Awesome-Code-LLM
Awesome-Code-LLM is a comprehensive, curated repository supporting research on language models for code and software engineering. Initially published as a survey in Transactions on Machine Learning Research, it consolidates key literature, datasets, and tools in this rapidly evolving field. The collection covers foundational aspects such as pretraining strategies, adaptation of existing large language models, instruction fine-tuning, and reinforcement learning specifically for coding tasks. It also explores emerging intersections like code agents, reasoning capabilities, interactive coding, and the application of models to low-resource or domain-specific languages. The repository maintains an up-to-date catalog that includes recent breakthroughs from major conferences and industry teams, featuring technical reports on advanced code search benchmarks, multilingual embedding models, and frontier encoder-decoder architectures. Designed for researchers and practitioners, it serves as a central reference point for