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.
2019fairseq: A Fast, Extensible Toolkit for Sequence Modeling
This map shows the geographic impact of Sam Gross'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 Sam Gross with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sam Gross more than expected).
This network shows the impact of papers produced by Sam Gross. 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 Sam Gross. The network helps show where Sam Gross may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Sam Gross, linked wherever they have
co-authored with each other. Click a name or a connecting line to browse the papers they
share.
Border = papers with Sam GrossLine = papers co-authored togetherSam Gross links everyone, so they are left out of the graph.
Sam Gross is a scholar working on General Social Sciences, Computer Vision and Pattern Recognition, Artificial Intelligence, Signal Processing and Statistical and Nonlinear Physics, having authored 6 papers that have together received 7.9k indexed citations. Recurring topics across this work include Topic Modeling (2 papers), Model Reduction and Neural Networks (1 paper), Genomics and Rare Diseases (1 paper), Computational and Text Analysis Methods (1 paper), Neural Networks and Applications (1 paper), Music and Audio Processing (1 paper), Advanced Vision and Imaging (1 paper) and Music Technology and Sound Studies (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (3.4k citations), Artificial Intelligence (3.8k citations), Signal Processing (579 citations), Media Technology (403 citations) and Computational Mathematics (25 citations). Sam Gross has collaborated with scholars based in Israel and United States. Frequent co-authors include Adam Lerer, Zachary DeVito, Luca Antiga, Alban Desmaison, Adam Paszke, Edward Z. Yang, Zeming Lin, Soumith Chintala, Myle Ott and Alexei Baevski. Their work appears in journals such as Nature Biotechnology and arXiv (Cornell University).
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.