AIDASLab/Awesome-Diffusion-LLM

A comprehensive list of papers about Large-Language-Diffusion-Models.

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updated Sep 1, 2026

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Awesome-Large-Language-Diffusion-Models

A comprehensive and structured list of research papers about Large-Language-Diffusion-Models (dLLMs).

Last major update: September 2026 — added 169 new papers from Jun–Aug 2026.

⚙️ Framework (Taxonomy)

Surveys & Useful Resources
Core Methodologies
Reasoning & Policy Optimization
- Reasoning & Planning
- Alignment & RL
Token Ordering & Generation Strategies
System Efficiency & Acceleration
Multi-modal & Physical AI
Agentic & Tool-Use dLLMs
Theory, Guidance & Applications
- Theory & Analysis
- Guidance & Downstream Applications
Seminal Diffusion Papers

1. Surveys & Useful Resources

📚 Blogs & Reports

📝 Survey & Perspective Papers

Paper Title	Year	Venue	Remark
Diffusion Models for Non-autoregressive Text Generation: A Survey	2023.03	IJCAI	Early NAR-text survey
A Survey of Diffusion Models in NLP	2023.05	Arxiv	Early NLP survey
Discrete Diffusion in Large Language and Multimodal Models: A Survey	2025.06	Arxiv	dLLM + dMLLM
Diffusion-based Large Language Models Survey	2025.08	TechRxiv	-
A Survey on Parallel Text Generation: From Parallel Decoding to Diffusion Language Models	2025.08	Arxiv	-
A Survey on Diffusion Language Models	2025.08	Arxiv	VILA-Lab; comprehensive
Efficient Diffusion Language Models: A Comprehensive Survey	2026.01		Efficiency-focused
Top 10 Open Challenges Steering the Future of Diffusion Language Model and Its Variants	2026.01	Arxiv	Perspective / roadmap
A Tutorial on Diffusion Theory: From Differential Equations to Diffusion Models	2026.05	Arxiv	Tutorial, Diffusion theory
Accelerating Masked Diffusion Large Language Models: A Survey of Efficient Inference Techniques	2026.07	Arxiv	A Survey of Efficient Inference Techniques
Is Multimodal Speculative Decoding Ready for Diffusion-Based Parallel Drafting? A Survey and Empirical Diagnosis	2026.08	Arxiv	Speculative decoding, Summarization

2. Core Methodologies

2.1 Discrete & Masked Diffusion

Paper Title	Year	Venue	Remark
DiffusER: Discrete Diffusion via Edit-based Reconstruction	2022.10	ICLR	<7B
SSD-LM: Semi-autoregressive Simplex-based Diffusion for Modular Control	2022.10	ACL	<7B, Simplex
DiffusionBERT: Improving Generative Masked Language Models	2022.11	ACL	<7B, Masked
A Reparameterized Discrete Diffusion Model for Text Generation	2023.02	COLM	<7B
David helps Goliath: Inference-Time Collaboration Between Small and Large Diffusion LMs	2023.05	NAACL	>7B, Scale-collaboration
TESS: Text-to-Text Self-Conditioned Simplex Diffusion	2023.05	EACL	<7B, Simplex
Diffusion Language Models Can Perform Many Tasks with Scaling and Instruction-Finetuning	2023.08	Arxiv	>7B, Scaling
Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution (SEDD)	2023.10	ICML	<7B, Discrete
Simplified and Generalized Masked Diffusion for Discrete Data (MD4)	2024.06	NeurIPS	-
Simple and Effective Masked Diffusion Language Models (MDLM)	2024.06	NeurIPS	<7B, Masked
Your Absorbing Discrete Diffusion Secretly Models the Conditional Distributions of Clean Data (RADD)	2024.06	ICLR	<7B, Masked
Scaling up Masked Diffusion Models on Text (SMDM)	2024.10	ICLR	<7B, 1.1B Scaling
Energy-Based Diffusion Language Models for Text Generation (EDLM)	2024.10	ICLR	<7B
Conditional MASK Discrete Diffusion Language Model	2024.11	EMNLP	<7B
Non-Markovian Discrete Diffusion with Causal Language Models	2025.02	NeurIPS	<7B
Large Language Diffusion Models (LLaDA)	2025.02	NeurIPS	>7B, LLaDA-8B
Anchored Diffusion Language Model (ADLM)	2025.05	NeurIPS	>7B; ANELBO objective
LongLLaDA: Unlocking Long Context Capabilities in Diffusion LLMs	2025.06	AAAI	>7B, Context Scaling
Esoteric Language Models (Eso-LMs)	2025.06	ICML	AR + MDM hybrid
Dream 7B: Diffusion Large Language Models	2025.08	Arxiv	>7B, Dream-7B
Sequential Diffusion Language Models	2025.09	Arxiv	>7B
LLaDA-MoE: A Sparse MoE Diffusion Language Model	2025.09	Arxiv	>7B, 7B-A1B MoE from scratch
UltraLLaDA: Scaling Context to 128K	2025.10	Arxiv	>7B, Context Scaling
Next Semantic Scale Prediction via Hierarchical Diffusion Language Models	2025.10	NeurIPS	-
Masked Diffusion Models as Energy Minimization	2025.10	NeurIPS	<7B
Soft-Masked Diffusion Language Models	2025.10	ICLR	<7B
Variational Masked Diffusion Models	2025.10	Arxiv	<7B
Diffusion LLM with Native Variable Generation Lengths: Let [EOS] Lead the Way	2025.10	Arxiv	>7B, Variable Length
Diffusion Language Models are Super Data Learners	2025.11	Arxiv	Data efficiency
DiffuMamba: High-Throughput Diffusion LMs with Mamba Backbone	2025.11	Arxiv	Non-Transformer Backbone
TiDAR: Think in Diffusion, Talk in Autoregression	2025.11	Arxiv	>7B
C2DLM: Causal Concept-Guided Diffusion Large Language Models	2025.11	Arxiv	>7B
Beyond Hard Masks: Progressive Token Evolution for Diffusion Language Models	2026.01	ACL	Soft tokens, Masked
LLaDA2.0: Scaling Up Diffusion Language Models to 100B	2025.12	Arxiv	>100B, MoE; Ant Group
LLaDA2.1: Speeding Up Text Diffusion via Token Editing	2026.02	Arxiv	Editable State Evolution
Introspective Diffusion Language Models (I-DLM)	2026.04	Arxiv	Introspective consistency
W1-4B-dLLM (WhaletechAI)	2026.04	HF Model	4B open dLLM; demo
Scaling Beyond Masked Diffusion Language Models	2026.02	Arxiv	Uniform-state & interpolating diffusion scaling
dLLM: Simple Diffusion Language Modeling	2026.02	Arxiv	Unified open-source dLLM framework
Generalized Discrete Diffusion from Snapshots	2026.03	Arxiv	Unified arbitrary noising framework
Diffutron: A Masked Diffusion Language Model for Turkish Language	2026.03	Arxiv	Multilingual, Turkish MDM
Expert-Choice Routing Enables Adaptive Computation in Diffusion Language Models	2026.04	COLM	MoE, Expert-choice routing
Rethinking Token Prediction: Tree-Structured Diffusion Language Model	2026.04	Arxiv	Tree-structured token prediction
Drifting Objectives for Refining Discrete Diffusion Language Models	2026.05	Arxiv	TokenDrift, anti-symmetric objective
Forward-Free Diffusion Language Models with BPTT-Free Looped Refinement	2026.06	Arxiv	-
Semantic DLM+: Improving Diffusion Language Models through Bias-variance Trade-off in Transition Kernel Design	2026.06	Arxiv	Improving Diffusion Language Models through Bias-variance
VoidPadding: Let [VOID] Handle Padding in Masked Diffusion Language Models so that [EOS] Can Focus on Semantic Termination	2026.06	Arxiv	Code
Sumi: Open Uniform Diffusion Language Model from Scratch	2026.06	Arxiv	Open Uniform Diffusion Language Model from
Improved Large Language Diffusion Models	2026.06	Arxiv	-
Bifocal Diffusion Language Models: Asymmetric Bidirectional Context for Parallel Generation	2026.06	Arxiv	KV cache, Serving
Tensor-Train Joint Modeling for Few-Step Discrete Diffusion	2026.07	Arxiv	Few-step, Unmasking order
PreDiff-LM: Pretrained Discrete Masked Diffusion Language Modeling with Hybrid Attention	2026.07	Arxiv	Pretrained Discrete Masked Diffusion Language Modeling
DiffusionGemma Technical Report	2026.07	Arxiv	MoE, Speculative decoding
Mean-to-Score Discrete Diffusion: Posterior-Mean Denoisers for Score Entropy	2026.07	Arxiv	Posterior-Mean Denoisers for Score Entropy
LLaDA MoE v2: Scaling Mixture-of-Experts Diffusion Language Models	2026.08	Arxiv	MoE
MDLMPE: Distribution Aware Positional Encoding for Masked Diffusion Language Models	2026.08	Arxiv	Distribution Aware Positional Encoding for Masked
Retrofitting Linear Attention into Diffusion Language Models	2026.08	Arxiv	Block diffusion, Serving
Reducing Pretraining-Generation Mismatch in Diffusion Language Models	2026.08	Arxiv	-

2.2 Continuous & Latent Space Diffusion

Paper Title	Year	Venue	Remark
Diffusion-LM Improves Controllable Text Generation	2022.05	NeurIPS	<7B, Embedding
DiffuSeq: Sequence to Sequence Text Generation	2022.10	ICLR	<7B, Embedding
Latent Diffusion for Language Generation	2022.12	NeurIPS	<7B, Latent
Diffusion Glancing Transformer for Parallel Sequence to Sequence Learning	2022.12	NAACL	<7B
Empowering Diffusion Models on the Embedding Space for Text Generation	2022.12	NAACL	<7B, Embedding
Text Generation with Diffusion Language Models: A Pre-training Approach with Continuous Paragraph Denoise	2022.12	ICML	<7B, Embedding
DINOISER: Diffused Conditional Sequence Learning by Manipulating Noises	2023.02	TACL	<7B, Embedding
Likelihood-Based Diffusion Language Models (Plaid)	2023.05	NeurIPS	<7B, Plaid 1B
PLANNER: Generating Diversified Paragraph via Latent Language Diffusion Model	2023.06	NeurIPS	<7B, Latent
Edit Flows: Flow Matching with Edit Operations	2025.06	Arxiv	-
Coevolutionary Continuous Discrete Diffusion: Latent Reasoner	2025.10	ICML	>7B; CCDD
Stop-Think-AutoRegress: Language Modeling with Latent Diffusion Planning	2026.02	Arxiv	Latent planning + AR hybrid
CoDAR: Continuous Diffusion Language Models are More Powerful Than You Think	2026.03	Arxiv	Contextual AR decoder for continuous diffusion
LangFlow: Continuous Diffusion Rivals Discrete in Language Modeling	2026.04	Arxiv	Flow matching via Bregman divergence
Scaling Properties of Continuous Diffusion Spoken Language Models	2026.04	Arxiv	Continuous diffusion SLM, scaling laws
Towards Closing the Autoregressive Gap via Entropy-Gated Continuous Bitstream Diffusion	2026.05	Arxiv	Continuous bitstream diffusion
TextLDM: Language Modeling with Continuous Latent Diffusion	2026.05	Arxiv	DiT-style flow matching for text
How to Train Your Latent Diffusion Language Model Jointly With the Latent Space	2026.05	Arxiv	Joint latent encoder+diffusion training
BitLM: Unlocking Multi-Token Language Generation with Bitwise Continuous Diffusion	2026.05	Arxiv	Bitwise continuous diffusion head
Language Generation as Optimal Control: Closed-Loop Diffusion in Latent Control Space	2026.05	Arxiv	HJB-based latent optimal control
Continuous Diffusion Scales Competitively with Discrete Diffusion for Language	2026.05	Arxiv	RePlaid scaling law, continuous vs discrete
Simplex Relaxation for Discrete Diffusion	2026.08	Arxiv	-

2.3 AR-to-Diffusion Adaptation

Paper Title	Year	Venue	Remark
Scaling Diffusion Language Models via Adaptation from Autoregressive Models (DiffuLLM)	2024.10	ICLR	>7B, GPT2/LLaMA2 Adaptation
Large Language Models to Diffusion Finetuning	2025.01	ICML	>7B
TESS 2: A Large-Scale Generalist Diffusion Language Model	2025.02	ACL	>7B, Adapted from Mistral
SDAR: A Synergistic Diffusion-AutoRegression Paradigm	2025.10	Arxiv	>7B, Qwen3-based BD
From Next-Token to Next-Block: Principled Adaptation Path	2025.11	Arxiv	>7B, Adaptation Path
Efficient-DLM: From Autoregressive to Diffusion Language Models, and Beyond in Speed	2025.12	Arxiv	>7B
LLaDA2.0: Scaling Up Diffusion Language Models to 100B	2025.12	Arxiv	>7B, AR→dLLM at 100B
Where Should Diffusion Enter a Language Model? Geometry-Guided Hidden-State Replacement	2026.05	Arxiv	Geometry-guided layer insertion
Data-Efficient Autoregressive-to-Diffusion Language Models via On-Policy Distillation	2026.06	Arxiv	Distillation
Nemotron-Labs-TwoTower: Diffusion Language Modeling with Pretrained Autoregressive Context	2026.06	Arxiv	MoE, Block diffusion
UNIFUSION: Adapting Autoregressive Language Models into Discrete Diffusion under a Unified Reverse-Rate Objective	2026.07	Arxiv	Adapting Autoregressive Language Models into Discrete

2.4 Hybrid AR-Diffusion (Block / Forcing)

A new section: hybrids that interleave block-level AR with intra-block diffusion, or "forcing" approaches that retain causal masks for KV-cache reuse.

Paper Title	Year	Venue	Remark
Block Diffusion: Interpolating Between Autoregressive and Diffusion Language Models (BD3-LM)	2025.03	ICLR	<7B, Interpolation
D2F: Diffusion LLMs Can Do Faster-Than-AR Inference via Discrete Diffusion Forcing	2025.08	ICLR	>7B, Faster-than-AR
Blockwise SFT for Diffusion Language Models: Reconciling Bidirectional Attention and Autoregressive Decoding	2025.08	Arxiv	>7B
SDAR: Synergistic Diffusion-AutoRegression Paradigm	2025.10	Arxiv	>7B, Block hybrid
Encoder-Decoder Block Diffusion Language Models for Efficient Training and Inference (E2D2)	2025.10	NeurIPS	Block Enc-Dec
Fast-dLLM v2: Efficient Block-Diffusion LLM	2025.09	Arxiv	>7B, Block Decoding
WeDLM: Reconciling Diffusion Language Models with Standard Causal Attention for Fast Inference	2025.12	Arxiv	Causal-attn diffusion
ReFusion: Diffusion LLM with Parallel Autoregressive Decoding	2025.12	Arxiv	Slot-level interleaving
Swordsman: Entropy-Driven Adaptive Block Partition for Efficient Diffusion Language Models	2026.02	Arxiv	Adaptive block
DFlash: Block Diffusion for Flash Speculative Decoding	2026.02	ICML	Block + speculative
Breaking Block Boundaries: Anchor-based History-stable Decoding for Diffusion Large Language Models	2026.04	ACL	Anchor-based cross-block decoding
When to Commit? Towards Variable-Size Self-Contained Blocks for Discrete Diffusion Language Models	2026.04	Arxiv	Variable-size blocks
Dynamic Chunking for Diffusion Language Models	2026.05	Arxiv	Content-defined semantic chunks
FLARE: Diffusion for Hybrid Language Model	2026.06	Arxiv	Serving
BlockGen: Flexible Blockwise Sequence Modeling with Hybrid Samplers	2026.06	Arxiv	Few-step, Block diffusion
SemBlock: Semantic Boundary Dynamic Blocks for Diffusion LLMs	2026.06	Arxiv	Block diffusion
Multi-Block Diffusion Language Models	2026.06	Arxiv	Block diffusion
Adaptive Block Diffusion: Resolving Training-Inference Mismatch in Diffusion Language Models	2026.06	Arxiv	Block diffusion
Beyond Block Boundaries: Multi-Block Editing for Diffusion Large Language Models	2026.06	Arxiv	Training-free, KV cache
Set Diffusion: Interpolating Token Orderings Between Autoregression and Diffusion for Fast and Flexible Decoding	2026.07	ICML	KV cache, Block diffusion
Training Hybrid Block Diffusion Language Models with Partial Bidirectionality	2026.07	Arxiv	Block diffusion, Serving
Nemotron-Labs-Diffusion: A Tri-Mode Language Model Unifying Autoregressive, Diffusion, and Self-Speculation Decoding	2026.07	Arxiv	Serving

3. Reasoning & Policy Optimization

3.1 Reasoning & Planning

Paper Title	Year	Venue	Remark
Diffusion of Thought: Chain-of-Thought Reasoning in dLLMs	2024.02	NeurIPS	<7B, CoT Foundation
Beyond Autoregression: Discrete Diffusion for Complex Reasoning	2024.10	ICLR	<7B
Tree Reward-Aligned Search for TReASURe in Masked Diffusion Language Models	2025.09	Arxiv	Planning
d1: Scaling Reasoning in dLLMs via RL	2025.04	NeurIPS	>7B, Reasoning scaling
Reinforcing the Diffusion Chain of Lateral Thought	2025.05	NeurIPS	>7B
Thinking Inside the Mask: In-Place Prompting in dLLMs	2025.08	Arxiv	>7B
Reinforced Context Order Recovery for Adaptive Reasoning	2025.08	Arxiv	<7B, Planning
d2: Improved Techniques for Training Reasoning dLLMs	2025.09	Arxiv	>7B
LaDiR: Latent Diffusion Enhances LLMs for Text Reasoning	2025.10	Arxiv	>7B
Beyond Surface Reasoning: Unveiling Long CoT Capacity	2025.10	Arxiv	>7B
Coevolutionary Continuous Discrete Diffusion: Latent Reasoner	2025.10	ICML	>7B
On the Reasoning Abilities of Masked Diffusion Language Models	2025.10	Arxiv	>7B
Planner and Executor: Collaboration between Discrete Diffusion And Autoregressive Models in Reasoning	2025.10	Arxiv	Collaboration
Diffuse Thinking: Exploring Diffusion Language Models as Efficient Thought Proposers for Reasoning	2025.10	Arxiv	>7B
Test-Time Scaling with Diffusion Language Models via Reward-Guided Stitching	2026.02	Arxiv	Step-level rationale stitching
Reasoning or Rationalization? The Role of Justifications in Masked Diffusion Models for Fact Verification	2026.03	Arxiv	CoT dynamics analysis
Diffusion LLMs can think EoS-by-EoS	2026.03	Arxiv	EoS-guided reasoning via padding
LogicDiff: Logic-Guided Denoising Improves Reasoning in Masked Diffusion Language Models	2026.03	Arxiv	Logic-guided unmasking order
Learnability-Informed Fine-Tuning of Diffusion Language Models	2026.05	Arxiv	LIFT, SFT with learnability schedule
d-OPSD: On-Policy Self-Distillation for Diffusion Language Models	2026.06	Arxiv	On-policy self-distillation, Code
Multi-Turn Reflective Masking Elicits Reasoning in Mask Diffusion Models	2026.06	Arxiv	-
DreamReasoner-8B: Block-Size Curriculum Learning for Diffusion Reasoning Models	2026.06	Arxiv	8B, Block diffusion
Diffusion-Proof: Recipe for Formal Theorem Proving Beyond Auto-Regressive Generation	2026.06	Arxiv	Block diffusion
Scheduling Thoughts: Learning the Order of Thought in Diffusion Language Models	2026.06	Arxiv	Unmasking order
Escaping Confidence Trap: Evolutionary Decoding for Mathematical Reasoning in Diffusion LLMs	2026.08	Arxiv	Training-free, Unmasking order
Semantic Reasoning Denoising: Correcting Language Model Reasoning with Semantic Operators	2026.08	Arxiv	Correcting Language Model Reasoning with Semantic
DCGC: Draft-Conditioned Global Correction for Complex Reasoning with Masked Diffusion Models	2026.08	Arxiv	Draft-Conditioned Global Correction for Complex Reasoning

3.2 Alignment & Reinforcement Learning

Paper Title	Year	Venue	Remark
Preference-Based Alignment of Discrete Diffusion Models	2025.03	Arxiv	>7B
DiFFPO: Training dLLMs to Reason Fast and Furious via RL	2025.10	Arxiv	>7B, Direct Preference
LLaDA 1.5: Variance-Reduced Preference Optimization	2025.05	Arxiv	>7B
wd1: Weighted Policy Optimization for Reasoning	2025.07	ICLR	>7B
Where to Start Alignment? Diffusion Large Language Model May Demand a Distinct Position	2025.08	AAAI	>7B, Safety
Jailbreaking Large Language Diffusion Models: Revealing Hidden Safety Flaws in Diffusion-Based Text Generation	2025.07	Arxiv	Safety
The Devil behind the mask: An emergent safety vulnerability	2025.07	ICLR	Safety
MDPO: Overcoming the Training-Inference Divide	2025.08	Arxiv	>7B
Reward-Weighted Sampling: Enhancing Non-Autoregressive Characteristics in Masked Diffusion LLMs	2025.08	EMNLP	>7B
Inpainting-Guided Policy Optimization for dLLMs	2025.09	Arxiv	>7B
Taming Masked Diffusion via Consistency Trajectory RL	2025.09	Arxiv	>7B
TR2-D2: Tree Search Guided Trajectory-Aware Fine-Tuning	2025.09	Arxiv	>7B
Revolutionizing RL Framework for Diffusion Large Language Models	2025.09	Arxiv	>7B
A2D: Any-Order, Any-Step Safety Alignment for Diffusion Language Models	2025.09	ICLR	Safety
DiffuGuard: How Intrinsic Safety is Lost and Found in Diffusion Large Language Models	2025.09	Arxiv	Safety
RFG: Test-Time Scaling for Diffusion Large Language Model Reasoning with Reward-Free Guidance	2025.09	Arxiv	>7B
AGRPO: Simple Policy Gradients for Reasoning with Diffusion Language Models	2025.10	Arxiv	>7B
Improving Reasoning via Group Diffusion Policy Optimization (GDPO)	2025.10	Arxiv	>7B
Step-Aware Policy Optimization for Reasoning	2025.10	Arxiv	>7B
MRO: Enhancing Reasoning via Multi-Reward Optimization	2025.10	NeurIPS	>7B
Enhancing Reasoning via Distribution Matching Policy Optimization	2025.10	Arxiv	>7B
Boundary-Guided Policy Optimization for Memory-efficient RL	2025.10	Arxiv	>7B
SPG: Sandwiched Policy Gradient for Masked Diffusion	2025.10	Arxiv	>7B
Improving Discrete Diffusion Unmasking Policies Beyond Explicit Reference Policies	2025.10	ICLR	>7B
Latent Refinement Decoding: Enhancing Diffusion-Based Language Models by Refining Belief States	2025.10	Arxiv	>7B
Principled RL for Diffusion LLMs Emerges from a Sequence-Level Perspective	2025.12	Arxiv	>7B
d-TreeRPO: Towards More Reliable Policy Optimization for Diffusion Language Models	2025.12	Arxiv	>7B
DARE: Diffusion Large Language Models Alignment and Reinforcement Executor	2026.04	Arxiv	Unified RL framework
DiRL: An Efficient Post-Training Framework for Diffusion Language Models	2025.12	Arxiv	Post-training
Efficient and Stable Reinforcement Learning for Diffusion Language Models	2026.02	Arxiv	Variance reduction
Agents of Diffusion: Enhancing Diffusion Language Models with Multi-Agent Reinforcement Learning for Structured Data Generation	2026.01	Arxiv	Multi-agent RL
Reinforcement Learning for Diffusion LLMs with Entropy-Guided Step Selection and Stepwise Advantages	2026.03	Arxiv	MDP formulation, entropy-guided steps
TRIMS: Trajectory-Ranked Instruction Masked Supervision for Diffusion Language Models	2026.04	Arxiv	Trajectory-ranked SFT
Relative Score Policy Optimization for Diffusion Language Models	2026.05	Arxiv	RSPO, RLVR for dLLMs
Adaptive Steering and Remasking for Safe Generation in Diffusion Language Models	2026.05	Arxiv	Safety, contrastive steering
Beyond Mode-Seeking RL: Trajectory-Balance Post-Training for Diffusion Language Models	2026.05	Arxiv	TraFL, trajectory-balance objective
Read the Trace, Steer the Path: Trajectory-Aware Reinforcement Learning for Diffusion Language Models	2026.06	Arxiv	MoE, Unmasking order
Back on Track: Aligning Rewards and States for Reasoning in Diffusion Large Language Models	2026.06	Arxiv	RL
A2D2: Fine-Tuning Any-Length Discrete Diffusion for Adaptive Decoding	2026.06	Arxiv	Unmasking order
SLIM-RL: Risk-Budgeted Random-Masking RL for Diffusion LLMs Without Trajectory Slicing	2026.06	Arxiv	Training-free, RL
A Continuous-Time Reinforcement Learning Framework for Fine-Tuning Discrete Diffusion Models	2026.07	Arxiv	RL
Mask-Aware Policy Gradients for Diffusion Language Models	2026.07	COLM	Remasking, Unmasking order
Beyond On-Policy Exploration: Integrating External Policy Rollouts for Reinforcement Learning in Diffusion Language Models	2026.08	Arxiv	RL

4. Token Ordering & Generation Strategies

Paper Title	Year	Venue	Remark
SSD-LM: Semi-autoregressive Simplex-based Diffusion for Modular Control	2022.10	ACL	<7B, Blockwise
AR-Diffusion: Auto-Regressive Diffusion Model for Text Generation	2023.05	NeurIPS	<7B, AR-like noise
Train for the Worst, Plan for the Best: Understanding Token Ordering	2025.02	ICML	<7B, Ordering Analysis
Block Diffusion: Interpolating Between Autoregressive and Diffusion LMs	2025.03	ICLR	<7B, Interpolation
Review, Remask, Refine (R3): Process-Guided Block Diffusion	2025.07	ICML MOSS	>7B, Block-wise
Any-Order Flexible Length Masked Diffusion	2025.09	Arxiv	<7B, Order Flexibility
Don't Settle Too Early: Self-Reflective Remasking for Diffusion Language Models	2025.09	Arxiv	>7B, Remasking
Don't Let It Fade: Preserving Edits via Token Timestep Allocation	2025.10	NeurIPS	<7B, Edit preservation
Finish First, Perfect Later: Test-Time Token-Level Cross-Validation for Diffusion Large Language Models	2025.10	Arxiv	>7B, Unmasking
Improving Discrete Diffusion Unmasking Policies Beyond Explicit Reference Policies	2025.10	ICLR	>7B, Unmasking
Parallel Sampling from Masked Diffusion Models via Conditional Independence Testing	2025.10	Arxiv	>7B, Unmasking
Diffusion Language Model Inference with Monte Carlo Tree Search	2025.12	Arxiv	>7B, MCTS
Optimizing Decoding Paths in Masked Diffusion Models by Quantifying Uncertainty	2025.12	Arxiv	>7B, Unmasking
Adaptation to Intrinsic Dependence in Diffusion Language Models	2026.02	Arxiv	Distribution-agnostic schedule
Efficient Self-Evaluation for Diffusion Language Models via Sequence Regeneration	2026.03	ACL	Self-evaluation, Flexible length
D5P4: Partition Determinantal Point Process for Diversity in Parallel Discrete Diffusion Decoding	2026.03	Arxiv	Diversity-aware decoding
Improving Sampling for Masked Diffusion Models via Information Gain	2026.02	Arxiv	Info-Gain sampler
DOS: Dependency-Oriented Sampler for Masked Diffusion Language Models	2026.03	Arxiv	Dependency-aware unmasking
Diffusion Language Models Are Natively Length-Aware	2026.03	Arxiv	Length-aware EoS generation
Locally Confident, Globally Stuck: The Quality-Exploration Dilemma in Diffusion Language Models	2026.04	Arxiv	Quality vs exploration trade-off
Remask, Don't Replace: Token-to-Mask Refinement in Masked Diffusion Language Models	2026.04	Arxiv	T2M refinement, LLaDA2.1 analysis
Edit-Based Refinement for Parallel Masked Diffusion Language Models	2026.05	ICML	ME-DLM, edit-based post-correction
When Confidence Misleads: Suffix Anchoring and Anchor-Proximity Confidence Modulation for Diffusion Language Models	2026.05	Arxiv	Suffix anchor, confidence modulation
Supportive Token Revealing for Fast Diffusion Language Model Decoding	2026.06	Arxiv	Training-free
NAVIRA: Decoupled Stochastic Remasking for Masked Diffusion Language Models	2026.06	Arxiv	Remasking, Unmasking order
Re-evaluating Confidence Remasking in Masked Diffusion Language Models	2026.06	Arxiv	Training-free, Remasking
Beyond Fully Random Masking: Attention-Guided Denoising and Optimization for Diffusion Language Models	2026.06	ACL	Unmasking order, RL
Who Should Lead Decoding Now? Tracking Reliable Trajectories for Ensembling Masked Diffusion Language Models	2026.06	Arxiv	-
Follow the Latent Roadmap: Navigating Revocable Decoding for Diffusion LLMs with Anchor Tokens	2026.06	Arxiv	Training-free, Remasking
When to Plan, When to Polish: Noise Level as a Granularity Axis for Diffusion Language Models	2026.06	Arxiv	Noise Level as a Granularity Axis
TACG: Trajectory-Aware Commit Gating for Diffusion Language Model Decoding	2026.07	Arxiv	Training-free
Don't Commit Alone: Joint Token Commitment in Diffusion Language Models	2026.07	Arxiv	Joint Token Commitment in Diffusion Language
Reinforcing the Generation Order of Multimodal Masked Diffusion Models	2026.07	Arxiv	RL, dMLLM
ST-Veto: Spatio-Temporal Token Veto for Diffusion MLLMs via Taylor Prediction and Visual Grounding	2026.07	ICML	Training-free, Unmasking order
Rethinking the Generation Order of Block Diffusion Language Models	2026.07	Arxiv	Training-free, Unmasking order
Commit Locally, Exit Globally: Coordinating Adaptive Sampling and Early Exit in Diffusion Language Models	2026.07	Arxiv	Coordinating Adaptive Sampling and Early Exit
Context-Aware Cluster Decoding: Semantic Anchor-Driven Coherence in dMLLMs	2026.08	EMNLP	dMLLM, Context-aware token ordering, Code
Ripple-Pivot Search: Active Parallel Decoding for Diffusion Large Language Models	2026.08	Arxiv	Training-free, Unmasking order
Dependency-Aware Revocable Decoding for Efficient Diffusion Large Language Model Inference	2026.08	Arxiv	Training-free, Remasking
Visual Information-Guided Parallel Decoding for Diffusion Multimodal Large Language Models	2026.08	Arxiv	Unmasking order, dMLLM
Information-Guided Frontier Decoding: Contextual Utility-Driven Commitment in dMLLMs	2026.08	EMNLP Findings	Training-free, Hallucination

5. System Efficiency & Acceleration

5.1 Caching & Memory Strategy

Paper Title	Year	Venue	Remark
dKV-Cache: The Cache for Diffusion Language Models	2025.05	NeurIPS	>7B
FlashDLM: Accelerating Diffusion Language Model Inference via Efficient KV Caching and Guided Diffusion	2025.05	Arxiv	>7B
Fast-dLLM: Training-free Acceleration via KV Cache + Parallel Decoding	2025.05	Arxiv	NVIDIA; KV cache + parallel
dLLM-Cache: Accelerating Diffusion Large Language Models with Adaptive Caching	2025.06	ICML	>7B
d^2Cache: Accelerating via Dual Adaptive Caching	2025.09	ICLR	>7B
Attention Is All You Need for KV Cache in dLLMs	2025.10	Arxiv	>7B
Attention Sinks in Diffusion Language Models	2025.10	Arxiv	>7B
WeDLM: Reconciling Diffusion Language Models with Standard Causal Attention for Fast Inference	2025.12	Arxiv	>7B, Causal cache
Stop the Flip-Flop: Context-Preserving Verification for Fast Revocable Diffusion Decoding (COVER)	2026.02	Arxiv	KV-override verification
Focus-dLLM: Accelerating Long-Context Diffusion LLM Inference via Confidence-Guided Context Focusing	2026.02	Arxiv	Long-context sparsity
Mosaic: Unlocking Long-Context Inference for Diffusion LLMs via Global Memory Planning and Dynamic Peak Taming	2026.01	Arxiv	Long-context memory
Residual Context Diffusion Language Models	2026.01	Arxiv	Recycle discarded tokens
MAGE: All-[MASK] Block Already Knows Where to Look in Diffusion LLM	2026.02	Arxiv	MASK-guided sparse attention, block dLLM
MetaState: Persistent Working Memory for Discrete Diffusion Language Models	2026.03	Arxiv	GRU-style cross-step memory
DyLLM: Efficient Diffusion LLM Inference via Saliency-based Token Selection and Partial Attention	2026.03	ICML	Saliency-based partial attention
EntropyCache: Decoded Token Entropy Guided KV Caching for Diffusion Language Models	2026.03	Arxiv	Entropy-guided KV cache refresh
LoSA: Locality Aware Sparse Attention for Block-Wise Diffusion Language Models	2026.04	Arxiv	Locality-aware sparse KV, block dLLM
PulseCol: Periodically Refreshed Column-Sparse Attention for Accelerating Diffusion Language Models	2026.05	Arxiv	Column-sparse attention, periodic refresh
Fast-dLLM++: Fréchet Profile Decoding for Faster Diffusion LLM Inference	2026.06	ICML Workshop
Prefilling-dLLM: Predictive Prefilling for Long-Context Inference in Diffusion Language Models	2026.06	EMNLP	Training-free, Long context
HERALD: High-Throughput Block Diffusion LLM Serving via CPU-GPU Cooperative KV Cache Retrieval	2026.06	Arxiv	KV cache, Block diffusion
Affix Cache for Diffusion Large Language Models	2026.06	Arxiv	Serving
LaCache: Exact Caching and Precision-Adaptive Inference for Diffusion Large Language Models	2026.07	Arxiv	Training-free, Quantization
Archer: Adaptive Reuse of Cached Hidden States for Efficient Rollback in Diffusion Language Models	2026.08	Arxiv	Training-free

5.2 Decoding & Sampling

Paper Title	Year	Venue	Remark
Speculative Diffusion Decoding: Accelerating Language Generation through Diffusion	2024.08	NAACL	<7B, Speculative Decoding
Wide-In, Narrow-Out: Revokable Decoding for Effective dLLMs	2025.07	Arxiv	>7B
Accelerating Diffusion LLMs via Adaptive Parallel Decoding (APD)	2025.05	NeurIPS	>7B
DLM-One: Diffusion Language Models for One-Step Generation	2025.06	Arxiv	<7B
Accelerating Diffusion Large Language Models with SlowFast Sampling: The Three Golden Principles	2025.06	Arxiv	>7B
Plan for Speed: Dilated Scheduling for Masked Diffusion Language Models	2025.06	ICML	>7B
Beyond Fixed: Training-Free Variable-Length Denoising for Diffusion Large Language Models	2025.08	Arxiv	>7B
DPad: Efficient Diffusion Language Models with Suffix Dropout	2025.08	Arxiv	>7B
Fast and Fluent Diffusion Language Models via Convolutional Decoding and Rejective Fine-tuning	2025.09	NeurIPS	>7B
AdaBlock-dLLM: Semantic-Aware Inference via Adaptive Block Size	2025.09	ICLR	>7B
dParallel: Learnable Parallel Decoding for dLLMs	2025.09	Arxiv	>7B
Learning to Parallel: Accelerating dLLMs via Learnable Parallel Decoding	2025.09	Arxiv	>7B
Spiffy: Multiplying Acceleration via Lossless Speculative Decoding	2025.09	ICML Workshop	>7B, Speculative Decoding
DiffuSpec: Unlocking dLLMs for Speculative Decoding	2025.09	Arxiv	>7B, Speculative Decoding
Loopholing Discrete Diffusion: Deterministic Bypass of the Sampling Wall	2025.10	ICLR	>7B
Saber: Efficient Sampling with Backtracking Enhanced Remasking	2025.10	ACL	>7B
CreditDecoding: Parallel Decoding with Trace Credits	2025.10	ACL	>7B
Accelerating dLLM Inference via Local Determinism Propagation	2025.10	Arxiv	>7B
Self Speculative Decoding for Diffusion Large Language Models	2025.10	Arxiv	>7B, Speculative Decoding
SpecDiff-2: Scaling Diffusion Drafter Alignment	2025.11	Arxiv	>7B, Speculative Decoding
Orchestrating Dual-Boundaries: An Arithmetic Intensity Inspired Acceleration Framework for Diffusion Language Models	2025.11	Arxiv	>7B
Beyond Confidence: Adaptive and Coherent Decoding for Diffusion Language Models	2025.11	Arxiv	>7B
Fail Fast, Win Big: Rethinking the Drafting Strategy in Speculative Decoding via Diffusion LLMs	2025.12	Arxiv	>7B, Speculative Decoding
Fast-Decoding via Progress-Aware Confidence Schedules	2025.12	Arxiv	>7B
ReFusion: A Diffusion Large Language Model with Parallel Autoregressive Decoding	2025.12	Arxiv	>7B
Context-Aware Initialization for Reducing Generative Path Length in Diffusion Language Models	2025.12	Arxiv	>7B
DART: Diffusion-Inspired Speculative Decoding for Fast LLM Inference	2026.01	Arxiv	Speculative drafting
DFlash: Block Diffusion for Flash Speculative Decoding	2026.02	ICML	Block + speculative
Swordsman: Entropy-Driven Adaptive Block Partition for Efficient Diffusion Language Models	2026.02	Arxiv	Entropy-adaptive blocks
Divide and Conquer: Accelerating Diffusion-Based Large Language Models via Adaptive Parallel Decoding	2026.02	Arxiv	DiCo, three-phase parallel decoding
Free Lunch for Pass@k? Low Cost Diverse Sampling for Diffusion Language Models	2026.03	Arxiv	Diverse sampling, Pass@k
S2D2: Fast Decoding for Diffusion LLMs via Training-Free Self-Speculation	2026.03	Arxiv	Self-speculation, block diffusion
Dependency-Guided Parallel Decoding in Discrete Diffusion Language Models	2026.04	Arxiv	DEMASK, dependency predictor
DualDiffusion: A Speculative Decoding Strategy for Masked Diffusion Models	2026.04	Arxiv	Speculative + causal drafter
Accelerating Speculative Decoding with Block Diffusion Draft Trees	2026.04	Arxiv	Draft trees for block diffusion
Stability-Weighted Decoding for Diffusion Language Models	2026.04	Arxiv	KL-based token stability metric
R²-dLLM: Accelerating Diffusion Large Language Models via Spatio-Temporal Redundancy Reduction	2026.04	Arxiv	Spatial + temporal redundancy reduction
Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast	2026.05	Arxiv	Self-contrast, HD token focus
Factorization-Error-Free Discrete Diffusion Language Model via Speculative Decoding	2026.05	Arxiv	FeF-DLLM, prefix-conditioned factorization
PSD: Pushing the Pareto Frontier of Diffusion LLMs via Parallel Speculative Decoding	2026.05	Arxiv	Parallel speculative, hierarchical acceptance
Roll Out and Roll Back: Diffusion LLMs are Their Own Efficiency Teachers	2026.05	Arxiv	WINO revokable parallel decoding
Cost-Aware Diffusion Draft Trees for Speculative Decoding	2026.06	Arxiv	Speculative decoding, Block diffusion
DFlare: Scaling Up Draft Capacity for Block Diffusion Speculative Decoding	2026.06	Arxiv	Speculative decoding, Block diffusion
SimSD: Simple Speculative Decoding in Diffusion Language Models	2026.06	Arxiv	Training-free, KV cache
SAID: Accelerating Diffusion-Based Language Models via Scaffold-Aware Iterative Decoding	2026.06	Arxiv	Block diffusion
Diffusion Language Model Parallel Decoding via Product-of-Experts Bridge	2026.06	ICML	-
AsyncLane: Decoupling Refinement from Advancement in Diffusion Language Model Decoding	2026.06	Arxiv	Training-free, Block diffusion
Unified Energy for Invariant and Independent Decoding in Diffusion Language Models	2026.06	Arxiv	-
Attention-Discounted Adaptive Sampler for Masked Diffusion Language Models	2026.06	Arxiv	Training-free
Teaching Diffusion to Speculate Left-to-Right	2026.06	Arxiv	Speculative decoding
Mean-Field Parallel Decoding for Discrete Diffusion Language Models	2026.06	Arxiv	Training-free
LESS Is More: Mutual-Stability Sampling for Diffusion Language Models	2026.06	Arxiv	Training-free, Unmasking order
Speculative Refinement: A Hybrid Autoregressive Diffusion Decoding Strategy and Its Behavior Across Benchmarks	2026.06	Arxiv	Training-free
$x$-Prediction Flow: Efficient Continuous Decoding for Masked Diffusion Language Models	2026.06	Arxiv	Unmasking order, RL
BlockPilot: Instance-Adaptive Policy Learning for Diffusion-based Speculative Decoding	2026.06	Arxiv	Speculative decoding
PRESTO: Prefix-Aligned Tree Drafting for Diffusion Speculative Decoding	2026.06	Arxiv	Speculative decoding, Serving
GRAFT: Adaptive DLM-Based Draft Tree Construction with Target-Distilled Edge Scoring	2026.06	Arxiv	Speculative decoding, Serving
Accelerating Discrete Diffusion Models with Parallel-In-Time Sampling	2026.07	Arxiv	-
DominoTree: Conditional Tree-Structured Drafting with Domino for Speculative Decoding	2026.07	Arxiv	Training-free, Speculative decoding
Adaptive Multi-Step Lookahead Decoding for Diffusion Language Models	2026.07	Arxiv	Few-step
FlowBlock: Wavefront-Parallel Decoding for Self-Correcting Diffusion Language Models	2026.07	Arxiv	Training-free, KV cache
AdaFlash: Adaptive Speculative Decoding via On-Policy Distilled Diffusion Drafters	2026.07	Arxiv	Speculative decoding, Distillation
AngelSpec: Towards Real-World High Performance Inference with Speculative Decoding	2026.07	Arxiv	Speculative decoding, Serving
Speculative Correction: Draft-then-Refine Decoding for Diffusion Language Models	2026.07	Arxiv	Training-free, Speculative decoding
CORA-Diff: Confidence-Oriented Residual Acceptance for Efficient Diffusion Language Model Inference	2026.07	Arxiv	Training-free, Block diffusion
DAVET: Denoising-Aware Visual Evidence Trajectory Allocation for Diffusion Vision-Language Models	2026.08	Arxiv	Training-free, Compression
xPress: Parallel Refinement for Diffusion Drafters in Speculative Decoding	2026.08	Arxiv	Speculative decoding, Serving
DBLAST: Dependent Block Drafting for Stochastic Speculative Decoding	2026.08	Arxiv	Speculative decoding, Block diffusion
LibraSpec: Dynamic Diffusion-Based Speculative Decoding via Marginal-Gain-Driven Optimization	2026.08	Arxiv	Training-free, Speculative decoding
CForce: Boosting Parallel Decoding for dLLMs via Consistency Forcing	2026.08	Arxiv	Distillation
From Positionwise Confidence to Prefix Scheduling: Verifier Skipping in Speculative Decoding	2026.08	Arxiv	Speculative decoding
LiLiCorr: Lightweight Likelihood Correlation of Parallel Drafts for Speculative Decoding	2026.08	Arxiv	Speculative decoding, Serving
CAI-DLLM: Convergence Aware Inference for Diffusion Language Models	2026.08	Arxiv	Training-free, Long context
Accelerating Diffusion Language Models via Structured Suffix Modeling	2026.08	Arxiv	Training-free, KV cache
Prefix-Denoising Consistency: Test-Time Verification for Diffusion Language Models	2026.08	Arxiv	Unmasking order
Survival-Guided Length Control for Efficient Diffusion Language Models	2026.08	EMNLP	Training-free
Trajectory-Level Speculative Decoding for Diffusion Language Models	2026.08	Arxiv	Speculative decoding, Unmasking order
ReTrace: Rejected-Trajectory Conditioning for Speculative Decoding	2026.08	Arxiv	Speculative decoding, Code
Ceiling-Clipped Acceptance Histograms Indicate Stranded Speed-up in Block-Diffusion Speculative Decoding	2026.08	Arxiv	Speculative decoding
CARVE: Verified Expansion for Variable-Length Generation in Diffusion Language Models	2026.08	EMNLP Findings	Training-free, Block diffusion

5.3 Distillation, Quantization & Sparsity

Paper Title	Year	Venue	Remark
Beyond Autoregression: Fast LLMs via Self-Distillation Through Time	2024.10	ICLR	<7B, Distillation
Sparse-dLLM: Accelerating Diffusion LLMs with Dynamic Cache Eviction	2025.08	Arxiv	>7B, Sparsity
DLLMQuant: Quantizing Diffusion-based Large Language Models	2025.08	Arxiv	>7B, Quantization
Quantization Meets dLLMs: Post-training Quantization Study	2025.08	Arxiv	>7B, Quantization
FS-DFM: Few-Step Diffusion Language Model	2025.09	ICLR	>7B
SparseD: Sparse Attention for Diffusion Language Models	2025.09	Arxiv	>7B, Sparsity
LLaDA-MoE: A Sparse MoE Diffusion Language Model	2025.09	Arxiv	>7B, MoE
Ultra-Fast Language Generation via Discrete Diffusion Divergence Instruct	2025.10	Arxiv	>7B, Distillation
CDLM: Consistency Diffusion Language Models For Faster Sampling	2025.11	Arxiv	>7B, Consistency
Sink-Aware Pruning for Diffusion Language Models	2026.02	Arxiv	Unstable sink pruning
FastDiSS: Few-step Match Many-step Diffusion Language Model on Sequence-to-Sequence Generation	2026.04	ACL Findings	Few-step distillation, S2S
On the Quantization Robustness of Diffusion Language Models in Coding Benchmarks	2026.04	Arxiv	GPTQ/HAWQ on code dLLMs
Turning the TIDE: Cross-Architecture Distillation for Diffusion Large Language Models	2026.04	Arxiv	Cross-architecture dLLM distillation
TAD: Temporal-Aware Trajectory Self-Distillation for Fast and Accurate Diffusion LLM	2026.05	Arxiv	Trajectory self-distillation
Infinite Mask Diffusion for Few-Step Distillation	2026.05	Arxiv	IMDM, stochastic infinite-state mask
Self-Distilled Trajectory-Aware Boltzmann Modeling for Diffusion Language Models	2026.05	Arxiv	TABOM, Boltzmann ranking objective
DiLaDiff: Distilled Latent-Augmented Diffusion for Language Modeling	2026.05	Arxiv	Latent + consistency distillation
STaR-Quant: State-Time Consistent Post-Training Quantization for Diffusion Large Language Models	2026.06	Arxiv	Quantization, Unmasking order
FAIR-Calib: Frontier-Aware Instability-Reweighted Calibration for Post-Training Quantization of Diffusion Large Language Models	2026.06	ICML	Quantization
Seeing the End at Step Zero: Accelerating Diffusion MLLMs via MLP Sparsity-Aware Truncation	2026.07	Arxiv	Training-free, Serving
Trace-Based On-Policy Distillation for Masked Diffusion Language Models	2026.07	Arxiv	Distillation, RL
Multi-Mask Diffusion Language Models for Few-Step Generation	2026.07	Arxiv	Distillation, Few-step
Neuromorphic Diffusion Language Models: Addressing Compute and Memory Bottlenecks via Sparsity and Block Denoising	2026.07	Arxiv	Block diffusion, Serving
REFLEX: Rethinking MoE Inference as Refinement-Aware Compute Allocation in Diffusion Language Models	2026.08	Arxiv	MoE, Training-free
OPTD: On-Policy Transition Distillation with Consistency-Guided Adaptive Compression for Few-Step Diffusion Language Models	2026.08	Arxiv	Distillation, Few-step
SelFusion: Self-distillation for Diffusion Language Models	2026.08	ACL	Distillation

5.4 Inference Frameworks & Systems

New section: production-grade frameworks and runtime engineering for dLLMs.

Paper Title	Year	Venue	Remark
dlmserve	2026.05	Repo	First OSS serving engine for diffusion LMs (LLaDA family); OpenAI-compatible HTTP, step-level batching (2.5x HF), LocalLeap (1.8x). MIT.
FOCUS: DLLMs Know How to Tame Their Compute Bound	2026.01	ICML	Training-free inference system; token eviction for higher throughput
dInfer: An Efficient Inference Framework for Diffusion Language Models	2025.10	Arxiv	Modular framework, >1100 TPS
JetEngine (SDAR)	2025.10	Repo	Lightweight engine for SDAR (3700+ TPS on H200)
Mercury: Ultra-Fast Language Models Based on Diffusion	2025.06	Arxiv	Inception Labs commercial dLLM
Seed Diffusion: Large-Scale dLLM with High-Speed Inference	2025.08	Arxiv	ByteDance code-focused dLLM
TIDE: Efficient and Lossless MoE Diffusion LLM Inference with I/O-aware Expert Offload	2026.05	Arxiv	MoE expert offload, lossless
Efficient On-Device Diffusion LLM Inference with Mobile NPU	2026.06	Arxiv	KV cache, Speculative decoding
DiLaServe: High SLO Attainment Serving for Diffusion Language Models	2026.06	Arxiv	Serving
Sangam: Efficiently Serving Diffusion LLMs with the AR Stack	2026.07	Arxiv	Serving
BlockServe: Block-Grained Continuous Batching for High-Throughput Diffusion LLM Serving	2026.07	Arxiv	Serving
Serving Masked Diffusion LLMs: Characterization and Design Principles from Real Hardware	2026.08	Arxiv	Serving

Paper Title	Year	Venue	Remark
Dual Diffusion for Unified Image Generation and Understanding	2025.01	Arxiv	Unified Task
Unified Multimodal Discrete Diffusion (UniDisc)	2025.03	Arxiv	Unified Diffusion
LaViDa: A Large Diffusion LLM for Multimodal Understanding	2025.05	NeurIPS Spotlight	Understanding
MMaDA: Multimodal Large Diffusion Language Models	2025.05	NeurIPS	Native Multimodal
Dimple: Discrete Diffusion Multimodal LLM with Parallel Decoding	2025.05	Arxiv	Parallel Multimodal
LLaDA-V: Diffusion LLMs with Visual Instruction Tuning	2025.06	Arxiv	Visual Tuning
Muddit: Liberating Generation Beyond Text-to-Image	2025.05	ICLR	Multi-modal
Show-o2: Improved Native Unified Multimodal Models	2025.06	Arxiv	Unified Generation
Diffuse Everything: Multimodal Diffusion on Arbitrary Spaces	2025.06	ICML	Arbitrary Spaces
TBAC-UniImage: Unified Understanding and Generation by Ladder-Side Diffusion Tuning	2025.08	Arxiv	Tencent ladder-side tuning
Lumina-DiMOO: Omni Diffusion LLM for Generation	2025.10	Arxiv	Omni-generation
MMaDA-Parallel: Thinking-Aware Editing and Generation	2025.11	Arxiv	Parallel Multimodal
DiffusionVL: Translating AR Models into Diffusion VL Models	2025.12	Arxiv	VL Adaptation
SDAR-VL: Stable and Efficient Block-wise Diffusion for Vision-Language Understanding	2025.12	Arxiv	Block-diffusion VL
Dream-VL: Open Vision-Language Model with Diffusion Backbone	2025.12	Arxiv	dVLM from Dream-7B
LaViDa-R1: Advancing Reasoning for Unified Multimodal Diffusion Language Models	2026.02	Arxiv	Unified RL post-training
Omni-Diffusion: Unified Multimodal Understanding and Generation with Masked Discrete Diffusion	2026.03	ICML	Any-to-any (text/speech/image)
LLaDA2.0-Uni: Unifying Multimodal Understanding and Generation	2026.04	Arxiv	SigLIP-VQ + block diffusion
Fast-dVLM: Efficient Block-Diffusion VLM via Direct Conversion from Autoregressive VLM	2026.04	Arxiv	AR-VLM → block-diffusion VLM
Analyzing Diffusion and Autoregressive VLMs in Multimodal Embedding Space	2026.02	Arxiv	Embedding analysis
Dynin-Omni: Omnimodal Unified Large Diffusion Language Model	2026.03	Arxiv	Omnimodal
UAT: Unified Audio-Text Diffusion for Audio Generation, Editing, and Captioning	2026.06	Arxiv	Unified Audio-Text Diffusion for Audio Generation,
Efficient Reinforcement for Visual-Textual Thinking with Discrete Diffusion Model	2026.06	Arxiv	RL, dMLLM
PerceptionDLM: Parallel Region Perception with Multimodal Diffusion Language Models	2026.06	Arxiv	dMLLM
Concurrent Image Understanding and Generation: Self-Correcting Coupled Markov Jump Processes	2026.07	Arxiv	Training-free, Remasking
Does More Retrieved Evidence Help Visual Retrieval-Augmented Generation with Diffusion Language Models?	2026.08	Arxiv	Training-free, Retrieval

6.2 Vision-Language-Action (VLA)

Scope note: this section covers VLA models that use a diffusion/masked-diffusion language model as the backbone (dVLM-based VLA) or apply discrete diffusion as the action-decoding mechanism (not continuous diffusion action heads grafted onto an AR VLM). Pure continuous-diffusion-policy VLAs such as DiVLA (Wen et al., 2024), HybridVLA, and ProgressVLA are intentionally excluded because their language model is autoregressive — only the action head is diffusion-based.

(a) dVLM-backbone VLA — language backbone itself is a diffusion language model.

Paper Title	Year	Venue	Remark
LLaDA-VLA: Vision Language Diffusion Action Models	2025.09	Arxiv	First LLaDA(d-VLM)-based VLA
dVLA: Diffusion VLA with Multimodal Chain-of-Thought	2025.09	Arxiv	dLLM backbone + multimodal CoT
Dream-VLA: Open Vision-Language-Action Model with Diffusion Backbone	2025.12	Arxiv	dVLA from Dream-7B; first dLLM pretrained VLA
MMaDA-VLA: Large Diffusion VLA with Unified Multi-Modal Instruction and Generation	2026.03	Arxiv	Native discrete-diffusion VLA from MMaDA

(b) Discrete-diffusion action decoding — language backbone may still be AR-VLM, but action chunks are decoded via discrete diffusion. Closely tied to dLLM literature for inference techniques.

Paper Title	Year	Venue	Remark
Discrete Diffusion VLA: Action Decoding in VLA Policies	2025.08	ICML	Unified-transformer + discrete-diffusion actions
E0: Enhancing Generalization and Fine-Grained Control in VLA Models via Tweedie Discrete Diffusion	2025.11	Arxiv	AR-VLM backbone + Tweedie discrete diffusion on action tokens

6.3 Autonomous Driving / World Models

Scope note: works that apply discrete diffusion / masked-diffusion language modeling to driving trajectories, action codebooks, or tokenized world states. Continuous trajectory-diffusion planners (e.g., classical Diffusion Policy applied to driving) are out of scope.

Paper Title	Year	Venue	Remark
Copilot4D: Learning Unsupervised World Models for Autonomous Driving via Discrete Diffusion	2023.11	ICLR	Discrete diffusion on tokenized point-cloud world model
ReflectDrive: Discrete Diffusion for Reflective Vision-Language-Action Models in Autonomous Driving	2025.09	Arxiv	dLLM finetuned on discretized 2D driving space
Efficient and Explainable End-to-End Autonomous Driving via Masked Vision-Language-Action Diffusion	2026.02	Arxiv	Discrete action codebook + masked diffusion
Fast-dDrive: Efficient Block-Diffusion VLM for Autonomous Driving	2026.05	Arxiv	Block-diffusion VLA, speculative scaffold decoding

7. Agentic & Tool-Use dLLMs

New section — emerging line: how dLLMs behave as agents (planning, multi-turn, tool calling). Critical for connecting dLLMs to robotics and physical-AI agent stacks.

Paper Title	Year	Venue	Remark
The Bitter Lesson of Diffusion Language Models for Agentic Workflows: A Comprehensive Reality Check	2026.01	Arxiv	Embodied + tool-call eval
Agents of Diffusion: Enhancing Diffusion Language Models with Multi-Agent Reinforcement Learning for Structured Data Generation	2026.01	Arxiv	Multi-agent RL
DLLM Agent: See Farther, Run Faster	2026.02	Arxiv	dLLM-as-agent comparison

8. Theory, Guidance & Applications

8.1 Theory & Analysis

Paper Title	Year	Venue	Remark
Can Diffusion Model Achieve Better Performance in Text Generation? Bridging the Gap between Training and Inference!	2023.05	ACL Findings	<7B
TEncDM: Understanding the Properties of the Diffusion Model in the Space of Language Model Encodings	2024.02	AAAI	<7B
Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling	2024.10	ICLR	<7B
Theoretical Benefit and Limitation of Diffusion Language Model	2025.02	NeurIPS	TER vs SER analysis
Generalized Interpolating Discrete Diffusion (GIDD)	2025.03	ICML	Noising
Understanding the Quality-Diversity Trade-off in Diffusion Language Models	2025.03	ICML	Quality-Diversity Trade-off
Unifying Continuous and Discrete Text Diffusion with Non-simultaneous Diffusion Processes	2025.05	ACL	<7B
The Diffusion Duality	2025.06	ICML	<7B, Theoretical Duality
Your Absorbing Discrete Diffusion Secretly Models the Bayesian Posterior	2025.07	Arxiv	<7B
Time Is a Feature: Exploiting Temporal Dynamics in dLLMs	2025.08	Arxiv	Temporal focus
Diffusion LLMs Know the Answer Before Decoding	2025.08	Arxiv	Semantic focus
What Makes Diffusion Language Models Super Data Learners?	2025.10	Arxiv	Data efficiency
Why mask diffusion does not work	2025.10	Arxiv	Failure analysis
Empirical Analysis of Decoding Biases in Masked Diffusion Models	2025.10	Arxiv	Decoding Bias
Beyond Next-Token Prediction: A Performance Characterization of Diffusion versus Autoregressive Language Models	2025.10	Arxiv	Speed Analysis
On the Role of Discreteness in Diffusion LLMs	2025.12	Arxiv	Speed Analysis
ParallelBench: Understanding the Trade-offs of Parallel Decoding in Diffusion LLMs	2025.10	ICLR
Efficient Self-Evaluation for Diffusion Language Models via Sequence Regeneration	2026.03	ACL	Self-evaluation, Generalization analysis
On the Role of Discreteness in Diffusion LLMs	2025.12	Arxiv	Discreteness analysis
ParallelBench: Understanding the Trade-offs of Parallel Decoding in Diffusion LLMs	2025.10	ICLR	Benchmark
Diffusion Language Models are Super Data Learners	2025.11	Arxiv	Data learner analysis
Adaptation to Intrinsic Dependence in Diffusion Language Models	2026.02	Arxiv	Distribution-agnostic schedule theory
Confidence-Based Decoding is Provably Efficient for Diffusion Language Models	2026.03	Arxiv	First theory of confidence-based decoding
Why Diffusion Language Models Struggle with Truly Parallel (Non-Autoregressive) Decoding?	2026.02	Arxiv	AR-like decoding analysis, NAP approach
Characterizing Memorization in Diffusion Language Models: Generalized Extraction and Sampling Effects	2026.03	Arxiv	Memorization, privacy analysis
Skip to the Good Part: Representation Structure & Inference-Time Layer Skipping in Diffusion vs. Autoregressive LLMs	2026.03	Arxiv	Layer skipping, representation analysis
Autoregressive vs. Masked Diffusion Language Models: A Controlled Comparison	2026.03	Arxiv	Controlled AR vs MDM empirical study
Why Gaussian Diffusion Models Fail on Discrete Data?	2026.04	Arxiv	Multimodal sampling interval theory
Generative Frontiers: Why Evaluation Matters for Diffusion Language Models	2026.04	Arxiv	Evaluation methodology critique
Lost in Diffusion: Uncovering Hallucination Patterns and Failure Modes in Diffusion Large Language Models	2026.04	ACL Findings	Hallucination patterns analysis
Early Decisions Matter: Proximity Bias and Initial Trajectory Shaping in Non-Autoregressive Diffusion Language Models	2026.04	ICML	Proximity bias analysis
Measuring Temporal Linguistic Emergence in Diffusion Language Models	2026.04	Arxiv	Temporal probing, linguistic emergence
Language Diffusion Models are Associative Memories Capable of Retrieving Unseen Data	2026.04	Arxiv	Associative memory theory
Understanding and Accelerating the Training of Masked Diffusion Language Models	2026.05	Arxiv	Bell-shaped time sampling, training speed
Uncertainty Quantification for Large Language Diffusion Models	2026.05	Arxiv	UQ, hallucination detection for dLLMs
Continuous Language Diffusion as a Decoder-Interface Problem	2026.06	Arxiv	-
Neither Parallel Nor Sequential: How DiffusionGemma Actually Commits Tokens	2026.06	Arxiv	MoE
Diffusion Language Models: An Experimental Analysis	2026.06	Arxiv	Unmasking order
Understanding Parallel Samplers in Masked Diffusion via Random Walks on Graphs	2026.06	Arxiv	Unmasking order
When Top-1 Fails: Calibrating LoRA Monitors for Masked Diffusion LMs	2026.06	Arxiv	Calibrating LoRA Monitors for Masked Diffusion
Understanding Evaluation Illusion in Diffusion Large Language Models	2026.06	Arxiv	-
CaRE Compute-aware Remasking Evaluation Protocol for Masked Diffusion Language Models	2026.06	Arxiv	Remasking, Unmasking order
Where Quality Breaks in Compressed Short-Text Generation: Staged Bottleneck Localization	2026.07	FRUCT	Staged codec-vs-generation bottleneck diagnosis; project
Low Perplexity is Repetition: A One-Dimensional Self-Conditioning Attractor in Continuous Diffusion LMs	2026.07	Arxiv	A One-Dimensional Self-Conditioning Attractor in Continuous
Subliminal Clocks: Latent Time Modelling in Diffusion Language Models	2026.07	Arxiv	Latent Time Modelling in Diffusion Language
Accepted Prefixes Are Not All You Need: A Negative Result on PEFT-Based Block-Diffusion Drafting	2026.07	Arxiv	Speculative decoding
Induction in Both Directions: A Mechanistic Analysis of In-Context Learning in Masked Diffusion Language Models	2026.07	Arxiv	A Mechanistic Analysis of In-Context Learning
Beyond the Bidirectional Promise: Re-evaluating the Robustness of Diffusion Language Models	2026.07	Arxiv	Safety attack
Faster but Different: Diagnosing and Controlling Content Drift in Accelerated Multimodal Diffusion Language Models	2026.07	Arxiv	Training-free, KV cache
Answer First, Reason Later: When Commitment Order Costs Accuracy in Diffusion Language Models	2026.08	Arxiv	When Commitment Order Costs Accuracy in
Lost in Interpolation: Why Predictive Feedback Fails in Diffusion Language Models	2026.08	Arxiv	Why Predictive Feedback Fails in Diffusion
Scaling Inherently Interpretable Language Models	2026.08	Arxiv	-
Unsure but Certain: Uncovering the Representation-Confidence Gap in Diffusion Language Models	2026.08	Arxiv	Uncovering the Representation-Confidence Gap in Diffusion
Minimax Optimality of Score-Entropy Discrete Diffusion	2026.08	Arxiv	-
Conditional Total Correlation and the Serial Depth of Adaptive Parallel Sampling	2026.08	Arxiv	-

8.2 Guidance & Downstream Applications

Paper Title	Year	Venue	Remark
DiffusEmp: A Diffusion Model-Based Framework with Multi-Grained Control for Empathetic Response Generation	2023.06	ACL	Dialogue
DiffuDetox: A Mixed Diffusion Model for Text Detoxification	2023.06	ACL Findings	Detoxification
PoetryDiffusion: Towards Joint Semantic and Metrical Manipulation in Poetry Generation	2023.06	AAAI	Poetry Generation
ParaGuide: Guided Diffusion Paraphrasers for Plug-and-Play Textual Style Transfer	2023.08	AAAI	Text Style Transfer
P^3SUM: Preserving Author's Perspective in News Summarization with Diffusion Language Models	2023.11	NAACL	Summarization
DiffuCOMET: Contextual Commonsense Knowledge Diffusion	2024.02	ACL	Commonsense
DiffusionDialog: A Diffusion Model for Diverse Dialog Generation with Latent Space	2024.04	LREC-COLING	Dialogue
Diffusion Guided Language Modeling	2024.08	ACL Findings	Control
DiffLM: Controllable Synthetic Data Generation via Diffusion Language Models	2024.11	ACL Findings	Data Synthesis
Segment-Level Diffusion: A Framework for Controllable Long-Form Generation with Diffusion Language Models	2024.12	ACL	Text Segmentation
EdiText: Controllable Coarse-to-Fine Text Editing with Diffusion Language Models	2025.02	ACL	Text Editing
Constrained Discrete Diffusion	2025.03	NeurIPS	Constraint
Planning with Diffusion Models for Target-Oriented Dialogue Systems	2025.04	ACL	Dialogue
CtrlDiff: Boosting dLLMs with Dynamic Block Prediction	2025.05	Arxiv	Control
Diffusion vs. Autoregressive Language Models: A Text Embedding Perspective	2025.05	Arxiv	Embedding
DINGO: Constrained Inference for Diffusion LLMs	2025.05	Arxiv	Constrained Decoding
Inference-Time Scaling of Discrete Diffusion Models via Importance Weighting and Optimal Proposal Design	2025.05	ICLR	SMC test-time scaling
Mercury: Ultra-Fast Language Models Based on Diffusion	2025.06	Arxiv	Code
DiffuCoder: Improving Masked Diffusion for Code Generation	2025.06	Arxiv	Code
Unveiling the Potential of Diffusion Large Language Model in Controllable Generation	2025.07	Arxiv	Control
Arg-LLaDA: Argument Summarization via Large Language Diffusion Models and Sufficiency-Aware Refinement	2025.07	Arxiv	Summarization
Improving Text Style Transfer using Masked Diffusion Language Models with Inference-time Scaling	2025.08	Arxiv	Text Style Transfer
Seed Diffusion: Large-Scale dLLM with High-Speed Inference	2025.08	Arxiv	Code
TreeDiff: AST-Guided Code Generation with Diffusion LLMs	2025.08	Arxiv	Code (syntax-aware)
Beyond Autoregression: Empirical Study for Code Generation	2025.09	Arxiv	Code
Tree Reward-Aligned Search for TReASURe in Masked Diffusion Language Models	2025.09	Arxiv	Control
Syntax-Guided Diffusion Language Models with User-Integrated Personalization	2025.10	Arxiv	Personalization
TraceDet: Hallucination Detection from the Decoding Trace of Diffusion Large Language Models	2025.10	Arxiv	Hallucination
Don't Let It Fade: Preserving Edits via Token Timestep Allocation	2025.10	NeurIPS	Control
Diffusion Language Models for Speech Recognition	2026.04	Arxiv	ASR rescoring (MDLM/USDM)
CAGenMol: Condition-Aware Diffusion Language Model for Goal-Directed Molecular Generation	2026.04	Arxiv	Molecular generation
TabDLM: Free-Form Tabular Data Generation via Joint Numerical-Language Diffusion	2026.02	Arxiv	Tabular generation, masked diffusion
Adaptive Guidance for Retrieval-Augmented Masked Diffusion Models	2026.03	Arxiv	RAG, retrieval-prior conflict handling
DynHD: Hallucination Detection for Diffusion Large Language Models via Denoising Dynamics Deviation Learning	2026.03	EMNLP Findings	Hallucination detection
Unlocking Prompt Infilling Capability for Diffusion Language Models	2026.04	Arxiv	Prompt infilling via full-sequence masking
DiffuMask: Diffusion Language Model for Token-level Prompt Pruning	2026.04	Arxiv	Prompt compression
BiMol-Diff: A Unified Diffusion Framework for Molecular Generation and Captioning	2026.04	Arxiv	Molecule generation + captioning
HIVE: Hidden-Evidence Verification for Hallucination Detection in Diffusion Large Language Models	2026.04	Arxiv	Hallucination detection, denoising dynamics
Chainwash: Multi-Step Rewriting Attacks on Diffusion Language Model Watermarks	2026.05	Arxiv	Watermark attack, security
DiffRetriever: Parallel Representative Tokens for Retrieval with Diffusion Language Models	2026.05	Arxiv	Dense retrieval with dLLMs
Guidance Is Not a Hyperparameter: Learning Dynamic Control in Diffusion Language Models	2026.05	Arxiv	Dynamic CFG via RL
Steering Without Breaking: Mechanistically Informed Interventions for Discrete Diffusion Language Models	2026.05	Arxiv	Adaptive guidance schedule, SAE analysis
Constrained Code Generation with Discrete Diffusion	2026.05	Arxiv	Neurosymbolic constrained code generation
Prompt Compression in Diffusion Large Language Models: Evaluating LLMLingua-2 on LLaDA	2026.05	Arxiv	Prompt compression study
Machine Unlearning for Masked Diffusion Language Models	2026.05	Arxiv	MDU, unlearning framework
Knowledge Editing in Masked Diffusion Language Models	2026.06	Arxiv	Unmasking order, Knowledge editing
MaskForge: Structure-Aware Adaptive Attacks for Jailbreaking Diffusion Large Language Models	2026.06	Arxiv	Safety attack
Global Sketch-Based Watermarking for Diffusion Language Models	2026.06	Arxiv	Watermarking
Dynamic Infilling Anchors for Format-Constrained Generation in Diffusion Large Language Models	2026.06	ACL	Training-free
Self-Augmenting Retrieval for Diffusion Language Models	2026.06	ICML	Training-free, Serving
TimpaTeks: Automatic In-place Text Sequence Modification via Diffusion Language Model Steering	2026.06	Arxiv	Automatic In-place Text Sequence Modification via
Detect, Remask, Repair: Diffusion Editing for Faithful Summarization of Evolving Contexts	2026.06	Arxiv	Few-step, Remasking
TimeROME-DLM: Temporal Causal Tracing and Low-Rank Inference-Time Knowledge Editing for Masked Diffusion Language Models	2026.06	Arxiv	MoE, Training-free
Self-Generated Error Training for Token Editing in Diffusion Language Models	2026.06	Arxiv	-
TAG-DLM: Diffusion Language Models for Text-Attributed Graph Learning	2026.06	Arxiv	Diffusion Language Models for Text-Attributed Graph
TRE: Training-Free Hallucination Detection for Diffusion Language Models	2026.06	Arxiv	Training-free, Hallucination
Diffusion-GR2: Diffusion Generative Reasoning Re-ranker	2026.07	Arxiv	Distillation, Serving
Discrete Diffusion Language Models for Interactive Radiology Report Drafting	2026.07	Arxiv	MoE, Clinical
Constrained Decoding for Diffusion Language Models via Efficient Inference over Finite Automata	2026.07	Arxiv	Remasking, Block diffusion
Audio-Native Speech Recognition with a Frozen Discrete-Diffusion Language Model	2026.07	Arxiv	MoE
Diffusion Language Model for Recommendation	2026.07	Arxiv	-
Exploring More to Solve More: Boosting Diversity in Text Diffusion Models via Entropy-Based Guidance	2026.07	Arxiv	Training-free
DeMTS: Denoising Trajectories as Multivariate Time Series for Hallucination Detection in Diffusion Language Models	2026.07	Arxiv	Hallucination
EchoChange: A Diffusion Language Model with Dual Pass Remasking for Factual Remote Sensing Disaster Change Captioning	2026.08	Arxiv	Remasking, dMLLM
Stoicheia: Character-Level Masked Diffusion for Ancient Greek Textual Restoration, Parsing, and Metrical Scansion	2026.08	Arxiv	Character-Level Masked Diffusion for Ancient Greek
Diffusion LLMs as Targets and Adversaries: Mechanistic Safety Exploits	2026.08	Arxiv	Safety attack
Commitment Before Realization: When Classifier-Free Guidance Becomes Unnecessary in Masked Diffusion Language Models	2026.08	Arxiv	When Classifier-Free Guidance Becomes Unnecessary in
Diffuse to Compress: Leveraging Diffusion LMs for Lossless Compression	2026.08	Arxiv	Serving, Compression
Discrete Diffusion Inference-Time Control with Nested Sequential Monte Carlo	2026.08	Arxiv	-
SAC-Copula: Quality-Preserving Watermarking for Diffusion Language Models via Smooth Correlated Gumbel Fields	2026.08	EMNLP Findings	Watermarking, Unmasking order
Length-Adaptive Decoding for Masked Diffusion Machine Translation	2026.08	EMNLP	Training-free, Unmasking order
DRRG: A Discrete Diffusion Framework for Radiology Report Generation	2026.08	Arxiv	Clinical

9. Seminal Diffusion Papers

Paper Title	Year	Venue	Remark
Deep Unsupervised Learning using Nonequilibrium Thermodynamics	2015.03	ICML	Formulation
Denoising Diffusion Probabilistic Models (DDPM)	2020.06	NeurIPS	-
Denoising Diffusion Implicit Models (DDIM)	2020.10	ICLR	-
Score-Based Generative Modeling through SDEs	2020.11	ICLR	-
Diffusion Models Beat GANs on Image Synthesis	2021.05	NeurIPS	CG
Structured Denoising Diffusion in Discrete State-Spaces (D3PM)	2021.07	NeurIPS	Discrete
Vector Quantized Diffusion Model (VQ-Diffusion)	2021.11	CVPR	VQ
High-Resolution Image Synthesis with Latent Diffusion (LDM)	2021.12	CVPR	-
Progressive Distillation for Fast Sampling	2022.02	ICLR	Distillation
DPM-Solver: Fast ODE Solver for Sampling	2022.06	NeurIPS	-
Classifier-Free Diffusion Guidance	2022.07	NeurIPS	CFG
Analog Bits: Generating Discrete Data using Diffusion	2022.08	ICLR	Self-conditioning
Scalable Diffusion Models with Transformers (DiT)	2022.12	ICCV	Scalable focus
Consistency Models	2023.03	ICML	-

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Maintainers: jake630@snu.ac.kr / wjk9904@snu.ac.kr
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