This repository compiles academic papers, technical reports, and tutorials addressing key challenges in LLM dependability. It covers uncertainty estimation, calibration, hallucination mitigation, mechanistic interpretability, reasoning, prompt optimization, instruction tuning, and fine-tuning strategies. The list serves researchers and practitioners working to improve LLM robustness and reliability.