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References (14)

[1]
VOCABTRIM: Vocabulary Pruning for Efficient Speculative Decoding in LLMs
2025Raghavv Goel, Sudhanshu Agrawal et al.
[2]
Training Domain Draft Models for Speculative Decoding: Best Practices and Insights
2025Fenglu Hong, Ravi Raju et al.
[3]
EAGLE-3: Scaling up Inference Acceleration of Large Language Models via Training-Time Test
2025Yuhui Li, Fangyun Wei et al.
[4]
The Perfect Blend: Redefining RLHF with Mixture of Judges
2024Tengyu Xu, Eryk Helenowski et al.
[5]
EAGLE-2: Faster Inference of Language Models with Dynamic Draft Trees
2024Yuhui Li, Fangyun Wei et al.
[6]
Advancing LLM Reasoning Generalists with Preference Trees
2024Lifan Yuan, Ganqu Cui et al.
[7]
Unlocking Efficiency in Large Language Model Inference: A Comprehensive Survey of Speculative Decoding
2024Heming Xia, Zhe Yang et al.
[8]
WizardCoder: Empowering Code Large Language Models with Evol-Instruct
2023Ziyang Luo, Can Xu et al.
[9]
Judging LLM-as-a-judge with MT-Bench and Chatbot Arena
2023Lianmin Zheng, Wei-Lin Chiang et al.
[10]
Let's Verify Step by Step
2023H. Lightman, Vineet Kosaraju et al.
[11]
Tree-structured Parzen estimator: Understanding its algorithm components and their roles for better empirical performance
2023Shuhei Watanabe
[12]
Fast Inference from Transformers via Speculative Decoding
2022Yaniv Leviathan, Matan Kalman et al.
[13]
Evaluating Large Language Models Trained on Code
2021Mark Chen, Jerry Tworek et al.
[14]
Optuna: A Next-generation Hyperparameter Optimization Framework
2019Takuya Akiba, Shotaro Sano et al.

Founder's Pitch

"Optimize language model draft latency with vocabulary trimming to enhance speculative decoding efficiency."

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