When Does Retrieval Help? A Study of In-Context Adaptation in Vision-Language-Action Models
cs.LG
Submitted: 2026-10-04
Updated: 2026-10-04
Terminology
Sources
- $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control
- OpenVLA: An Open-Source Vision-Language-Action Model
- FAST: Efficient Action Tokenization for Vision-Language-Action Models
- Octo: An Open-Source Generalist Robot Policy
- RoboCat: A Self-Improving Generalist Agent for Robotic Manipulation
- RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control
- Gemini Robotics: Bringing AI into the Physical World
- GPT-4 Technical Report
- Gemini: A Family of Highly Capable Multimodal Models
- Enhancing LLM Safety via Constrained Direct Preference Optimization
- Risk-Conditioned Fine-Tuning of Large Language Models
- MemBoost: A Memory-Boosted Framework for Cost-Aware LLM Inference
- RICL: Adding In-Context Adaptability to Pre-Trained Vision-Language-Action Models
- DINOv2: Learning Robust Visual Features without Supervision
- In-Context Imitation Learning via Next-Token Prediction
- StellaVLA: In-Context Structured Demonstration for Generalizable Vision-Language-Action Models
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