3 papers
cs.RO2026
Causal Reward World Models: Zero-shot Reward Design for Automated Skill Generation
Yang Yang, Yuchuang Tong, Zhengtao Zhang +6
Automated Reward Design (ARD) aims to replace manual reward engineering in reinforcement learning with language-driven reward function synthesis. However, existing approaches based…
cs.SE2026
Skilled AI Agents for Embedded and IoT Systems Development
Yiming Li, Yuhan Cheng, Mingchen Ma +6
Large language models (LLMs) and agentic systems have shown promise for automated software development, but applying them to hardware-in-the-loop (HIL) embedded and Internet-of-Thi…
cs.SE2025
Tree-of-Code: A Tree-Structured Exploring Framework for End-to-End Code Generation and Execution in Complex Task Handling
Ziyi Ni, Yifan Li, Ning Yang +3
Solving complex reasoning tasks is a key real-world application of agents. Thanks to the pretraining of Large Language Models (LLMs) on code data, recent approaches like CodeAct su…