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Sebastian Moller

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#machine learning Preprint May 2026

Judge Circuits Explain Format-Induced Inconsistency in LLM-as-a-Judge

By structurally decoupling abstract judging from output formatting, this work provides a mechanistic account of format-induced inconsistency on the open-weight models the authors study and implies that benchmark comparisons of judge reliability across formats partly measure the fragile formatting stage, and can underst...

Nils Feldhus, Tanja Baeumel, Elena Golimblevskaia et al. · 1 citation
#natural language process... Preprint Jun 2026

Does Finetuning with Scientific Data Increase Hallucinations? A Multi-domain Factuality Evaluation of LLMs

SciFactCheck, a benchmark of 2,500 prompts across five scientific domains, is paired with a modular evaluation framework targeting three factuality hallucination types: unverifiability, overclaim, and attribution, and fundamentally challenge current methods of domain-specific fine-tuning for factuality and call for dev...

Raia Abu Ahmad, Nikolas Rauscher, Ekaterina Borisova et al. · 0 citations

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