This repository hosts an arXiv survey paper on LLM alignment, collating research on data collection, training methodologies (RLHF, supervised fine-tuning), and model evaluation. It functions as an awesome-list style resource for researchers and practitioners to understand alignment techniques for making LLMs follow human instructions, reduce bias, and minimize hallucinations.