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cs.CL2026
Post-Training Recipe, More Than Model Family, Shapes Multi-Agent LLM Conversational Behavior
Luyang Zhang, Jialu Wang, Fei Xue +1
Multi-LLM systems use multiple language models to deliberate, judge each other's outputs, or coordinate as agents. Their value depends on the models producing measurably different…
cs.CL2026
SPOT: Span-level Pause-of-Thought for Efficient and Interpretable Latent Reasoning in Large Language Models
Yunlong Chu, Minglai Shao, Yuhang Liu +4
Explicit Chain-of-Thought improves the reasoning performance of large language models but often incurs high inference cost due to verbose token-level traces. While recent approache…