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cs.CL2025
MediEval: A Unified Medical Benchmark for Patient-Contextual and Knowledge-Grounded Reasoning in LLMs
Zhan Qu, Michael Färber
Large Language Models (LLMs) are increasingly applied to medicine, yet their adoption is limited by concerns over reliability and safety. Existing evaluations either test factual m…
cs.CL2025
Extractive Fact Decomposition for Interpretable Natural Language Inference in one Forward Pass
Nicholas Popovič, Michael Färber
Recent works in Natural Language Inference (NLI) and related tasks, such as automated fact-checking, employ atomic fact decomposition to enhance interpretability and robustness. Fo…