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School of Electronic and Computer Engineering, Peking University
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Transition supervision can dramatically boost LLM agent performance, outperforming standard policy optimization by leveraging environmental feedback.
Kimi K3's innovative architecture achieves a 2.5x scaling efficiency improvement, enabling robust performance across diverse long-horizon tasks.
A unified evaluation framework that simplifies the assessment of LLM-based agents could drastically enhance reproducibility and accelerate research breakthroughs.
