggregation Network of Multi-Representation. IEEE Access. 7. 111736–111745. 11 indexed citations
11.
Luo, Da, et al.. (2019). Improving BERT-Based Text Classification With Auxiliary Sentence and Domain Knowledge. IEEE Access. 7. 176600–176612. 78 indexed citations
12.
Iqbal, Zohaib, Da Luo, Peter Henry, et al.. (2018). Accurate real time localization tracking in a clinical environment using Bluetooth Low Energy and deep learning. PLoS ONE. 13(10). e0205392–e0205392. 47 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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