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cs.AI2026
Dynamic Routing as a New Dimension for Test-time Versatility of LLMs
Michal Štefánik, Marek Kadlčík, Josef Kuchař +1
Beyond scaling their parameters and data, large language models currently gain versatility on new problems along a single axis: the tokens they spend on chain-of-thought (CoT). We…
cs.AI2026
Prompt-Robust Language Models: Which Training Strategies Work?
Frederic Sadrieh, Michal Štefánik
Despite their strong performance, large language models remain highly sensitive to prompt formulation. Prior work addresses this through refined data construction or through dedica…