MMaDA-VLA: Large Diffusion Vision-Language-Action Model with Unified Multi-Modal Instruction and Generation
On the map: Vision-language-action models → Efficient VLA inference and adaptation
Abstract (arXiv)
Vision-Language-Action (VLA) models map visual observations and natural-language instructions to robot actions; however, hierarchical and autoregressive paradigms often incur architectural overhead, accumulate long-horizon errors, and require auxiliary modules to capture environment dynamics. To this end, we present MMaDA-VLA, a fully native, pretrained discrete diffusion VLA that unifies multi-modal understanding and generation. Specifically, MMaDA-VLA uses a shared discrete token space to jointly denoise a future goal observation and an action chunk, grounding actions in predicted visual outcomes without an auxiliary world model. In this way, parallel, order-free refinement improves long-horizon consistency. Extensive experiments and comprehensive analyses demonstrate that MMaDA-VLA achieves an average success rate of 98.0% on LIBERO and an average successful sequence length of 4.78 on CALVIN, while performing strongly in real-world settings. The project page is available at https://yliu-cs.github.io/MMaDA-VLA.
Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). Placed in Efficient VLA inference and adaptation, one of 13 directions in Vision-language-action models. Builds on 95 of its 109 references that are in the map. First posted on arXiv 26 Mar 2026.
Builds on
95 of 109 references.
Closest ancestors · 8
Same direction, newest first
- 2025Unified Diffusion VLA: Vision-Language-Action Model via Joint Discrete Denoising Diffusion Process3 Nov
- 2025OmniSAT: Compact Action Token, Faster Auto Regression8 Oct
- 2025Discrete Diffusion VLA: Bringing Discrete Diffusion to Action Decoding in Vision-Language-Action Policies27 Aug
- 2025VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers1 Jul
- 2025CEED-VLA: Consistency Vision-Language-Action Model with Early-Exit Decoding16 Jun
- 2025PD-VLA: Accelerating Vision-Language-Action Model Integrated with Action Chunking via Parallel Decoding4 Mar
- 2025FAST: Efficient Action Tokenization for Vision-Language-Action Models16 Jan
- 2024Diffusion Transformer Policy21 Oct
Other references · 87
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
- 2020Language Models are Few-Shot Learnerscited by 32,199
- 2020Denoising Diffusion Probabilistic Modelscited by 20,851
- 2023LLaMA: Open and Efficient Foundation Language Modelscited by 13,958
- 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,185
- 2023Adding Conditional Control to Text-to-Image Diffusion Modelscited by 5,466
- 2023Qwen Technical Reportcited by 3,273
- 2023RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Controlcited by 2,993
- 2024OpenVLA: An Open-Source Vision-Language-Action Modelcited by 2,777
- 2023Diffusion Policy: Visuomotor Policy Learning via Action Diffusioncited by 2,730
- 2024π0: A Vision-Language-Action Flow Model for General Robot Controlcited by 2,297
- 2022RT-1: Robotics Transformer for Real-World Control at Scalecited by 2,007
38 more
- 2025π0.5: a Vision-Language-Action Model with Open-World Generalizationcited by 1,653
- 2024Octo: An Open-Source Generalist Robot Policycited by 1,427
- 2023LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learningcited by 1,338
- 2019ZeRO: Memory Optimizations Toward Training Trillion Parameter Modelscited by 1,278
- 2025GR00T N1: An Open Foundation Model for Generalist Humanoid Robotscited by 1,167
- 2022MaskGIT: Masked Generative Image Transformercited by 1,082
- 2025Large Language Diffusion Modelscited by 872
- 2025Fine-Tuning Vision-Language-Action Models: Optimizing Speed and Successcited by 844
- 2024DROID: A Large-Scale In-The-Wild Robot Manipulation Datasetcited by 801
- 2025V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planningcited by 738
- 2024Show-o: One Single Transformer to Unify Multimodal Understanding and Generationcited by 734
- 2018QT-Opt: Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulationcited by 730
- 2024Genie: Generative Interactive Environmentscited by 706
- 2023BridgeData V2: A Dataset for Robot Learning at Scalecited by 634
- 2023Language Model Beats Diffusion -- Tokenizer is Key to Visual Generationcited by 633
- 2021CALVIN: A Benchmark for Language-Conditioned Policy Learning for Long-Horizon Robot Manipulation Taskscited by 564
- 2022BC-Z: Zero-Shot Task Generalization with Robotic Imitation Learningcited by 517
- 2025Dream 7B: Diffusion Large Language Modelscited by 515
- 2023Learning Universal Policies via Text-Guided Video Generationcited by 506
- 2025SpatialVLA: Exploring Spatial Representations for Visual-Language-Action Modelcited by 502
- 2025CoT-VLA: Visual Chain-of-Thought Reasoning for Vision-Language-Action Modelscited by 440
- 2023The Reversal Curse: LLMs trained on "A is B" fail to learn "B is A"cited by 399
- 2025UniVLA: Learning to Act Anywhere with Task-centric Latent Actionscited by 386
- 2023Unleashing Large-Scale Video Generative Pre-training for Visual Robot Manipulationcited by 353
- 2025WorldVLA: Towards Autoregressive Action World Modelcited by 351
- 2023Vision-Language Foundation Models as Effective Robot Imitatorscited by 344
- 2024Video Prediction Policy: A Generalist Robot Policy with Predictive Visual Representationscited by 279
- 2025LLaDA 1.5: Variance-Reduced Preference Optimization for Large Language Diffusion Modelscited by 273
- 2023Zero-Shot Robotic Manipulation with Pretrained Image-Editing Diffusion Modelscited by 264
- 2025MMaDA: Multimodal Large Diffusion Language Modelscited by 241
- 2022Interactive Language: Talking to Robots in Real Timecited by 217
- 2025DreamVLA: A Vision-Language-Action Model Dreamed with Comprehensive World Knowledgecited by 203
- 2018RoboTurk: A Crowdsourcing Platform for Robotic Skill Learning through Imitationcited by 202
- 2025MemoryVLA: Perceptual-Cognitive Memory in Vision-Language-Action Models for Robotic Manipulationcited by 183
- 2025dLLM-Cache: Accelerating Diffusion Large Language Models with Adaptive Cachingcited by 168
- 2024Predictive Inverse Dynamics Models are Scalable Learners for Robotic Manipulationcited by 159
- 2023StyleTTS 2: Towards Human-Level Text-to-Speech through Style Diffusion and Adversarial Training with Large Speech Language Modelscited by 148
- 2025LLaDA-V: Large Language Diffusion Models with Visual Instruction Tuningcited by 145
50 most cited of 87 All 87 (JSON)
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Citing papers per year: 2026: 10.
10 papers.
- 2026DMax: Aggressive Parallel Decoding for dLLMscited by 14
- 2026Human Cognition in Machines: A Unified Perspective of World Modelscited by 5
- 2026TACG: Trajectory-Aware Commit Gating for Diffusion Language Model Decodingcited by 2
- 2026dVLA-RL: Reinforcement Learning over Denoising Trajectories for Discrete Diffusion Vision-Language-Action Modelscited by 1
- 2026SA-VLA: State-aware tokenizer for improving Vision-Language-Action Models' performancecited by 1
- 2026WorldDiT: A Unified Diffusion Architecture for World and Action Modelingcited by 0
- 2026WAM-Diff2: Hierarchical AR-to-Diffusion Distillation for Highly Efficient Autonomous Driving VLAcited by 0
- 2026Diffusion Language Models for Mobile Edge Agentic AI: Foundations, Applications, and Challengescited by 0
- 2026Dynin-Robotics: Omnimodal Unified Diffusion Vision-Language-Action Modelcited by 0
- 2026KerColle: Unlocking Fine-Grained GPU Concurrency in Vision-Language-Action Modelscited by 0
- 2026KerColle: Unlocking Fine-Grained GPU Concurrency in Vision-Language-Action Models16 Sep 2026
- 2026Dynin-Robotics: Omnimodal Unified Diffusion Vision-Language-Action Model11 Sep 2026
- 2026Diffusion Language Models for Mobile Edge Agentic AI: Foundations, Applications, and Challenges4 Sep 2026
- 2026WAM-Diff2: Hierarchical AR-to-Diffusion Distillation for Highly Efficient Autonomous Driving VLA2 Aug 2026
- 2026WorldDiT: A Unified Diffusion Architecture for World and Action Modeling27 Jul 2026
- 2026TACG: Trajectory-Aware Commit Gating for Diffusion Language Model Decoding3 Jul 2026
- 2026SA-VLA: State-aware tokenizer for improving Vision-Language-Action Models' performance29 Jun 2026
- 2026dVLA-RL: Reinforcement Learning over Denoising Trajectories for Discrete Diffusion Vision-Language-Action Models22 Jun 2026
- 2026Human Cognition in Machines: A Unified Perspective of World Models17 Apr 2026
- 2026DMax: Aggressive Parallel Decoding for dLLMs9 Apr 2026
Similar, not cited
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- 2025dVLA: Diffusion Vision-Language-Action Model with Multimodal Chain-of-Thought
- 2025E0: Enhancing Generalization and Fine-Grained Control in VLA Models via Tweedie Discrete Diffusion
- 2025Dream-VL & Dream-VLA: Open Vision-Language and Vision-Language-Action Models with Diffusion Language Model Backbone
- 2025HybridVLA: Collaborative Diffusion and Autoregression in a Unified Vision-Language-Action Model
- 2025Evo-1: Lightweight Vision-Language-Action Model with Preserved Semantic Alignment
- 2026StairVLA: Stage-Aware Hierarchical Action Generation for Vision-Language-Action Models
- 2026Rethinking the Practicality of Vision-language-action Model: A Comprehensive Benchmark and An Improved Baseline
- 2025DexVLA: Vision-Language Model with Plug-In Diffusion Expert for General Robot Control