This repository hosts the official code and data artifact for the paper "Monitor-Guided Decoding of Code LMs with Static Analysis of Repository Context" appearing at NeurIPS 2023 ("Guiding Language ...

Meta’s AI chief says new Muse Spark update will sharpen coding, agentic AI Alexandr Wang said the upcoming Muse Spark update will significantly improve coding and agentic capabilities, while analysts ...

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扩散语言模型展现出较高的发展潜力，但在代码等形式语言生成任务中，仍难以稳定满足语法约束。针对这一问题，本文提出了针对扩散语言模型约束解码方法 —— LAVE，通过对扩散语言模型的中间输出进行前瞻补全与语法验证，为模型生成过程提供了可靠的语法保障。实验表明，LAVE 能够显著提升多种扩散语言模型生成形式化语言（例如源代码、JSON、化学表达式）的语法正确率，同时改善功能正确率，并保持较低的推理开销。