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arXiv cs.CL
arXiv cs.CL
6/23/2026
Post-Training Recipe, More Than Model Family, Shapes Multi-Agent LLM Conversational Behavior

Post-Training Recipe, More Than Model Family, Shapes Multi-Agent LLM Conversational Behavior

Short summary

Research shows post-training recipe, not model family alone, is the primary factor shaping LLM behavior in multi-agent systems. A reasoning-distilled Llama model shifted 18% in hedging behavior based on which partner it interacted with—larger than cross-family variation. Teams building multi-LLM systems should prioritize post-training diversity for behavioral diversity.

  • •Post-training recipe shapes conversational behavior more than model family in multi-agent systems
  • •Same-base Llama checkpoints showed 18% hedging shift depending on partner, exceeding cross-family variation
  • •Post-training should be a primary axis for multi-LLM panel composition, not just model family selection

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Read full article at arXiv cs.CL

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