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.
MoverScore: Text Generation Evaluating with Contextualized Embeddings and Earth Mover Distance
2019274 citationsWei Zhao, Steffen Eger et al.TUbilio (Technical University of Darmstadt)profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Steffen Eger'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 Steffen Eger with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Steffen Eger more than expected).
This network shows the impact of papers produced by Steffen Eger. 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 Steffen Eger. The network helps show where Steffen Eger may publish in the future.
Co-authorship network of co-authors of Steffen Eger
This figure shows the co-authorship network connecting the top 25 collaborators of Steffen Eger.
A scholar is included among the top collaborators of Steffen Eger 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 Steffen Eger. Steffen Eger is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Eger, Steffen, et al.. (2019). Practitioner’s view: A comparison and a survey of lemmatization and morphological tagging in German and Latin. 7. 1–52.2 indexed citations
Eger, Steffen, et al.. (2018). Killing Four Birds with Two Stones: Multi-Task Learning for Non-Literal Language Detection. TUbilio (Technical University of Darmstadt). 1558–1569.7 indexed citations
16.
Eger, Steffen, et al.. (2018). One Size Fits All? A simple LSTM for non-literal token and construction-level classification.. TUbilio (Technical University of Darmstadt). 70–80.1 indexed citations
17.
Eger, Steffen, et al.. (2016). Lemmatization and Morphological Tagging in German and Latin: A Comparison and a Survey of the State-of-the-art.. Language Resources and Evaluation. 1507–1513.8 indexed citations
Eger, Steffen. (2012). Lexical semantic typologies from bilingual corpora — A framework. Joint Conference on Lexical and Computational Semantics. 90–94.1 indexed citations
20.
Eger, Steffen. (2012). S-Restricted Monotone Alignments: Algorithm, Search Space, and Applications. International Conference on Computational Linguistics. 781–798.5 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.