Adaptive multi-step lookahead decoding for diffusion language models
Read the original at arxiv.org→arXiv:2607.15655v1 Announce Type: new Abstract: Masked diffusion language models (DLMs) enable parallel text generation by iteratively refining masked tokens, offering a promising alternative to autoregressive...
Original headline: "Adaptive Multi-Step Lookahead Decoding for Diffusion Language Models"
Coverage timeline
- Jul 20, 04:00 UTC arXiv cs.CL lead source Adaptive Multi-Step Lookahead Decoding for Diffusion Language Models
- Jul 20, 04:00 UTC arXiv cs.CL Induction in Both Directions: A Mechanistic Analysis of In-Context Learning in Masked Diffusion Language Models
- Jul 21, 04:00 UTC arXiv cs.AI Masked Diffusion Language Models are Strong and Steerable Text-Based World Models for Agentic RL
- Jul 21, 04:00 UTC arXiv cs.AI JUMP: Single-Pass Membership Inference on Fine-Tuned Diffusion Language Models
- Jul 21, 04:00 UTC arXiv cs.CL Trace-Based On-Policy Distillation for Masked Diffusion Language Models
- Jul 23, 04:00 UTC arXiv cs.CL Multi-Mask Diffusion Language Models for Few-Step Generation