arXiv (All)
open access
Write Once, Plan Many: Building Reusable Visual Planning Systems from One Scene
Vision-language models (VLMs) can reason about visual planning tasks, but querying them for every instance incurs repeated inference cost and latency. Generating reusable planning programs offers an alternative, but constructing reliable planning systems for new problem domains without extensive sup
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Plan-Bench: Can Existing VLMs Go Well Beyond Perception to Reason and Plan in Embodied Worlds?#1344716
- Latent Goal Prediction from Language for Model-Based Planning#1186493
- VLM-Guided Experience Replay#1117317
- LLM+P: Empowering Large Language Models with Optimal Planning Proficiency#16624
- Scale-Plan: Scalable Language-Enabled Task Planning for Heterogeneous Multi-Robot Teams#792714
Record · ID 1345057
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive