5 papers
Fork, Explore, Commit: OS Primitives for Agentic Exploration
Cong Wang, Yusheng Zheng
AI agents increasingly perform agentic exploration: pursuing multiple solution paths in parallel and committing only the successful one. Because each exploration path may modify fi…
Writing With Machines and Peers: Designing for Critical Engagement with Generative AI
Xinran Zhu, Cong Wang, Duane Searsmith
The growing integration of generative AI in higher education is transforming how students write, learn, and engage with knowledge. As AI tools become more integrated into classroom…
HiBerNAC: Hierarchical Brain-emulated Robotic Neural Agent Collective for Disentangling Complex Manipulation
Hongjun Wu, Heng Zhang, Pengsong Zhang +2
Recent advances in multimodal vision-language-action (VLA) models have revolutionized traditional robot learning, enabling systems to interpret vision, language, and action in unif…
Scaling Laws in Scientific Discovery with AI and Robot Scientists
Pengsong Zhang, Heng Zhang, Huazhe Xu +7
Scientific discovery is poised for rapid advancement through advanced robotics and artificial intelligence. Current scientific practices face substantial limitations as manual expe…
Robust Mobile Robot Path Planning via LLM-Based Dynamic Waypoint Generation
Muhammad Taha Tariq, Congqing Wang, Yasir Hussain
Mobile robot path planning in complex environments remains a significant challenge, especially in achieving efficient, safe and robust paths. The traditional path planning techniqu…