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Subjectivity-Adaptive soft-Label Training (SALT) transforms LLM training by embracing the inherent variability in human responses, leading to more robust social simulations.
MoE dLLMs can outperform leading models with significantly fewer training tokens, challenging assumptions about data efficiency in large-scale language models.
