Linyao Yang

511 citations
17 papers · 274 · 1 hit paper · h-index 9

Impact in

Papers in

Linyao Yang

13 papers receiving 265 citations

Linyao Yang's Hit Papers

Give us the Facts: Enhancing Large Language Models With Knowledge Graphs for Fact-Aware Language Modeling 2024 · 86 citations
860+1Years since publication255075

Peers

Linyao Yang
Comparison fields: 5 of 63
  • Health Informatics 5
  • Artificial Intelligence 111
  • Ocean Engineering 35
  • Transportation 14
  • Computer Networks and Communications 46
Replace Yuzheng Li with:
Yuzheng Li China
Pengzhan Zhou China
Yanyu Cheng China
Yinuo Zhao China
Jinghua Zhu China
Bhupesh Kumar Dewangan India
Sandeep Harit India
Leon Kester Netherlands
Linyao Yang relative to Yuzheng Li China Yuzheng Li's profile →
Citations per field
00.5×2.8×
Yuzheng Li · 1×
Citations per year

Countries citing papers authored by Linyao Yang

Since Specialization
Citations

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

Fields of papers citing papers by Linyao Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Linyao Yang, 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 Linyao Yang Line = papers co-authored together Linyao Yang links everyone, so they are left out of the graph.

All Works

17 of 17 papers shown
#Work
1
Give us the Facts: Enhancing Large Language Models With Knowledge Graphs for Fact-Aware Language Modeling
Hit paper breakdown →
202486
2 202038
3 202130
4 201826
5 202023
6 202218
7 201817
8 202213
9 202112
10 20217
11 20242
12 20251
13 20201
14
Leveraging Large Language Models for Enhanced Digital Twin Modeling: Trends, Methods, and Challenges
20250
15 20240
16 20230
17 20250

About Linyao Yang

Linyao Yang is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering, Management Science and Operations Research, Ocean Engineering and Safety, Risk, Reliability and Quality, having authored 17 papers that have together received 274 indexed citations. Recurring topics across this work include Topic Modeling (7 papers), Advanced Graph Neural Networks (5 papers), Data Quality and Management (4 papers), Evacuation and Crowd Dynamics (3 papers), Vehicular Ad Hoc Networks (VANETs) (3 papers), Wireless Body Area Networks (2 papers), Natural Language Processing Techniques (2 papers) and IoT Networks and Protocols (2 papers). The work is most often cited by research in Health Informatics (5 citations), Artificial Intelligence (111 citations), Ocean Engineering (35 citations), Transportation (14 citations) and Computer Networks and Communications (46 citations). Linyao Yang has collaborated with scholars based in China, Macao and United States. Frequent co-authors include Xiao Wang, Fei–Yue Wang, Shuangshuang Han, Hongyang Chen, Xiao Ding, Zhao Li, Xindong Wu, Yuke Li, Tingting Yao and Lingxi Li. Their work appears in journals such as IEEE Transactions on Computational Social Systems, IEEE Internet of Things Journal, IEEE/CAA Journal of Automatica Sinica, Knowledge-Based Systems and Neurocomputing.

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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