LLM chain-of-thought crosses a commitment boundary early; subsequent steps are epiphenomenal, enabling early-exit that shortens traces 55% with negligible performance change.
Teaching M odern NLP and LLM s at Kyiv School of Economics: A Practice-Oriented Course with U krainian Language Focus
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ACTS models LLM reasoning control as an MDP solved by a controller agent initialized on synthetic multi-budget trajectories and refined with budget-conditioned RL, achieving token savings while matching full-reasoning accuracy.
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Beyond the Commitment Boundary: Probing Epiphenomenal Chain-of-Thought in Large Reasoning Models
LLM chain-of-thought crosses a commitment boundary early; subsequent steps are epiphenomenal, enabling early-exit that shortens traces 55% with negligible performance change.