Nils Reimers

24 papers receiving 5.4k citations

Hit Papers

Sentence-BERT: Sentence Embeddings using Siamese BERT-Net...20192026202120232019202310002.0k3.0k4.0k5.0k

Peers

Nils Reimers
Comparison fields: 5 of 157
  • Artificial Intelligence 4.1k
  • Information Systems 1.0k
  • Computer Vision and Pattern Recognition 920
  • Sociology and Political Science 437
  • Management Science and Operations Research 266
Replace Édouard Grave with:
Édouard Grave Israel
Yoav Goldberg Israel
Steven Bethard United States
Steven Bird Australia
Edward Loper United States
Xuanjing Huang China
Qiaozhu Mei United States
Mihai Surdeanu United States
David McClosky United States
Kathleen McKeown United States
Nils Reimers relative to Édouard Grave Israel Édouard Grave's profile →
Citations per field
00.5×3.2×
Édouard Grave · 1×
Citations per year

Countries citing papers authored by Nils Reimers

Since Specialization
Citations

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

Fields of papers citing papers by Nils Reimers

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nils Reimers

This figure shows the co-authorship network connecting the top 25 collaborators of Nils Reimers. A scholar is included among the top collaborators of Nils Reimers 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 Nils Reimers. Nils Reimers 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
#WorkIndexed citations
1 0
2
MTEB: Massive Text Embedding Benchmarkbreakdown →
121
3 0
4 34
5 2
6 31
7 58
8
Breaking the Subtopic Barrier in Cross-Document Event Coreference Resolution
6
9
Sentence-BERT: Sentence Embeddings using Siamese BERT-Networksbreakdown →
5203
10 12
11
Task-Oriented Intrinsic Evaluation of Semantic Textual Similarity
27
12 2
13 25
14 1
15 2
16 34
17 6
18
GermEval-2014: Nested Named Entity Recognition with Neural Networks
26
19 13
20 66

About Nils Reimers

Nils Reimers is a scholar working on Orthopedics and Sports Medicine, Oral Surgery and Artificial Intelligence, having authored 27 papers that have together received 5.7k indexed citations. Recurring topics across this work include Natural Language Processing Techniques (10 papers), Topic Modeling (9 papers) and Advanced Text Analysis Techniques (4 papers). The work is most often cited by research in Artificial Intelligence (4.1k citations), General Social Sciences (159 citations) and Information Systems (1.0k citations). Nils Reimers has collaborated with scholars based in Germany, Switzerland and Australia. Frequent co-authors include Iryna Gurevych, Niklas Muennighoff, Loïc Magne, Kexin Wang, Rainer Burgkart, Mauricio Reyes, Philippe Büchler, Nandan Thakur, Stefan Weber and Miguel Á. González Ballester. Their work appears in journals such as Clinical Orthopaedics and Related Research, Medical Image Analysis and Transactions of the Association for Computational Linguistics.

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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