JarvisBench: A New Benchmark for Always-On Human-Agent Coordination
A recent study has unveiled JarvisBench, a benchmark aimed at assessing the collaboration between humans and long-horizon AI agents. This research, published on arXiv (2608.14870), introduces an 'always-on attention-coordination layer' called Jarvis, named after the AI assistant from Iron Man. This layer facilitates communication between users and multiple active agents, tackling the challenge of bidirectional coordination, where human focus is limited while agents function continuously. JarvisBench measures two aspects: the ability of the intermediary to swiftly and accurately respond to user inquiries regarding ongoing tasks, and its capacity to identify when user judgment is needed, effectively soliciting and relaying that input to enhance task performance. This work contributes to the broader field of AI and human-agent interaction, with significant implications for autonomous systems and human oversight.
Key facts
- Paper title: JarvisBench: Always-on Intelligence Between Humans and Agents
- Published on arXiv with identifier 2608.14870
- Introduces Jarvis, an always-on attention-coordination layer
- Named after the fictional AI assistant in Iron Man
- Evaluates bidirectional coordination between humans and agents
- Focuses on answering user questions and soliciting user judgment
- Addresses the problem of intermittent human attention in long-horizon tasks
- Available at https://arxiv.org/abs/2608.14870
Entities
Institutions
- arXiv