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.
Natural Questions: A Benchmark for Question Answering Research
2019984 citationsTom Kwiatkowski, Jennimaria Palomaki et al.Transactions of the Association for Computational Linguisticsprofile →
A Decomposable Attention Model for Natural Language Inference
2016772 citationsAnkur P. Parikh, Oscar Täckström et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
hero ref
Countries citing papers authored by Jakob Uszkoreit
Since
Specialization
Citations
This map shows the geographic impact of Jakob Uszkoreit'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 Jakob Uszkoreit with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jakob Uszkoreit more than expected).
This network shows the impact of papers produced by Jakob Uszkoreit. 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 Jakob Uszkoreit. The network helps show where Jakob Uszkoreit may publish in the future.
Co-authorship network of co-authors of Jakob Uszkoreit
This figure shows the co-authorship network connecting the top 25 collaborators of Jakob Uszkoreit.
A scholar is included among the top collaborators of Jakob Uszkoreit 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 Jakob Uszkoreit. Jakob Uszkoreit 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
1.
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
2.
Locatello, Francesco, Dirk Weissenborn, Thomas Unterthiner, et al.. (2020). Object-Centric Learning with Slot Attention. Neural Information Processing Systems. 33. 11525–11538.13 indexed citations
Huang, Cheng-Zhi Anna, Ashish Vaswani, Jakob Uszkoreit, et al.. (2019). Music Transformer: Generating Music with Long-Term Structure. International Conference on Learning Representations.119 indexed citations
Kwiatkowski, Tom, Jennimaria Palomaki, Michael Collins, et al.. (2019). Natural Questions: A Benchmark for Question Answering Research. Transactions of the Association for Computational Linguistics. 7. 453–466.984 indexed citations breakdown →
7.
Huang, Cheng-Zhi Anna, Ashish Vaswani, Jakob Uszkoreit, et al.. (2018). An Improved Relative Self-Attention Mechanism for Transformer with Application to Music Generation. arXiv (Cornell University).21 indexed citations
Parikh, Ankur P., Oscar Täckström, Dipanjan Das, & Jakob Uszkoreit. (2016). A Decomposable Attention Model for Natural Language Inference. 2249–2255.772 indexed citations breakdown →
11.
Angeli, Gabor & Jakob Uszkoreit. (2013). Language-Independent Discriminative Parsing of Temporal Expressions. Meeting of the Association for Computational Linguistics. 1. 83–92.13 indexed citations
12.
Täckström, Oscar, Ryan McDonald, & Jakob Uszkoreit. (2012). Cross-lingual Word Clusters for Direct Transfer of Linguistic Structure. KTH Publication Database DiVA (KTH Royal Institute of Technology). 477–487.139 indexed citations
13.
DeNero, John, et al.. (2012). A Feature-Rich Constituent Context Model for Grammar Induction. Meeting of the Association for Computational Linguistics. 17–22.7 indexed citations
14.
Venugopal, Ashish, Jakob Uszkoreit, David Talbot, Franz Josef Och, & Juri Ganitkevitch. (2011). Watermarking the Outputs of Structured Prediction with an application in Statistical Machine Translation.. Empirical Methods in Natural Language Processing. 1363–1372.16 indexed citations
15.
DeNero, John & Jakob Uszkoreit. (2011). Inducing Sentence Structure from Parallel Corpora for Reordering. Empirical Methods in Natural Language Processing. 193–203.37 indexed citations
16.
Uszkoreit, Jakob, Jay Ponte, Ashok C. Popat, & Moshe Dubiner. (2010). Large Scale Parallel Document Mining for Machine Translation. International Conference on Computational Linguistics. 1101–1109.89 indexed citations
17.
Genzel, Dmitriy, Jakob Uszkoreit, & Franz Josef Och. (2010). "Poetic" Statistical Machine Translation: Rhyme and Meter. Empirical Methods in Natural Language Processing. 158–166.42 indexed citations
18.
Uszkoreit, Jakob & Thorsten Brants. (2008). Distributed Word Clustering for Large Scale Class-Based Language Modeling in Machine Translation. Meeting of the Association for Computational Linguistics. 755–762.52 indexed citations
Romeike, Bernd, et al.. (2006). Automated nuclear segmentation in the determination of the Ki-67 labeling index in meningiomas.. PubMed. 25(2). 67–73.40 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.