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This paper introduces distributed speculative inference (DSI), a novel inference algorithm that is provably faster than speculative inference (SI) [leviathan2023, chen2023, miao2024, sun2025, timor2025] and standard autoregressive inference (non-SI).
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Language models as agent models
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Accelerating large language model decoding with speculative sampling
Mamba: Linear-time sequence modeling with selective state spaces
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MiniLLM: Knowledge distillation of large language models
Yuxian Gu, Li Dong, Furu Wei, and Minlie Huang · 2024
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EAGLE: Speculative sampling requires rethinking feature uncertainty
Yuhui Li, Fangyun Wei, Chao Zhang, and Hongyang Zhang · 2024
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Awq: Activation-aware weight quantization for llm compression and acceleration
Ji Lin, Jiaming Tang, Haotian Tang, Shang Yang, Wei-Ming Chen, Wei-Chen Wang, Guangxuan Xiao, Xingyu Dang, Chuang Gan, and Song Han · 2024
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Dynamic speculation lookahead accelerates speculative decoding of large language models
Jonathan Mamou, Oren Pereg, Daniel Korat, Moshe Berchansky, Nadav Timor, Moshe Wasserblat, and Roy Schwartz · 2024
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Specinfer: Accelerating large language model serving with tree-based speculative inference and verification
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Fast inference from transformers via speculative decoding
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LLM-pruner: On the structural pruning of large language models
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Efficient streaming language models with attention sinks
Guangxuan Xiao, Yuandong Tian, Beidi Chen, Song Han, and Mike Lewis · 2024
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Context parallelism for scalable million-token inference
Amy Yang, Jingyi Yang, Aya Ibrahim, Xinfeng Xie, Bangsheng Tang, Grigory Sizov, Jeremy Reizenstein, Jongsoo Park, and Jianyu Huang · 2024
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Exploring post-training quantization in llms from comprehensive study to low rank compensation
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Fastdraft: How to train your draft
Ofir Zafrir, Igor Margulis, Dorin Shteyman, and Guy Boudoukh · 2024
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Distillspec: Improving speculative decoding via knowledge distillation
Yongchao Zhou, Kaifeng Lyu, Ankit Singh Rawat, Aditya Krishna Menon, Afshin Rostamizadeh, Sanjiv Kumar, Jean-François Kagy, and Rishabh Agarwal · 2024
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Judge decoding: Faster speculative sampling requires going beyond model alignment
Gregor Bachmann, Sotiris Anagnostidis, Albert Pumarola, Markos Georgopoulos, Artsiom Sanakoyeu, Yuming Du, Edgar Schönfeld, Ali Thabet, and Jonas K Kohler · 2025
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PEARL: Parallel speculative decoding with adaptive draft length
Tianyu Liu, Yun Li, Qitan Lv, Kai Liu, Jianchen Zhu, Winston Hu, and Xiao Sun · 2025
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Niklas Muennighoff, Zitong Yang, Weijia Shi, Xiang Lisa Li, Li Fei-Fei, Hannaneh Hajishirzi, Luke Zettlemoyer, Percy Liang, Emmanuel Candès, and Tatsunori Hashimoto · 2025
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Faster cascades via speculative decoding
Harikrishna Narasimhan, Wittawat Jitkrittum, Ankit Singh Rawat, Seungyeon Kim, Neha Gupta, Aditya Krishna Menon, and Sanjiv Kumar · 2025
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Magicdec: Breaking the latency-throughput tradeoff for long context generation with speculative decoding
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Block verification accelerates speculative decoding
Ziteng Sun, Uri Mendlovic, Yaniv Leviathan, Asaf Aharoni, Ahmad Beirami, Jae Hun Ro, and Ananda Theertha Suresh · 2025
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Nadav Timor, Jonathan Mamou, Daniel Korat, Moshe Berchansky, Oren Pereg, Gaurav Jain, Roy Schwartz, Moshe Wasserblat, and David Harel · 2025
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