Follow the Latent Roadmap: Navigating Revocable Decoding for Diffusion LLMs with Anchor Tokens

arXiv:2606.16847 · cs.CL, cs.AI · Submitted 2026-06-15 · Read on arXiv

cs.CL, cs.AI

Submitted: 2026-06-15

Updated: 2026-09-16

Terminology

• Accuracy — 40× in this paper · explained in 1 episode
• Verification — 39× in this paper · explained in 2 episodes
• Anchor Tokens — 28× in this paper · explained in 1 episode
• Benchmark — 21× in this paper · explained in 2 episodes
• Consistency — 15× in this paper · explained in 3 episodes
• Diffusion Model — 11× in this paper · explained in 8 episodes
• Diffusion Models — 11× in this paper · explained in 6 episodes
• Anchor Tokens Cache — 9× in this paper
• Ablation — 8× in this paper · explained in 1 episode
• Embeddings — 8× in this paper · explained in 2 episodes
• Temporal consistency — 7× in this paper · explained in 2 episodes
• Alignment — 4× in this paper · explained in 1 episode
• Reinforcement Learning — 3× in this paper · explained in 4 episodes
• Anchor Supervised Revocable Decoding — 2× in this paper
• Failure Modes — 2× in this paper · explained in 3 episodes
• Training-Free Framework — 2× in this paper · explained in 2 episodes
• Ablation study — 1× in this paper · explained in 1 episode
• Adaptation — 1× in this paper · explained in 1 episode
• Attention Mechanism — 1× in this paper · explained in 3 episodes
• Computational overhead — 1× in this paper · explained in 2 episodes
• Core — 1× in this paper · explained in 2 episodes
• Decode — 1× in this paper · explained in 2 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• KV cache — 1× in this paper · explained in 3 episodes
• Supervised Fine-Tuning (SFT) — 1× in this paper · explained in 8 episodes
• Transformer — 1× in this paper · explained in 2 episodes
• Verifier — 1× in this paper · explained in 2 episodes

Sources

• Parallel Sampling from Masked Diffusion Models via Conditional Independence Testing
• LLaDA2.0: Scaling Up Diffusion Language Models to 100B
• Beyond Confidence: Adaptive and Coherent Decoding for Diffusion Language Models
• Evaluating Large Language Models Trained on Code
• Training Verifiers to Solve Math Word Problems
• Saber: An Efficient Sampling with Adaptive Acceleration and Backtracking Enhanced Remasking for Diffusion Language Model
• GPT-4 Technical Report
• Scaling Diffusion Language Models via Adaptation from Autoregressive Models
• Program Synthesis with Large Language Models
• DiffuSeq: Sequence to Sequence Text Generation with Diffusion Models
• DiffuCoder: Understanding and Improving Masked Diffusion Models for Code Generation
• The Llama 3 Herd of Models
• dLLM-Cache: Accelerating Diffusion Large Language Models with Adaptive Caching
• Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution
• dKV-Cache: The Cache for Diffusion Language Models
• Wide-In, Narrow-Out: Revokable Decoding for Efficient and Effective DLLMs
• Rethinking Reasoning with MDLMs: Early Exits, Post-hoc Reasoning, and Beyond
• Large Language Diffusion Models
• Accelerating Diffusion LLMs via Adaptive Parallel Decoding
• Your Absorbing Discrete Diffusion Secretly Models the Conditional Distributions of Clean Data

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