mlsanityData to 7 Oct 2026

RA-VLA: Retrieval-Augmented VLA for Test-Time Adaptation

arXiv 2608.25585 ↗First posted 26 Aug 2026cs.ROcited by 0

On the map: Vision-language-action models → Reinforcement learning and post-training

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Abstract (arXiv)

Vision-Language-Action (VLA) models provide a versatile foundation for general robotic manipulation, yet they exhibit significant brittleness when confronted with novel task distributions. While In-Context Imitation Learning (ICIL) offers a training-free alternative, existing frameworks suffer from an adaptation bottleneck that hinders the effective translation of expert context to executable actions. This failure originates from superficial retrieval mechanisms and an inherent behavioral inertia that anchors the policy to its pre-trained priors. To address these limitations, we present RA-VLA, a retrieval-augmented VLA framework that integrates behavior-aligned context retrieval with a grounded execution pipeline. By enforcing faithful adherence to functional cues within a scalable architecture, RA-VLA facilitates seamless task adaptation while preserving inference efficiency. Our empirical evaluations across the LIBERO benchmark and a real-world UR5e environment demonstrate that RA-VLA achieves superior success rates and computational efficiency, establishing a robust framework for training-free robotic adaptation.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Reinforcement learning and post-training, one of 13 directions in Vision-language-action models. Builds on 36 of its 39 references that are in the map. First posted on arXiv 26 Aug 2026.

Builds on

36 of 39 references.

References · 36

  1. 2017Attention Is All You Needcited by 59,932
  2. 2020A Simple Framework for Contrastive Learning of Visual Representationscited by 11,979
  3. 2022Scalable Diffusion Models with Transformerscited by 5,931
  4. 2023RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Controlcited by 2,993
  5. 2024OpenVLA: An Open-Source Vision-Language-Action Modelcited by 2,777
  6. 2024π0: A Vision-Language-Action Flow Model for General Robot Controlcited by 2,297
  7. 2025π0.5: a Vision-Language-Action Model with Open-World Generalizationcited by 1,653
  8. 2023Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardwarecited by 1,490
  9. 2023LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learningcited by 1,338
  10. 2025GR00T N1: An Open Foundation Model for Generalist Humanoid Robotscited by 1,167
  11. 2025SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Featurescited by 1,127
  12. 2025Fine-Tuning Vision-Language-Action Models: Optimizing Speed and Successcited by 844
24 more
  1. 2024DROID: A Large-Scale In-The-Wild Robot Manipulation Datasetcited by 801
  2. 2025FAST: Efficient Action Tokenization for Vision-Language-Action Modelscited by 643
  3. 2023BridgeData V2: A Dataset for Robot Learning at Scalecited by 634
  4. 2024CogACT: A Foundational Vision-Language-Action Model for Synergizing Cognition and Action in Robotic Manipulationcited by 411
  5. 2024Prismatic VLMs: Investigating the Design Space of Visually-Conditioned Language Modelscited by 336
  6. 2023Trusting Your Evidence: Hallucinate Less with Context-aware Decodingcited by 319
  7. 2025LIBERO-Plus: In-depth Robustness Analysis of Vision-Language-Action Modelscited by 278
  8. 2017One-Shot Imitation Learningcited by 232
  9. 2024PaliGemma 2: A Family of Versatile VLMs for Transfercited by 204
  10. 2023GELLO: A General, Low-Cost, and Intuitive Teleoperation Framework for Robot Manipulatorscited by 180
  11. 2024Make Your LLM Fully Utilize the Contextcited by 118
  12. 2025SAFE: Multitask Failure Detection for Vision-Language-Action Modelscited by 74
  13. 2024Keypoint Action Tokens Enable In-Context Imitation Learning in Roboticscited by 71
  14. 2024In-Context Imitation Learning via Next-Token Predictioncited by 65
  15. 2025Eagle 2.5: Boosting Long-Context Post-Training for Frontier Vision-Language Modelscited by 62
  16. 2024Enhancing Contextual Understanding in Large Language Models through Contrastive Decodingcited by 49
  17. 2024Instant Policy: In-Context Imitation Learning via Graph Diffusioncited by 38
  18. 2024Retrieval-Augmented Embodied Agentscited by 30
  19. 2025From Intention to Execution: Probing the Generalization Boundaries of Vision-Language-Action Modelscited by 23
  20. 2023One-Shot Imitation Learning: A Pose Estimation Perspectivecited by 21
  21. 2025RICL: Adding In-Context Adaptability to Pre-Trained Vision-Language-Action Modelscited by 19
  22. 2023One-shot Imitation Learning via Interaction Warpingcited by 16
  23. 2025More is not always better? Enhancing Many-Shot In-Context Learning with Differentiated and Reweighting Objectivescited by 12
  24. 2025RoboSSM: Scalable In-context Imitation Learning via State-Space Modelscited by 5

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  1. 2026AC^2-VLA: Action-Context-Aware Adaptive Computation in Vision-Language-Action Models for Efficient Robotic Manipulation
  2. 2026VLA-REPLICA: A Low-Cost, Reproducible Benchmark for Real-World Evaluation of Vision-Language-Action Models
  3. 2026Agentic-VLA: Efficient Online Adaptation for Vision-Language-Action Models
  4. 2026When Does Retrieval Help? A Study of In-Context Adaptation in Vision-Language-Action Models
  5. 2026Retrieve-then-Steer: Online Success Memory for Test-Time Adaptation of Generative VLAs
  6. 2026Hierarchical Skill Retrieval for Data-Efficient Adaptation of Vision-Language-Action Models
  7. 2026PriorVLA: Prior-Preserving Adaptation for Vision-Language-Action Models
  8. 2025MoS-VLA: A Vision-Language-Action Model with One-Shot Skill Adaptation