arXiv CS
open access
ARC: A Reasoning Recipe for Robot Foundation Models
The prevailing approach to improving robot foundation models (RFMs) relies on larger models, more robot demonstrations, and costly training at scale. We show that there exists an effective and efficient complementary approach: the right reasoning recipe can substantially improve the zero-shot task p
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
- ARC: A Reasoning Recipe for Robot Foundation Models#1249810
- T2-z: Test-Time Optimization of Environment Latents for Robotic World Models#1358019
- T2-z: Test-Time Optimization of Environment Latents for Robotic World Models#1348877
- Mine Odyssey: Benchmarking Spatial Agentic Intelligence in the Wild#1248608
- EMPIRIC: Experiment-Driven Learning of Residual World Models for Robot Planning#1129649
Record · ID 1242781
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