speculators/examples/train/dspark_qwen3_0_6b_sharegpt_online.sh at main · vllm-project/speculators

DeepSpec/DSpark_paper.pdf at main · deepseek-ai/DeepSpec

DSpark: A Speculative Decoding Framework Using Semi-Autoregressive Generation and Confidence-Scheduled Verification for LLM Inference Acceleration

DSpark is a speculative decoding framework for Large Language Models (LLMs) that improves inference efficiency by combining semi-autoregress

Speculative Speculative Decoding: Parallelizing LLM Inference for Faster Performance

Researchers introduce speculative speculative decoding (SSD), a novel technique to accelerate large language model inference by parallelizin

ATLAS: Adaptive Learning System for Faster LLM Inference Without Manual Tuning

Together AI introduces ATLAS (AdapTive-LeArning Speculator System), a novel runtime-learning accelerator for LLM inference that automaticall

LK Losses: A New Training Objective to Optimize Acceptance Rate in Speculative Decoding for LLMs

This paper introduces LK losses, a novel training objective for speculative decoding in large language models (LLMs). Speculative decoding a

AnyBlox: A Framework for Self-Decoding Datasets [pdf]