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cs.CL2026
Tracing Relational Knowledge Recall in Large Language Models
Nicholas Popovič, Michael Färber
We study how large language models recall relational knowledge during text generation, with a focus on identifying latent representations suitable for relation classification via l…
cs.CL2026
Semantic Calibration Prevails Where Token Confidence Fails: Benchmarking Long-Form Scientific QA
Philip Müller, Nicholas Popovič, Michael Färber +1
Reliable uncertainty quantification (UQ) is essential for safe deployment of large language models (LLMs) in scientific question answering, where long-form outputs exceed practical…