arXiv Machine Learning June 16, 2026 By Yihe Deng, Yu Yang, Junkai Zhang, Wei Wang, Bo Li

Enhancing LLM Safety Through a Theoretical Minimax Game Lens

Read the original on arXiv Machine Learning →

arXiv:2502. 05163v2 Announce Type: replace-cross Abstract: The rapid advancement of large language models (LLMs) necessitates effective mechanisms to ensure their responsible deployment by accurately distinguishing unsafe content from benign content.

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Jun 16

CHILLGuard: Towards Fine-Grained Chinese LLM Safety Guardrail with Scalable Data Construction and Model-aware Preference Alignment

arXiv:2606. 15396v1 Announce Type: cross Abstract: Malicious content generated from large language models (LLMs) could pose severe safety risks and ethical concerns.

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Safety Alignment of LMs via Non-cooperative Games

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Safety Game: Inference-Time Alignment of Black-Box LLMs via Constrained Optimization

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When the API Speaks the Wrong Language: Revisiting Post-Training for Multilingual Tool Use

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CHILLGuard: Towards Fine-Grained Chinese LLM Safety Guardrail with Scalable Data Construction and Model-aware Preference Alignment

Safety Alignment of LMs via Non-cooperative Games

Safety Game: Inference-Time Alignment of Black-Box LLMs via Constrained Optimization

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