A Zeroth-Order Paradigm for LLM Preference Alignment
ComPO is a zeroth-order preference alignment method using comparison oracles to mitigate likelihood displacement across Mistral, Llama, Gemma, and Qwen3 models.
The paper proposes Comparison-based Preference Optimization (ComPO), a zeroth-order alignment method that extracts directional information from preference pairs with small likelihood margins without directly optimizing a differentiable preference loss. The authors prove convergence guarantees for the offline scheme and performance guarantees for a constrained online variant with reverse-KL control. Experiments on Mistral, Llama, Gemma-2, Qwen3, and Gemma-3 show improvements over existing direct alignment methods, including length-controlled win rates, with pair-level diagnostics consistent with mitigating likelihood displacement.