Discrete Forcing: Infusing Discrete Guidance into Continuous Denoising for Few-Step Action Experts

arXiv:2609.39526 · cs.RO · Submitted 2026-09-30 · Read on arXiv

cs.RO

Submitted: 2026-09-30

Updated: 2026-09-30

Terminology

• Benchmark — 15× in this paper · explained in 2 episodes
• Ablation — 7× in this paper · explained in 1 episode
• Consistency — 7× in this paper · explained in 3 episodes
• Distillation — 6× in this paper · explained in 2 episodes
• Action Space — 5× in this paper · explained in 1 episode
• Foundation Model — 5× in this paper · explained in 3 episodes
• Transformer — 5× in this paper · explained in 2 episodes
• Discrete Forcing Expert — 4× in this paper
• Generalization — 4× in this paper · explained in 13 episodes
• Alignment — 3× in this paper · explained in 1 episode
• Ablation Studies — 2× in this paper · explained in 1 episode
• Action Chunking — 2× in this paper · explained in 1 episode
• Action Flow — 2× in this paper · explained in 1 episode
• Consistency Distillation — 2× in this paper · explained in 2 episodes
• Diffusion Model — 2× in this paper · explained in 8 episodes
• Diffusion Models — 2× in this paper · explained in 6 episodes
• Diffusion Process — 2× in this paper · explained in 2 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Flow Matching — 2× in this paper · explained in 8 episodes
• Grounding — 2× in this paper · explained in 3 episodes
• Number of Function Evaluations — 2× in this paper
• Visual Grounding — 2× in this paper · explained in 2 episodes
• Benchmarking — 1× in this paper · explained in 3 episodes
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Distribution Matching — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Few-Shot Learning — 1× in this paper · explained in 4 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Latent Dynamics — 1× in this paper · explained in 2 episodes
• Overview of the Discrete Forcing — 1× in this paper
• Representation Learning — 1× in this paper · explained in 2 episodes
• Tokenization — 1× in this paper · explained in 2 episodes
• VLA Models — 1× in this paper · explained in 3 episodes
• Vision-Language-Action (VLA) Models — 1× in this paper · explained in 2 episodes
• World Model — 1× in this paper · explained in 7 episodes

Sources

• Latent Forcing: Reordering the Diffusion Trajectory for Pixel-Space Image Generation
• GR00T N1: An Open Foundation Model for Generalist Humanoid Robots
• $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control
• RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control
• Unified Diffusion VLA: Vision-Language-Action Model via Joint Discrete Denoising Diffusion Process
• DFM-VLA: Iterative Action Refinement for Robot Manipulation via Discrete Flow Matching
• RoboTwin 2.0: A Scalable Data Generator and Benchmark with Strong Domain Randomization for Robust Bimanual Robotic Manipulation
• StarVLA: A Lego-like Codebase for Vision-Language-Action Model Developing
• ActionCodec: What Makes for Good Action Tokenizers
• Knowledge Insulating Vision-Language-Action Models: Train Fast, Run Fast, Generalize Better
• CF-VLA: Efficient Coarse-to-Fine Action Generation for Vision-Language-Action Policies
• OpenVLA: An Open-Source Vision-Language-Action Model
• Fine-Tuning Vision-Language-Action Models: Optimizing Speed and Success
• MolmoAct: Action Reasoning Models that can Reason in Space
• RoboMemArena: A Comprehensive and Challenging Robotic Memory Benchmark
• Causal World Modeling for Robot Control
• LangForce: Bayesian Decomposition of Vision Language Action Models via Latent Action Queries
• Discrete Diffusion VLA: Bringing Discrete Diffusion to Action Decoding in Vision-Language-Action Policies
• OAT: Ordered Action Tokenization
• HybridVLA: Collaborative Diffusion and Autoregression in a Unified Vision-Language-Action Model

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