2025
Improving Preference Alignment of LLM with Inference-Free Self-Refinement
EMNLP 2025
Large language models (LLMs) develop the in-context learning capability through pretraining and instruction tuning, enabling task adaptation without parameter updates. Self-refinement is a manifestation of this capability, which allows LLMs to iteratively refine the output using self-generated feedb