mlsanityData to 14 Oct 2026

MetaVLA: Unified Meta Co-training For Efficient Embodied Adaption

arXiv 2510.05580 ↗First posted 7 Oct 2025cs.AI cs.ROcited by 5

On the map: Vision-language-action models → Reasoning and chain-of-thought in VLA

Abstract (arXiv)

Vision-Language-Action (VLA) models show promise in embodied reasoning, yet remain far from true generalists-they often require task-specific fine-tuning, incur high compute costs, and generalize poorly to unseen tasks. We propose MetaVLA, a unified, backbone-agnostic post-training framework for efficient and scalable alignment. MetaVLA introduces Context-Aware Meta Co-Training, which consolidates diverse target tasks into a single fine-tuning stage while leveraging structurally diverse auxiliary tasks to improve in-domain generalization. Unlike naive multi-task SFT, MetaVLA integrates a lightweight meta-learning mechanism-derived from Attentive Neural Processes-to enable rapid adaptation from diverse contexts with minimal architectural change or inference overhead. On the LIBERO benchmark, MetaVLA with six auxiliary tasks outperforms OpenVLA by up to 8.0% on long-horizon tasks, reduces training steps from 240K to 75K, and cuts GPU time by ~76%. These results show that scalable, low-resource post-training is achievable-paving the way toward general-purpose embodied agents. Code will be available.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Placed in Reasoning and chain-of-thought in VLA, one of 13 directions in Vision-language-action models. Builds on 33 of its 47 references that are in the map. First posted on arXiv 7 Oct 2025.

Builds on

33 of 47 references.

Closest ancestors · 3

Same direction, newest first

  1. 2025ThinkAct: Vision-Language-Action Reasoning via Reinforced Visual Latent Planning22 Jul
  2. 2025OneTwoVLA: A Unified Vision-Language-Action Model with Adaptive Reasoning17 May
  3. 2025CoT-VLA: Visual Chain-of-Thought Reasoning for Vision-Language-Action Models27 Mar

Other references · 30

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,380
  3. 2017Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networkscited by 4,897
  4. 2023RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Controlcited by 3,080
  5. 2024OpenVLA: An Open-Source Vision-Language-Action Modelcited by 2,887
  6. 2023Diffusion Policy: Visuomotor Policy Learning via Action Diffusioncited by 2,838
  7. 2022RT-1: Robotics Transformer for Real-World Control at Scalecited by 2,061
  8. 2025π0.5: a Vision-Language-Action Model with Open-World Generalizationcited by 1,761
  9. 2024Octo: An Open-Source Generalist Robot Policycited by 1,484
  10. 2023LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learningcited by 1,410
  11. 2025GR00T N1: An Open Foundation Model for Generalist Humanoid Robotscited by 1,225
  12. 2017A Survey on Multi-Task Learningcited by 840
18 more
  1. 2025FAST: Efficient Action Tokenization for Vision-Language-Action Modelscited by 665
  2. 2020Multi-Task Learning with Deep Neural Networks: A Surveycited by 375
  3. 2024TraceVLA: Visual Trace Prompting Enhances Spatial-Temporal Awareness for Generalist Robotic Policiescited by 304
  4. 2019Attentive Neural Processescited by 283
  5. 2024A Survey on Vision-Language-Action Models for Embodied AIcited by 279
  6. 2023Any-point Trajectory Modeling for Policy Learningcited by 215
  7. 2017Multi-task Self-Supervised Visual Learningcited by 200
  8. 2021Muppet: Massive Multi-task Representations with Pre-Finetuningcited by 192
  9. 2019AdaShare: Learning What To Share For Efficient Deep Multi-Task Learningcited by 160
  10. 2025Knowledge Insulating Vision-Language-Action Models: Train Fast, Run Fast, Generalize Bettercited by 146
  11. 2025NORA: A Small Open-Sourced Generalist Vision Language Action Model for Embodied Taskscited by 127
  12. 2024GRAPE: Generalizing Robot Policy via Preference Alignmentcited by 109
  13. 2025FLOWER: Democratizing Generalist Robot Policies with Efficient Vision-Language-Action Flow Policiescited by 57
  14. 2025OTTER: A Vision-Language-Action Model with Text-Aware Visual Feature Extractioncited by 54
  15. 2025Vision Language Action Models in Robotic Manipulation: A Systematic Reviewcited by 38
  16. 2025Exploring the Limits of Vision-Language-Action Manipulations in Cross-task Generalizationcited by 33
  17. 2025Multi-Task Reinforcement Learning Enables Parameter Scalingcited by 8
  18. 2025Benchmarking Vision, Language, & Action Models in Procedurally Generated, Open Ended Action Environmentscited by 6

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 5.

5 papers.

  1. 2026Information-Theoretic Constraints for Continual Vision-Language-Action Alignmentcited by 3
  2. 2026Robotic Policy Adaptation via Weight-Space Meta-Learningcited by 1
  3. 2026Test-Time Perturbation Learning with Delayed Feedback for Vision-Language-Action Modelscited by 0
  4. 2026PAPO-VLA: Planning-Aware Policy Optimization for Vision-Language-Action Modelscited by 0
  5. 2026Triggering Generalist Reasoning via Predictive Uncertainty for Dual-System VLAcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2026DM0: An Embodied-Native Vision-Language-Action Model towards Physical AI
  2. 2026StarVLA: A Lego-like Codebase for Vision-Language-Action Model Developing
  3. 2026GigaBrain-0.7: Scaling Embodied Foundation Models to Emergent Capabilities with a Three-System Architecture
  4. 2025EfficientVLA: Training-Free Acceleration and Compression for Vision-Language-Action Models
  5. 2025DualVLA: Building a Generalizable Embodied Agent via Partial Decoupling of Reasoning and Action
  6. 2026EmbodiedMidtrain: Bridging the Gap between Vision-Language Models and Vision-Language-Action Models via Mid-training
  7. 2025InstructVLA: Vision-Language-Action Instruction Tuning from Understanding to Manipulation
  8. 2025Igniting VLMs toward the Embodied Space