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Data imbalance in MoE models is overcome by biasing expert selection, unlocking capacity for underrepresented categories without sacrificing cross-category sharing.
LLM agents are far more susceptible to multi-turn misuse than previously thought, with a new framework showing they complete illicit tasks at substantially higher rates compared to single-turn attacks.
