arXiv (All)
open access
Greedy Multi-Path Block Verification for Faster Decoding in Speculative Sampling
The goal of $L$-step speculative decoding is to accelerate autoregressive decoding of a target model by using a cheaper draft model to generate a candidate path of $L$ tokens. Based on a verification algorithm involving target and draft model probabilities, a prefix of the candidate sequence is acce
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- BitNest: Bit-Nested Speculative Decoding for Memory-Efficient LLM Inference Acceleration#1187114
- AdaFlash: Adaptive Speculative Decoding via On-Policy Distilled Diffusion Drafters#1257979
- D-Loop: Looped Diffusion Drafting for Speculative Decoding#1202430
- TreeSpark: Calibrated, Load-Adaptive Draft Trees for Semi-Autoregressive Speculative Decoding#1036782
- SPEED-Bench: A Unified and Diverse Benchmark for Speculative Decoding#615955
Record · ID 1199752
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive