Aligned Data Can Induce Misalignment via Context Confusion
Large language models (LLMs) are frequently updated for various use cases, where filtering out misaligned training samples is a common practice for preventing post-update misalignment. However, alignment is inherently context-dependent: a recommendation that is aligned in one…
- 01.Large language models (LLMs) are frequently updated for various use cases, where filtering out misaligned training samples is a common practice for preventing post-update misalignment
- 02.However, alignment is inherently context-dependent: a recommendation that is aligned in one…
This material is provided as an extended analytical summary.
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