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Chain-of-thought (CoT) improves reasoning but incurs substantial autoregressive rationale cost. Continuous CoT moves intermediate computation into recurrent hidden states, yet typically uses a fixed number of updates even though the best budget varies across questions and accuracy need not improve monotonically with $K...
An agent-centric view of data-efficient learning is developed, an agentic learning loop is formulated, data efficiency is defined as capability improvement without proportional increases in supervision or real-environment trial-and-error, and methods are synthesized into experience augmentation, agent structural design...
WSE-bench is introduced, a process benchmark that separately evaluates sustained generation, canonical coherence, and meaningful development in dynamic LLM storytelling, showing that sustained generation, canonical coherence, and meaningful development are distinct and sometimes competing capacities.
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