Survey on Language Models for Code
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A comprehensive survey of LLMs for code covering 50+ models, 30+ evaluation tasks, and 500 related works.
Model landscape: Catalogs 50+ code LLMs across sizes, architectures, and training regimes, providing a single reference for what's available.
Task taxonomy: Reviews 30+ evaluation tasks spanning code generation, repair, translation, summarization, and execution prediction.
Training and data recipes: Walks through pretraining corpus construction, instruction tuning, and RLHF specifically for code.
Open problems: Highlights challenges in long-context code understanding, multi-file reasoning, and robust evaluation beyond HumanEval-style metrics.
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