Year: 2026
Type: conference-paper
Abstract: Modern human labor is characterized by specialization; we train for years and develop particular tools that allow us to perform well across a variety of tasks.Similarly, specialized AI agents with task-specific tools or architectures often fail to generalize beyond their intended scope.In this work, we ask: can agents achieve generalizability across diverse domains with a small, but well-chosen set of general tools?We propose OpenHands-Versa, a single-agent system with a modest number of general tools like code execution, search engine, web browser and multimodal file viewer, for three practical domains: software engineering, deep research, and web browsing.Notably, OpenHands-Versa demonstrates superior or competitive performance over task-specific specialized agents on three challenging benchmarks: SWE-Bench Multimodal, GAIA, and The Agent Company, with absolute improvements in success rate of 9.1, 1.3, and 9.1 points, respectively.Thus, our single-agent system can achieve strong generalization indicating that specialist agents for these domains provide no practical benefit.Furthermore, we find that specialist multi-agent systems do not generalize beyond their intended scope.These findings establish OpenHands-Versa as a strong baseline for future research.1
Institution: Carnegie Mellon University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W7140093760