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.
arXiv preprint arXiv:2406.18872 , year=
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LLM agent pairs in a resource allocation negotiation game fail to reach Pareto-optimal outcomes due to dynamic grounding failures such as loss of interaction history, anchoring, and referential errors.
DPA-GRPO trains a generator-verifier pair via group-relative policy optimization on paired counterfactual actions, improving structured output accuracy on TaxCalcBench over zero-shot and generator-only baselines.
citing papers explorer
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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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Talk is Cheap, Communication is Hard: Dynamic Grounding Failures and Repair in Multi-Agent Negotiation
LLM agent pairs in a resource allocation negotiation game fail to reach Pareto-optimal outcomes due to dynamic grounding failures such as loss of interaction history, anchoring, and referential errors.
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Interactive Critique-Revision Training for Reliable Structured LLM Generation
DPA-GRPO trains a generator-verifier pair via group-relative policy optimization on paired counterfactual actions, improving structured output accuracy on TaxCalcBench over zero-shot and generator-only baselines.