arXiv (All)
open access
Skill-SLM: Agent Skill-driven Small Language Models for Reliable Robot Operation
Small language models (SLMs) have been increasingly adopted for onboard robot operation because they enable intelligent decision-making. However, existing approaches are mainly distillation-oriented and rely on enumerating representative task-solution pairs. This makes dataset construction difficult
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
- Silicon Language: A Robot-Native Knowledge Exchange Framework for Heterogeneous Robots#1217025
- Dual-Process Atomic Skill Learning: Decoupling Semantic Reasoning and Real-Time Control#1069860
- Human-like Knowledge Invention: A Non Monotonic Reasoning framework#699174
- UrbanDS: A Graph-Guided LLM Multi-Agent System for Data-Intensive Urban Tasks#820574
- Eluna: An Agentic LLM System for Automating Warehouse Operations with Reasoning and Task Execution#670677
Record · ID 1247739
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