PIG: Parallel Inconsistency Guidance for Accelerating Diffusion Language Models
cs.CL
Submitted: 2026-10-12
Updated: 2026-10-12
Comments: 66 pages, 22 figures, 11 tables. Code: https://github.com/Quentin-Fruytier/PIG-DLM-release
Code: https://github.com/Quentin-Fruytier/PIG-DLM-release
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Sources
- Program Synthesis with Large Language Models
- Accelerated Sampling from Masked Diffusion Models via Entropy Bounded Unmasking
- Confidence-Based Decoding is Provably Efficient for Diffusion Language Models
- Evaluating Large Language Models Trained on Code
- Optimal Inference Schedules for Masked Diffusion Models
- Training Verifiers to Solve Math Word Problems
- Nemotron-Labs-Diffusion: A Tri-Mode Language Model Unifying Autoregressive, Diffusion, and Self-Speculation Decoding
- Learning Unmasking Policies for Diffusion Language Models
- DAPD: Dependency-Aware Parallel Decoding via Attention for Diffusion LLMs
- CD4LM: Consistency Distillation and aDaptive Decoding for Diffusion Language Models
- Large Language Diffusion Models
- Cluster-Level Attention-Guided Parallel Decoding for Masked Diffusion Language Models
- Dependency-Guided Parallel Decoding in Discrete Diffusion Language Models
- Attention-Discounted Adaptive Sampler for Masked Diffusion Language Models
- DiffusionGemma Technical Report
- Fast-dLLM: Training-free Acceleration of Diffusion LLM by Enabling KV Cache and Parallel Decoding
- Generation Order and Parallel Decoding in Masked Diffusion Models: An Information-Theoretic Perspective
- Attention-Based Sampler for Diffusion Language Models
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