arXiv AI
Early-Bird Decoding: Accelerating Diffusion LLMs with Learnable Block Sizes and Parallel Sampling
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CAI-DLLM: Convergence Aware Inference for Diffusion Language Models
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Polestar: Drift-Aware Cache Calibration and Token Commitment for Efficient Inference of Diffusion LLMs
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BlockBatch: Multi-Scale Consensus Decoding for Efficient Diffusion Language Model Inference
arXiv:2605. 29233v2 Announce Type: replace-cross Abstract: Diffusion language models (dLLMs) generate text by iteratively denoising multiple token positions in parallel, offering an attractive alternative to strictly autoregressive decoding.
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Fast-dLLM++: Fr\'{e}chet Profile Decoding for Faster Diffusion LLM Inference
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$R^2$-dLLM: Accelerating Diffusion Large Language Models via Spatio-Temporal Redundancy Reduction
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