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cs.CL2026
Benchmarking Uncertainty Calibration in Large Language Model Long-Form Question Answering
Philip Müller, Nicholas Popovič, Michael Färber +1
Large Language Models (LLMs) are commonly used in Question Answering (QA) settings, increasingly in the natural sciences if not science at large. Reliable Uncertainty Quantificatio…
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…