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2min chapter
#199 - OpenAI's 03-mini, Gemini Thinking, Deep Research, s1
Last Week in AI
Theoretical Framework for Safe Alignment of LLMs
This chapter explores the theoretical framework for safe alignment of large language models during inference, emphasizing a proposed method involving a critic in a constrained decision process. The discussion highlights the challenges in defining effective safety metrics to ensure robust protection against exploitation.
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