Anchored Bipolicy Self-Play trains role-specific LoRA adapters on a frozen base model to break self-consistency collapse in self-play red-teaming, yielding up to 100x parameter efficiency and stronger safety on Qwen2.5 models.
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Presents a game-theoretic model with group actions for data augmentation in LLM adversarial evaluation, demonstrating local generalization from fine-tuning on three model families and redefining benchmarks as orbits under group actions.
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The Attacker in the Mirror: Breaking Self-Consistency in Safety via Anchored Bipolicy Self-Play
Anchored Bipolicy Self-Play trains role-specific LoRA adapters on a frozen base model to break self-consistency collapse in self-play red-teaming, yielding up to 100x parameter efficiency and stronger safety on Qwen2.5 models.
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The Evaluation Game: Beyond Static LLM Benchmarking
Presents a game-theoretic model with group actions for data augmentation in LLM adversarial evaluation, demonstrating local generalization from fine-tuning on three model families and redefining benchmarks as orbits under group actions.