Papers by Andreas Hotho
SuperGLEBer: German Language Understanding Evaluation Benchmark (2024.naacl-long)
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| Challenge: | a new set of German-pretrained models are being released, but no established, diverse and systematic evaluation suite is available for them. |
| Approach: | They assemble a Natural Language Understanding benchmark suite for the German language and evaluate 10 existing German-pretrained models. |
| Outcome: | The proposed benchmark suite evaluates 10 German-pretrained models on 29 tasks . the results show that encoder models are good choices for most tasks, but not all . |
Assessing the State of the Art in Scene Segmentation (2025.naacl-long)
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| Challenge: | Recent advances in scene segmentation have made it difficult to detect scenes in literary texts. |
| Approach: | They propose to modify existing models to improve detection of scenes in literary texts . they propose to use a training sample generation scheme to alleviate this problem . |
| Outcome: | The proposed model is more robust to different types of texts, while its overall performance is slightly worse than that of BERT-based models. |
LLäMmlein: Transparent, Compact and Competitive German-Only Language Models from Scratch (2025.acl-long)
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| Challenge: | Large Language Models (LLMs) have achieved remarkable success, yet this progress is predominantly centered on English. |
| Approach: | They create two German-only decoder models from scratch and publish them for the (German) NLP research community to use. |
| Outcome: | The two models performed competitively on the German SuperGLEBer benchmark, but performance improvements plateaued early during training, offering valuable insights into resource allocation for future models. |
Where to Submit? Helping Researchers to Choose the Right Venue (2020.findings-emnlp)
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| Challenge: | Whenever researchers write a paper, the same question occurs: "Where to submit?" In this paper, we introduce "Where To Submit" (WTS) that recommends conferences and journals based on title, abstract, and keywords of a given paper. |
| Approach: | They propose an open and interpretable NLP system that recommends conferences and journals to researchers based on the title, abstract, and/or keywords of a given paper. |
| Outcome: | The proposed system achieves an Accuracy@5 of approximately 83% for AI papers and 95% in medicine. |
Detecting Scenes in Fiction: A new Segmentation Task (2021.eacl-main)
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Albin Zehe, Leonard Konle, Lea Katharina Dümpelmann, Evelyn Gius, Andreas Hotho, Fotis Jannidis, Lucas Kaufmann, Markus Krug, Frank Puppe, Nils Reiter, Annekea Schreiber, Nathalie Wiedmer
| Challenge: | Text segmentation is a long standing issue in the area of natural language processing . even modern methods struggle with processing text longer than a couple of sentences or paragraphs . |
| Approach: | They introduce the task of scene segmentation on narrative texts and provide an annotated corpus . they discuss linguistic and narrative properties of the task and provide baseline experiments . |
| Outcome: | The proposed task is very challenging and the results are impressive. |