Xiujun Li

2.1k citations
17 papers · 528 · h-index 11

Impact in

Papers in

Xiujun Li

17 papers receiving 515 citations

Peers

Xiujun Li
Comparison fields: 5 of 60
  • Artificial Intelligence 393
  • Computer Vision and Pattern Recognition 130
  • Soil Science 52
  • Health Informatics 2
  • Information Systems 30
Replace P. Punitha with:
P. Punitha India
Haitian Sun China
Larisa Markeeva Russia
Mingzhu Shen China
Saroj Kumar Lenka India
Alexis Drogoul France
Ilyes Jenhani Saudi Arabia
Ashu Sharma India
Ali Zeeshan Ijaz Pakistan
Shaomin Mu China
Xiujun Li relative to P. Punitha India P. Punitha's profile →
Citations per field
00.5×5.4×
P. Punitha · 1×
Citations per year

Countries citing papers authored by Xiujun Li

Since Specialization
Citations

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

Fields of papers citing papers by Xiujun Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Xiujun Li, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Xiujun Li Line = papers co-authored together Xiujun Li links everyone, so they are left out of the graph.

All Works

17 of 17 papers shown
#Work
1 2018101
2 201869
3 201866
4 201963
5 201845
6 201841
7 202132
8 201726
9 201821
10 202019
11 201919
12 20237
13 20207
14
Composite Task-Completion Dialogue System via Hierarchical Deep Reinforcement Learning.
20176
15 20223
16 20212
17
Efficient Dialogue Policy Learning with BBQ-Networks
20161

About Xiujun Li

Xiujun Li is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Soil Science, Nuclear and High Energy Physics and Civil and Structural Engineering, having authored 17 papers that have together received 528 indexed citations. Recurring topics across this work include Topic Modeling (10 papers), Speech and dialogue systems (9 papers), Soil Carbon and Nitrogen Dynamics (3 papers), Context-Aware Activity Recognition Systems (3 papers), Particle physics theoretical and experimental studies (3 papers), Quantum Chromodynamics and Particle Interactions (3 papers), High-Energy Particle Collisions Research (3 papers) and Multimodal Machine Learning Applications (3 papers). The work is most often cited by research in Artificial Intelligence (393 citations), Computer Vision and Pattern Recognition (130 citations), Soil Science (52 citations), Health Informatics (2 citations) and Information Systems (30 citations). Xiujun Li has collaborated with scholars based in United States, China and Taiwan. Frequent co-authors include Jianfeng Gao, Baolin Peng, Kam‐Fai Wong, Jun Liu, Yun-Nung Chen, Lihong Li, Aslı Çelikyılmaz, Jianfeng Gao, S. Faisal Ahmed and Zachary C. Lipton. Their work appears in journals such as Physics Letters B, Soil and Tillage Research, Soil Biology and Biochemistry, European Journal of Soil Science and Nuclear Science and Techniques.

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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