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näkemys - Controllable Preference Optimization
Controllable Preference Optimization: Achieving Multi-Objective Alignment
The author argues for the importance of grounding large language models (LLMs) with evident preferences to achieve controllable preference optimization (CPO). By explicitly specifying preference scores for different objectives, CPO guides the model to generate responses that align with various preferences.
Controllable Preference Optimization: Achieving Multi-Objective Alignment
Grounding LLMs with evident preferences through controllable preference optimization can achieve multi-objective alignment.
Controllable Preference Optimization: Achieving Multi-Objective Alignment
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