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Jian Lan · Zhicheng Liu · Udo Schlegel · Raoyuan Zhao · Yihong Liu · Hinrich Schuetze · Michael Hedderich · Thomas Seidl
Qianli Wang · Van Bach Nguyen · Yihong Liu · Fedor Splitt · Nils Feldhus · Christin Seifert · Hinrich Schuetze · Sebastian Möller · Vera Schmitt
Counterfactuals refer to minimally edited inputs that cause a model’s prediction to change, serving as a promising approach to explaining the model’s behavior. Large language models (LLMs) excel at generating English counterfactuals and demonstrate multilingual proficiency. However, their effecti...
Raoyuan Zhao · Yihong Liu · Lena Altinger · Hinrich Schuetze · Michael A. Hedderich
Large language models (LLMs) are increasingly deployed in multilingual, real-world applications with user inputs – naturally introducing typographical errors (typos). Yet most benchmarks assume clean input, leaving the robustness of LLMs to typos across languages largely underexplored. To address...
Yihong Liu · Raoyuan Zhao · Hinrich Schuetze · Michael A. Hedderich
Large reasoning models (LRMs) achieve strong performance on mathematical reasoning tasks, often attributed to their capability to generate explicit chain-of-thought (CoT) explanations. However, recent work shows that LRMs often arrive at the correct answer before completing these textual reasonin...