Holger Schwenk

83 papers receiving 3.3k citations

Hit Papers

Supervised Learning of Universal Sentence Representations...20172026202020232017201820182505007501000

Peers

Holger Schwenk
Comparison fields: 5 of 135
  • Artificial Intelligence 3.5k
  • Computer Vision and Pattern Recognition 816
  • Signal Processing 317
  • Information Systems 264
  • Molecular Biology 142
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Sergey Edunov United States
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Citations per year

Countries citing papers authored by Holger Schwenk

Since Specialization
Citations

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

Fields of papers citing papers by Holger Schwenk

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Holger Schwenk

This figure shows the co-authorship network connecting the top 25 collaborators of Holger Schwenk. A scholar is included among the top collaborators of Holger Schwenk 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 Holger Schwenk. Holger Schwenk 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 7
2 2
3 3
4 5
5
Multimodal and Multilingual Embeddings for Large-Scale Speech Mining
17
6
Beyond English-Centric Multilingual Machine Translation
11
7
Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyondbreakdown →
426
8
Supervised Learning of Universal Sentence Representations from Natural\n Language Inference Databreakdown →
1002
9
OCR Error Correction Using Statistical Machine Translation
15
10
THE MATECAT TOOL
37
11
LIUM's SMT Machine Translation Systems for WMT 2012
0
12
A General Framework to Weight Heterogeneous Parallel Data for Model Adaptation in Statistical MT.
1
13
N-gram-based machine translation enhanced with neural networks for the French-English BTEC-IWSLT'10 task.
6
14
Lium smt machine translation system for wmt 2010
3
15
Translation model adaptation for an Arabic/French news translation system by lightly-supervised training
21
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Investigations on large-scale lightly-supervised training for statistical machine translation
39
17
Smooth Bilingual N-gram Translation
26
18
Training Methods for Adaptive Boosting of Neural Networks
28
19
Transformation Invariant Autoassociation with Application to Handwritten Character Recognition
36
20
BEST/1 - Design of a tool for computer system capacity planning.
10

About Holger Schwenk

Holger Schwenk is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition, having authored 93 papers that have together received 3.8k indexed citations. Recurring topics across this work include Natural Language Processing Techniques (71 papers), Topic Modeling (55 papers) and Speech Recognition and Synthesis (24 papers). The work is most often cited by research in Artificial Intelligence (3.5k citations), Computer Vision and Pattern Recognition (816 citations) and Signal Processing (317 citations). Holger Schwenk has collaborated with scholars based in France, United States and Spain. Frequent co-authors include Alexis Conneau, Loïc Barrault, Mikel Artetxe, Douwe Kiela, Antoine Bordes, Yoshua Bengio, Jean‐Luc Gauvain, Guillaume Lample, Ruty Rinott and Samuel Bowman. Their work appears in journals such as Neural Computation, Journal of Machine Learning Research and European Journal of Inorganic Chemistry.

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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