NASA’s new dark energy space telescope can also detect killer asteroids
technologyreview.com·3h ago
AI Research
arXiv CS.AI·Jun 9·5 min read
WeaveBench: A Long-Horizon, Real-World Benchmark for Computer-Use Agents with Hybrid Interfaces
TL;DR
Existing benchmarks for computer-use agents (CUAs) often treat different interfaces separately, neglecting their integration in real-world tasks. WeaveBench is introduced as a long-horizon benchmark that evaluates CUAs across 114 tasks in 8 work domains, focusing on hybrid interfaces.
✦ Why It Matters
Engineers can use WeaveBench to better evaluate and improve the performance of computer-use agents in real-world applications.
Key Takeaways
- Utilize WeaveBench for comprehensive CUA performance evaluation.
- Focus on cross-interface orchestration in agent design.
- Incorporate real user requests into task development.
- Explore hybrid interface capabilities for improved agent functionality.
Full Summary
Computer-use agents (CUAs) are increasingly required to navigate complex environments that combine visual desktop control, command-line execution, and web browsing. Traditional benchmarks have evaluated these interfaces in isolation, failing to capture the challenges of long-horizon tasks that require cross-interface coordination.
WeaveBench was developed to address this gap, featuring 114 tasks across 8 real-world domains, all based on actual user requests. The benchmark allows for the assessment of CUAs' performance in hybrid environments, where multiple interfaces must be orchestrated effectively.
Initial evaluations using WeaveBench reveal significant insights into agent capabilities and limitations in real-world scenarios. This tool not only enhances the benchmarking process but also provides a framework for future research in agent development and evaluation.
The implications for engineers include improved design and testing of CUAs that can operate seamlessly across various interfaces.