arXiv Computation and Language August 25, 2026 By Philipp Steigerwald, Eric Rudolph, Jens Albrecht

N\"urnberg NLP @ GermEval Shared Task 2026: Harmful Content Detection in German Social Media through Error-Independent LLM Voters

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The paper reports on the N"urnberg NLP team’s system for the GermEval 2026 shared task on harmful content detection in German social media. The authors tackle severe class imbalance by building a nine‑voter ensemble that varies along three orthogonal axes—LLM choice, training method, and class scope—to achieve error independence. Their system attains macro‑F1 scores of 89.56 (C2A), 71.63 (DBO), 54.84 (VIO), and 83.02 (DEF) on the hidden test set, winning all four subtasks.

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