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cs.LG2026
Predicting Future Behaviors in Reasoning Models Enables Better Steering
Evgenii Kortukov, Piotr Komorowski, Florian Klein +5
Deployed large reasoning models (LRMs) often behave unexpectedly. Test-time steering controls LRM outputs by intervening on their hidden representations, but it can degrade output…
cs.LG2025
Attribution-Guided Decoding
Piotr Komorowski, Elena Golimblevskaia, Reduan Achtibat +3
The capacity of Large Language Models (LLMs) to follow complex instructions and generate factually accurate text is critical for their real-world application. However, standard dec…