arXiv cs.AIPaper
Don't Drop the BATON: Long-Horizon Robot Manipulation via Agentic Subtask Exploration and Transition-aware Memory
The real insight is that VLA models alone hit a wall on sequential tasks because errors compound and interface conditions aren't explicit. By freezing the VLA and letting an LLM agent handle the logic layer and memory, the authors buy interpretability and efficiency. If you're building robot systems, this is the architecture to test: it separates concerns in a way that might actually scale to real warehouse and manufacturing tasks.