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Efficiency: DPad-enhanced dLLMs achieve up to a 61.39× speedup over vanilla dLLM baselines. Accuracy: DPad-enhanced dLLMs achieve up to a +26.46% improvement over vanilla dLLM baselines. (Evaluation conducted on NVIDIA A100-PCIe-80GB GPUs).
Free Draft-and-Verification: Toward Lossless Parallel Decoding for Diffusion Large Language Models
DMax is a new dLLM paradigm achieving aggressive parallel decoding while preserving generation quality.
Code accompanying the paper "Layer Collapse in Diffusion Language Models" by Alexander Conzelmann, Albert Catalan-Tatjer, and Shiwei Liu (Tübingen AI Center / MPI for Intelligent Systems / ELLIS Institute Tübingen). Link: https://arxiv.org/abs/2605.06366
We would like to express our gratitude to the previous studies on DLLM KV caching that inspired our work. Special thanks to the authors of d2Cache for providing excellent open-source code, which served as a valuable foundation for our experimental framework. We also acknowledge the developers of…
The main features of mscheong01/entropycache are: Inference Optimization.
Projects with overlapping indexed features include: crys-chen/dpad — Efficiency: DPad-enhanced dLLMs achieve up to a 61.39× speedup over vanilla dLLM baselines. Accuracy: DPad-enhanced… cychomatica/freedave — Free Draft-and-Verification: Toward Lossless Parallel Decoding for Diffusion Large Language Models. czg1225/dmax — DMax is a new dLLM paradigm achieving aggressive parallel decoding while preserving generation quality. danielmisrael/apd — Official repository for the paper: Accelerating Diffusion LLMs via Adaptive Parallel Decoding. duterscmy/soar — . conzel/super-outlier-dlm — Code accompanying the paper "Layer Collapse in Diffusion Language Models" by Alexander Conzelmann, Albert…