Toward a Unified View of Preference Learning for Large Language Models: A Survey

The survey decomposes existing alignment strategies for preference learning in large language models into four components: model, data, feedback, and algorithm, and proposes a unified framework to establish connections between different methods. The authors also provide detailed worked examples of mainstream algorithms and, based on the unified perspective, discuss the challenges and future research directions for aligning large language models with human preferences.