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.
The Many Faces of Robustness: A Critical Analysis of Out-of-Distribution Generalization
2021503 citationsDan Hendrycks, Steven Basart et al.2021 IEEE/CVF International Conference on Computer Vision (ICCV)profile →
Natural Adversarial Examples
2021374 citationsDan Hendrycks, Steven Basart et al.profile →
Countries citing papers authored by Jacob Steinhardt
Since
Specialization
Citations
This map shows the geographic impact of Jacob Steinhardt'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 Jacob Steinhardt with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jacob Steinhardt more than expected).
Fields of papers citing papers by Jacob Steinhardt
This network shows the impact of papers produced by Jacob Steinhardt. 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 Jacob Steinhardt. The network helps show where Jacob Steinhardt may publish in the future.
Co-authorship network of co-authors of Jacob Steinhardt
This figure shows the co-authorship network connecting the top 25 collaborators of Jacob Steinhardt.
A scholar is included among the top collaborators of Jacob Steinhardt 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 Jacob Steinhardt. Jacob Steinhardt is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Hendrycks, Dan, Steven Basart, Norman Mu, et al.. (2021). The Many Faces of Robustness: A Critical Analysis of Out-of-Distribution Generalization. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 8320–8329.503 indexed citations breakdown →
3.
Steinhardt, Jacob, et al.. (2021). Grounding Representation Similarity Through Statistical Testing. arXiv (Cornell University). 34.6 indexed citations
Hendrycks, Dan, Steven Basart, Mantas Mazeika, et al.. (2019). A Benchmark for Anomaly Segmentation.. arXiv (Cornell University).23 indexed citations
9.
Raghunathan, Aditi, Jacob Steinhardt, & Percy Liang. (2018). Certified Defenses against Adversarial Examples. arXiv (Cornell University).79 indexed citations
10.
Diakonikolas, Ilias, Gautam Kamath, Daniel M. Kane, et al.. (2018). Sever: A Robust Meta-Algorithm for Stochastic Optimization. eScholarship (California Digital Library). 1596–1606.17 indexed citations
11.
Steinhardt, Jacob & Percy Liang. (2016). Unsupervised Risk Estimation Using Only Conditional Independence Structure. arXiv (Cornell University). 29. 3657–3665.7 indexed citations
12.
Shi, Tianlin, Jacob Steinhardt, & Percy Liang. (2015). Learning Where to Sample in Structured Prediction. International Conference on Artificial Intelligence and Statistics. 875–884.7 indexed citations
13.
Steinhardt, Jacob & John C. Duchi. (2015). Minimax rates for memory-bounded sparse linear regression. Conference on Learning Theory. 1564–1587.5 indexed citations
14.
Steinhardt, Jacob & Percy Liang. (2015). Learning with relaxed supervision. Neural Information Processing Systems. 28. 2827–2835.4 indexed citations
15.
Steinhardt, Jacob, Gregory Valiant, & Stefan Wager. (2015). Memory, Communication, and Statistical Queries. Electronic colloquium on computational complexity. 22. 126–1516.2 indexed citations
Steinhardt, Jacob & Percy Liang. (2014). Adaptivity and Optimism: An Improved Exponentiated Gradient Algorithm. International Conference on Machine Learning. 1593–1601.11 indexed citations
18.
Steinhardt, Jacob & Percy Liang. (2014). Filtering with Abstract Particles. International Conference on Machine Learning. 727–735.2 indexed citations
19.
Steinhardt, Jacob & Zoubin Ghahramani. (2012). Flexible Martingale Priors for Deep Hierarchies.. Cambridge University Engineering Department Publications Database. 1108–1116.5 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.