Julian Hitschler
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 10%
- Information Systems
- Molecular Biology
- Signal Processing
- Co-authors
- Stefan RiezlerAntonio Valerio Miceli BaroneMarcin Junczys-DowmuntMaria NădejdeBarry HaddowSamuel LäubliKyunghyun ChoRico Sennrich
- Topics
- Natural Language Processing Techniques (6 papers)Topic Modeling (5 papers)Multimodal Machine Learning Applications (2 papers)
- Journals
- SHILAP Revista de lepidopterologíaLanguage Resources and EvaluationEdinburgh Research Explorer (University of Edinburgh)
- Partner nations
- GermanyUnited StatesSwitzerland
In The Last Decade
Julian Hitschler
7 papers receiving 232 citations
Peers
Comparison fields: 5 of 16
- Artificial Intelligence 239
- Computer Vision and Pattern Recognition 108
- Information Systems 21
- Molecular Biology 9
- Signal Processing 7
Countries citing papers authored by Julian Hitschler
This map shows the geographic impact of Julian Hitschler'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 Julian Hitschler with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Julian Hitschler more than expected).
Fields of papers citing papers by Julian Hitschler
This network shows the impact of papers produced by Julian Hitschler. 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 Julian Hitschler. The network helps show where Julian Hitschler may publish in the future.
Co-authorship network of co-authors of Julian Hitschler
This figure shows the co-authorship network connecting the top 25 collaborators of Julian Hitschler. A scholar is included among the top collaborators of Julian Hitschler 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 Julian Hitschler. Julian Hitschler is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Correction of OCR Word Segmentation Errors in Articles from the ACL Collection through Neural Machine Translation Methods | 3 |
| 2 | A Dataset and Reranking Method for Multimodal MT of User-Generated Image Captions | 4 |
| 3 | 28 | |
| 4 | 167 | |
| 5 | 49 | |
| 6 | 3 | |
| 7 | The Heidelberg University English-German translation system for IWSLT 2015 | 2 |
About Julian Hitschler
Julian Hitschler is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Language and Linguistics, having authored 7 papers that have together received 256 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (6 papers), Topic Modeling (5 papers) and Multimodal Machine Learning Applications (2 papers). The work is most often cited by research in Artificial Intelligence (239 citations), Computer Vision and Pattern Recognition (108 citations) and Information Systems (21 citations). Julian Hitschler has collaborated with scholars based in Germany, United States and Switzerland. Frequent co-authors include Stefan Riezler, Antonio Valerio Miceli Barone, Marcin Junczys-Dowmunt, Maria Nădejde, Barry Haddow, Samuel Läubli, Kyunghyun Cho, Rico Sennrich, Orhan Fırat and Alexandra Birch. Their work appears in journals such as SHILAP Revista de lepidopterología, Language Resources and Evaluation and Edinburgh Research Explorer (University of Edinburgh).
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.