arXiv AI By Zirong Chen, Hongchao Zhang, Meiyi Ma

PACE: A Personalized Adaptive Curriculum Engine for 9-1-1 Call-taker Training

Read the original on arXiv AI →

arXiv:2603. 05361v2 Announce Type: replace Abstract: 9-1-1 call-taking training requires mastery of over a thousand interdependent skills, covering diverse incident types and protocol-specific nuances.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv AI.

arXiv AI
Jul 13

Empowering 9-1-1 Calltaking Training with Generative AI: Experiences and Lessons Learned

arXiv:2602. 13241v3 Announce Type: replace-cross Abstract: Emergency call-takers form the first operational link in public safety response, handling over 240 million calls annually while facing a sustained training crisis: staffing shortages exceed 25\% in many centers, and preparing a single new hire can require up to 720 hours of one-on-one instruction that removes experienced personnel from active duty.

By Zirong Chen, Meiyi Ma
arXiv AI
Aug 7

Search2Skill: Skill Distillation Beyond Knowledge Boundaries Via Rubric-Based Reinforcement Learning

arXiv:2608. 05245v1 Announce Type: new Abstract: Reusable skills, which encapsulate the procedural knowledge required to solve real-world professional tasks, offer LLM-based agents a path toward self-evolution in expert domains.

By Muyang Ye, Tian Lan, Feihu Jiang, Yongshi Ye, Wuyunsiqin, Bin Zhu, Qianghuai Jia, Zhao Xu, Weihua Luo, Ye Wang, Jinyang Zhang, Longyue Wang, Lingfeng Bao