3 papers
cs.CL2026
Reasoning Gets Harder for LLMs Inside A Dialogue
Ivan Kartáč, Mateusz Lango, Ondřej Dušek
Large Language Models (LLMs) achieve strong performance on many reasoning benchmarks, yet these evaluations typically focus on isolated tasks that differ from real-world usage in t…
cs.CL2025
LLMs as Span Annotators: A Comparative Study of LLMs and Humans
Zdeněk Kasner, Vilém Zouhar, Patrícia Schmidtová +7
Span annotation - annotating specific text features at the span level - can be used to evaluate texts where single-score metrics fail to provide actionable feedback. Until recently…
cs.CL2025
OpeNLGauge: An Explainable Metric for NLG Evaluation with Open-Weights LLMs
Ivan Kartáč, Mateusz Lango, Ondřej Dušek
Large Language Models (LLMs) have demonstrated great potential as evaluators of NLG systems, allowing for high-quality, reference-free, and multi-aspect assessments. However, exist…