English(EN) Accelerating Constrained Decoding with Token Space Compression

新技术压缩令牌空间以加速 LLM 约束解码

作者 PulseAugur 编辑部 · [1 个来源] · 2026-05-29 04:00

研究人员开发了 CFGzip，这是一种新颖的离线技术，旨在显著加速大型语言模型 (LLM) 中的约束解码。该方法压缩了令牌搜索空间，大大降低了确保 LLM 输出符合指定无上下文语法 (CFG) 的相关开销。实验表明，CFGzip 可将延迟降低多达两个数量级，使总约束生成时间提高 7.5 倍，从而使复杂的 CFG 解码能够大规模实现。 AI

排序理由该集群包含一篇学术论文，详细介绍了加速 LLM 约束解码的新方法。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.AI TIER_1 English(EN) · Michael Sullivan, Alexander Koller · 2026-05-29 04:00

加速带约束的解码与令牌空间压缩

arXiv:2605.29986v1 Announce Type: new Abstract: To guarantee that an LLM's outputs conform to a specified structure, context-free grammar (CFG) decoding engines force the selection of next tokens that produce strings that conform to a given CFG. While current CFG-constrained deco…

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加速带约束的解码与令牌空间压缩

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