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cs.AI2026
Harnessing non-adversarial robustness in large language models
Qinghua Zhou, Ellina Aleshina, Andrey Lovyagin +6
The work presents an approach for addressing the challenge of robustness in Large Language Models (LLMs) to alterations and potential errors caused by semantically similar but text…
cs.CL2026
Evolutionary Search for Automated Design of Uncertainty Quantification Methods
Mikhail Seleznyov, Daniil Korbut, Viktor Moskvoretskii +3
Uncertainty quantification (UQ) methods for large language models are predominantly designed by hand based on domain knowledge and heuristics, limiting their scalability and genera…