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Barbara Plank

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#machine learning Preprint Sep 2026

Don't Forget! Decomposing the Training Dynamics of Memorization in Language Models

Memorization has been proposed as a mechanism to explain how language models fit the tail of their training distributions, but its training dynamics are not understood well. In this work, we take a fine-grained look at memorization by decomposing the loss trajectory of memorized sequences over training and model parame...

Florian Eichin, Philipp Mondorf, Andrei Mircea et al. · 0 citations
Preprint Aug 2026

When Do Explanations Help In-Context Learning? A Comparative Study of Natural Language Explanation Types and Faithfulness

Natural language explanations (NLEs) are increasingly used as inputs, for example, as few-shot rationales that influence model behavior in in-context learning (ICL). However, it remains unclear how different types of NLEs compare in their effects on downstream model performance in explanation-augmented prompting. There...

Mahdi Dhaini, Adam Dejl, Juraj Vladika et al. · 0 citations
Preprint Jul 2026

AIMO Interpretability Challenge

We propose the AIMO Interpretability Challenge, a competition on distinguishing robust from spurious reasoning in frontier mathematical language models based on the models'internal mechanisms. The challenge is motivated by a central limitation of standard reasoning benchmarks: strong final-answer accuracy does not reve...

Michal vStef'anik, Philipp Mondorf, Andreas Waldis et al. · 0 citations
Preprint Aug 2026

BavGround: A Benchmark for Regional Cultural Grounding and Dialect Competence in Bavarian

Cultural evaluation of large language models (LLMs) often focuses on high-resource standard languages, leaving regional culture and dialect communities underrepresented. We introduce BavGround, a benchmark for evaluating Bavarian regional cultural grounding and dialect competence across English, German and Bavarian. Ba...

Jophin John, Michael Hoffmann, Jan Fillies et al. · 0 citations

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