Loïc Magne

458 citations
2 papers · 172 · 1 hit paper · h-index 2

Impact in

    • Topic Modeling
    • Natural Language Processing Techniques
    • Advanced Text Analysis Techniques
    • Machine Learning in Healthcare
    • Sentiment Analysis and Opinion Mining
    • Text and Document Classification Technologies

Papers in

Loïc Magne

2 papers receiving 162 citations

Loïc Magne's Hit Papers

MTEB: Massive Text Embedding Benchmark 2023 · 171 citations
1710+1+2Years since publication50100150

Peers

Loïc Magne
Comparison fields: 5 of 51
  • Artificial Intelligence 119
  • Health Informatics 4
  • Computer Vision and Pattern Recognition 24
  • Information Systems 26
  • Management Science and Operations Research 12
Replace Aleksandra Piktus with:
Aleksandra Piktus Germany
Matthias Gallé France
Benjamin Heinzerling Japan
Iulia Turc United States
Or Honovich Israel
David Ifeoluwa Adelani Germany
Jane Dwivedi-Yu United Kingdom
Linyong Nan United States
Nora Kassner Germany
Loïc Magne relative to Aleksandra Piktus Germany Aleksandra Piktus's profile →
Citations per field
00.5×7.5×
Aleksandra Piktus · 1×
Citations per year

Countries citing papers authored by Loïc Magne

Since Specialization
Citations

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

Fields of papers citing papers by Loïc Magne

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 4 scholars most cited alongside Loïc Magne, 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 Loïc Magne Line = papers co-authored together Loïc Magne links everyone, so they are left out of the graph.

All Works

2 of 2 papers shown
#Work
1
MTEB: Massive Text Embedding Benchmark
Hit paper breakdown →
2023171
2 20231

About Loïc Magne

Loïc Magne is a scholar working on Computer Networks and Communications, Artificial Intelligence, Computational Theory and Mathematics, Infectious Diseases and Organic Chemistry, having authored 2 papers that have together received 172 indexed citations. Recurring topics across this work include Complexity and Algorithms in Graphs (1 paper), Topic Modeling (1 paper), Advanced Graph Neural Networks (1 paper), Interconnection Networks and Systems (1 paper), Advanced Graph Theory Research (1 paper) and Natural Language Processing Techniques (1 paper). The work is most often cited by research in Artificial Intelligence (119 citations), Health Informatics (4 citations), Computer Vision and Pattern Recognition (24 citations), Information Systems (26 citations) and Management Science and Operations Research (12 citations). Loïc Magne has collaborated with scholars based in Burundi and France. Frequent co-authors include Niklas Muennighoff, Nils Reimers, Christophe Paul and Dimitrios M. Thilikos. Their work appears in journals such as Discrete Applied Mathematics.

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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