3 papers
cs.CL2026
Mock Worlds, Real Skills: Building Small Agentic Language Models with Synthetic Tasks, Simulated Environments, and Rubric-Based Rewards
Yuanjie Lyu, Chengyu Wang, Lei Shen +2
Small LLMs often struggle to match the agentic capabilities of large, costly models. While reinforcement learning can help, progress has been limited by two structural bottlenecks:…
cs.AI2026
How Foundational Skills Influence VLM-based Embodied Agents:A Native Perspective
Bo Peng, Pi Bu, Keyu Pan +7
Recent advances in vision-language models (VLMs) have shown promise for human-level embodied intelligence. However, existing benchmarks for VLM-driven embodied agents often rely on…
cs.RO2025
An Atomic Skill Library Construction Method for Data-Efficient Embodied Manipulation
Dongjiang Li, Bo Peng, Chang Li +13
Embodied manipulation is a fundamental ability in the realm of embodied artificial intelligence. Although current embodied manipulation models show certain generalizations in speci…