Christoph Alt

Postdoctoral researcher
mail: christoph.alt@informatik.hu–berlin.de

Christoph Alt is a postdoctoral researcher at Humboldt University of Berlin and part of the Cluster Science of Intelligence. He received his Bachelor’s degree in Electrical Engineering from the University of Applied Sciences Munich and his Master’s degree in Computer Engineering from the Technical University of Berlin. For his doctoral degree in Computer Science at Technical University of Berlin and the German Research Center for AI (DFKI), he studied the generalizability and data efficiency of neural-network-based natural language processing (NLP) approaches, in particular, how to learn from limited amounts of labeled data and transfer linguistic knowledge between related NLP tasks.

At SCIoI, Christoph works at Project A002, Project 44, Project 45.

SCIoI Publications:

Weber, L., Sänger, M., Garda, S., Barth, F., Alt, C., & Leser, U. (2021). Humboldt@ DrugProt: Chemical-Protein Relation Extraction with Pretrained Transformers and Entity Descriptions. Proceedings of the BioCreative VII challenge evaluation workshop. https://biocreative.bioinformatics.udel.edu/media/store/files/2021/Track1_pos_2_BC7_submission_172.pdf
Harbecke, D., Chen, Y., Hennig, L., & Alt, C. (2022). Why only Micro-F1? Class Weighting of Measures for Relation Classification. Proceedings of the 1st Workshop on Efficient Benchmarking in NLP. https://doi.org/10.18653/v1/2022.nlppower-1.4
Chen, Y., Mikkelsen, J., Binder, A., Alt, C., & Hennig, L. (2022). A Comparative Study of Pre-trained Encoders for Low-Resource Named Entity Recognition. Proceedings of the 7th Workshop on Representation Learning for NLP. https://doi.org/10.18653/v1/2022.repl4nlp-1.6
Gefördert durch die Deutsche Forschungsgemeinschaft (DFG) im Rahmen der Exzellenzstrategie des Bundes und der Länder – EXC-2002/1 – Projektnummer 390523135 .
Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany ́s Excellence Strategy – EXC-2002/1 – Projectnumber 390523135.

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