Cover Image

RICL: Adding In-Context Adaptability to Pre-Trained Vision-Language-Action Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Sridhar, Kaustubh, Dutta, Souradeep, Jayaraman, Dinesh, Lee, Insup
Format:	Preprint
Published:	2025
Subjects:	Robotics Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Memory-Consistent Neural Networks for Imitation Learning
by: Sridhar, Kaustubh, et al.
Published: (2023)

REGENT: A Retrieval-Augmented Generalist Agent That Can Act In-Context in New Environments
by: Sridhar, Kaustubh, et al.
Published: (2024)

Improving Pre-Trained Vision-Language-Action Policies with Model-Based Search
by: Neary, Cyrus, et al.
Published: (2025)

Distributionally Robust Statistical Verification with Imprecise Neural Networks
by: Dutta, Souradeep, et al.
Published: (2023)

VLMgineer: Vision Language Models as Robotic Toolsmiths
by: Gao, George Jiayuan, et al.
Published: (2025)

Composing Pre-Trained Object-Centric Representations for Robotics From "What" and "Where" Foundation Models
by: Shi, Junyao, et al.
Published: (2024)

ContextVLA: Vision-Language-Action Model with Amortized Multi-Frame Context
by: Jang, Huiwon, et al.
Published: (2025)

Vision Language Models are In-Context Value Learners
by: Ma, Yecheng Jason, et al.
Published: (2024)

ALOE: Action-Level Off-Policy Evaluation for Vision-Language-Action Model Post-Training
by: Yang, Rushuai, et al.
Published: (2026)

Action Hallucination in Generative Vision-Language-Action Models
by: Soh, Harold, et al.
Published: (2026)

Maestro: Orchestrating Robotics Modules with Vision-Language Models for Zero-Shot Generalist Robots
by: Shi, Junyao, et al.
Published: (2025)

NORA-1.5: A Vision-Language-Action Model Trained using World Model- and Action-based Preference Rewards
by: Hung, Chia-Yu, et al.
Published: (2025)

LAP: Language-Action Pre-Training Enables Zero-shot Cross-Embodiment Transfer
by: Zha, Lihan, et al.
Published: (2026)

Bring My Cup! Personalizing Vision-Language-Action Models with Visual Attentive Prompting
by: Lee, Sangoh, et al.
Published: (2025)

Hierarchical Vision Language Action Model Using Success and Failure Demonstrations
by: Park, Jeongeun, et al.
Published: (2025)

ActionFlow: A Pipelined Action Acceleration for Vision Language Models on Edge
by: Dai, Yuntao, et al.
Published: (2025)

AR-VLA: True Autoregressive Action Expert for Vision-Language-Action Models
by: Hu, Yutong, et al.
Published: (2026)

Adversarial Attacks on Robotic Vision Language Action Models
by: Jones, Eliot Krzysztof, et al.
Published: (2025)

Survey of Vision-Language-Action Models for Embodied Manipulation
by: Li, Haoran, et al.
Published: (2025)

Eurekaverse: Environment Curriculum Generation via Large Language Models
by: Liang, William, et al.
Published: (2024)

DexHiL: A Human-in-the-Loop Framework for Vision-Language-Action Model Post-Training in Dexterous Manipulation
by: Han, Yifan, et al.
Published: (2026)

Adaptive Capacity Allocation for Vision Language Action Fine-tuning
by: Kim, Donghoon, et al.
Published: (2026)

Developing Vision-Language-Action Model from Egocentric Videos
by: Yoshida, Tomoya, et al.
Published: (2025)

Emergence of Human to Robot Transfer in Vision-Language-Action Models
by: Kareer, Simar, et al.
Published: (2025)

SAFE: Multitask Failure Detection for Vision-Language-Action Models
by: Gu, Qiao, et al.
Published: (2025)

Continually Evolving Skill Knowledge in Vision Language Action Model
by: Wu, Yuxuan, et al.
Published: (2025)

Exploring the Adversarial Vulnerabilities of Vision-Language-Action Models in Robotics
by: Wang, Taowen, et al.
Published: (2024)

Toward Accurate Long-Horizon Robotic Manipulation: Language-to-Action with Foundation Models via Scene Graphs
by: Dinesh, Sushil Samuel, et al.
Published: (2025)

Privileged Sensing Scaffolds Reinforcement Learning
by: Hu, Edward S., et al.
Published: (2024)

Hybrid Training for Vision-Language-Action Models
by: Mazzaglia, Pietro, et al.
Published: (2025)

WMPO: World Model-based Policy Optimization for Vision-Language-Action Models
by: Zhu, Fangqi, et al.
Published: (2025)

Experiences from Benchmarking Vision-Language-Action Models for Robotic Manipulation
by: Zhang, Yihao, et al.
Published: (2025)

10 Open Challenges Steering the Future of Vision-Language-Action Models
by: Poria, Soujanya, et al.
Published: (2025)

Pure Vision Language Action (VLA) Models: A Comprehensive Survey
by: Zhang, Dapeng, et al.
Published: (2025)

Do What? Teaching Vision-Language-Action Models to Reject the Impossible
by: Hsieh, Wen-Han, et al.
Published: (2025)

V-VLAPS: Value-Guided Planning for Vision-Language-Action Models
by: Ren, Ke, et al.
Published: (2026)

Towards Backdoor-Based Ownership Verification for Vision-Language-Action Models
by: Sun, Ming, et al.
Published: (2026)

Action-aware Dynamic Pruning for Efficient Vision-Language-Action Manipulation
by: Pei, Xiaohuan, et al.
Published: (2025)

KineVLA: Towards Kinematics-Aware Vision-Language-Action Models with Bi-Level Action Decomposition
by: Han, Gaoge, et al.
Published: (2026)

RLRC: Reinforcement Learning-based Recovery for Compressed Vision-Language-Action Models
by: Chen, Yuxuan, et al.
Published: (2025)