Improving Recall and Precision in Unsupervised Multi-Label Document Classification Tasks by Combining Word Embeddings with TF-IDF. - Stefan Hirschmeier; Johannes Werner Melsbach; Detlef Schoder; Sven Stahlmann (ECIS, 2020)

Triplet transformer network for multi-label document classification. - Johannes Werner Melsbach; Sven Stahlmann; Stefan Hirschmeier; Detlef Schoder (DocEng, 2022)

Deep Learning Enabled Consumer Research for Product Development. - Sven Stahlmann; Oliver Ettrich; Detlef Schoder (ECIS, 2022)

Processing Patient Information Leaflets with Embeddings. - Sven Stahlmann; Stefan Hirschmeier; Detlef Schoder (HICSS, 2022)

What Do Customers Say About My Products? Benchmarking Machine Learning Models for Need Identification. - Sven Stahlmann; Oliver Ettrich; Marco Kurka; Detlef Schoder (HICSS, 2023)

Revealing Hidden Self-financed Wash Trading in Non-Fungible-Token Markets. - Henri Beyer; Patrick Seidel; Sven Stahlmann; Detlef Schoder (Wirtschaftsinformatik, 2023)

Automatically identifying customer needs in user-generated content using token classification. - Oliver Ettrich; Sven Stahlmann; Henrik Leopold; Christian Barrot (Decis. Support Syst., 2024)

Contrastive Transformer Network for Long Tail Classification. - Johannes Werner Melsbach; Frederic Haase; Sven Stahlmann; Stefan Hirschmeier; Detlef Schoder (Knowl. Based Syst., 2025)

Optimizing Small Language Models for In-Vehicle Function-Calling. - Yahya Sowti Khiabani; Farris Atif; Chieh Hsu; Sven Stahlmann; Tobias Michels; Sebastian Kramer; Benedikt Heidrich; M. Saquib Sarfraz; Julian Merten; Faezeh Tafazzoli (CoRR, 2025)