Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Scaling Vision Transformers
2022430 citationsXiaohua Zhai, Alexander Kolesnikov et al.2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)profile →
This map shows the geographic impact of Lucas Beyer'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 Lucas Beyer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lucas Beyer more than expected).
This network shows the impact of papers produced by Lucas Beyer. 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 Lucas Beyer. The network helps show where Lucas Beyer may publish in the future.
Co-authorship network of co-authors of Lucas Beyer
This figure shows the co-authorship network connecting the top 25 collaborators of Lucas Beyer.
A scholar is included among the top collaborators of Lucas Beyer 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 Lucas Beyer. Lucas Beyer is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Zhai, Xiaohua, Basil Mustafa, А. И. Колесников, & Lucas Beyer. (2023). Sigmoid Loss for Language Image Pre-Training. 11941–11952.173 indexed citations breakdown →
Zhai, Xiaohua, Xiao Wang, Basil Mustafa, et al.. (2022). LiT: Zero-Shot Transfer with Locked-image text Tuning. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 18102–18112.207 indexed citations breakdown →
6.
Zhai, Xiaohua, Alexander Kolesnikov, Neil Houlsby, & Lucas Beyer. (2022). Scaling Vision Transformers. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 1204–1213.430 indexed citations breakdown →
7.
Dosovitskiy, Alexey, Lucas Beyer, Alexander Kolesnikov, et al.. (2021). An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale. International Conference on Learning Representations.143 indexed citations
8.
Beyer, Lucas, et al.. (2019). Effect of a Global Metronome on Ensemble Accuracy in Networked Music Performance. Journal of the Audio Engineering Society.9 indexed citations
9.
Kolesnikov, Alexander, Lucas Beyer, Xiaohua Zhai, et al.. (2019). Large Scale Learning of General Visual Representations for Transfer.. arXiv (Cornell University).26 indexed citations
10.
Zhai, Xiaohua, Joan Puigcerver, Alexander Kolesnikov, et al.. (2019). The Visual Task Adaptation Benchmark. arXiv (Cornell University).22 indexed citations
Beyer, Lucas, Alexander Hermans, Timm Linder, Kai O. Arras, & Bastian Leibe. (2018). Deep Person Detection in Two-Dimensional Range Data. IEEE Robotics and Automation Letters. 3(3). 2726–2733.23 indexed citations
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.