Jan Philip Wahle

Doctoral Researcher

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Jan Philip Wahle in the Göttingen offices doing paraphrase plagiarism and natural language processing research

RESEARCH INTERESTS

Jan Philip’s current research interests lie in the development of natural language processing systems for paraphrase plagiarism detection based on deep learning models.

His prime interests lie in the areas of

  • Deep learning
  • Natural language processing
  • Paraphrase plagiarism detection
  • Paraphrase generation

PARAPHRASE PROJECTS

I am open to student projects in the areas of natural language processing and paraphrasing, especially applied to plagiarism detection. The slides here are projects on which I work. Don’t hesitate to get in touch with me if you are interested and let’s talk!

SHORT CV

10/2022 – present

Ph.D. Student
Chair for Scientific Information Analytics, University of Göttingen

09/2021 – 10/2022

Ph.D. Student
Chair for Data & Knowledge Engineering, University of Wuppertal

07/2020 – 10/2021

Deep Learning Research Engineer
Chair for Data & Knowledge Engineering, University of Wuppertal

10/2019 – 07/2020

Student Researcher
Chair for Data & Knowledge Engineering, University of Wuppertal

10/2018 – 10/2020

Computer Science (Data Analytics), M. Sc.
Chair for Data & Knowledge Engineering, University of Wuppertal

03/2018 – 10/2018

Student Researcher
Parallel Hardware and Software Systems, University of Wuppertal

03/2017 – 10/2018

Junior Software Engineer/Student Trainee
Aptiv PLC Wuppertal, Germany

10/2015 – 10/2018

Information Technology (Information Science), B. Sc.
University of Wuppertal

SELECTED PUBLICATIONS

A complete list of my publications is available here


We are Who We Cite: Bridges of Influence Between Natural Language Processing and Other Academic Fields
J. P. Wahle, T. Ruas, M. Abdalla, B. Gipp, S. M. Mohammad
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP)
(PDF DOI BibTeX)


Paraphrase Types for Generation and Detection
J. P. Wahle, T. Ruas, B. Gipp
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP)
(PDF DOI BibTeX)


How Large Language Models are Transforming Machine-Paraphrase Plagiarism

J. P. Wahle, T. Ruas, F. Kirstein, B. Gipp
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP)
(PDF DOI BibTeX)


Identifying Machine-Paraphrased Plagiarism

J. P. Wahle, T. Ruas, T. Foltynek, N. Meuschke, B. Gipp
Information for a Better World: Shaping the Global Future – 17th International Conference, iConference 2022.
(PDF  DOI  BibTeX)


Are Neural Language Models Good Plagiarists? A Benchmark for Neural Paraphrase Detection

J. P. Wahle, T. Ruas, N. Meuschke, B. Gipp
ACM/IEEE Joint Conference on Digital Libraries, JCDL 2021, Champaign, IL, USA, September 27-30, 2021
(PDF  DOI  BibTeX)


D3: A Massive Dataset of Scholarly Metadata for Analyzing the State of Computer Science Research

J. P. Wahle, T. Ruas, Saif M. Mohammad. Meuschke, B. Gipp
Proceedings of The 13th Language Resources and Evaluation Conference, LREC 2022, Marseille, France, June 20-25, 2022
(PDF  DOI  BibTeX)