Papers by Jan Pfister

2 papers
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 .
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.

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