2026
Dynamic Thinking-Token Selection for Efficient Reasoning in Large Reasoning Models
ICML 2026poster
Large Reasoning Models (LRMs) excel at solving complex problems by explicitly generating a reasoning trace before deriving the final answer. However, these extended generations incur substantial memory footprint and computational overhead, bottlenecking LRMs' efficiency. This work uses attention map…