Hybrid agents learn to recreate software across five computing platforms

RecreationWorld combines GUI control, coding tools, and reference-grounded tests to train and evaluate agents that inspect, implement, and verify applications.

Chinese Tech
Shuai Bai · Jiayong Deng · Yikun Fu · Chang Gao · Xuhao Hu · Mianqiu Huang · +26 more

Alibaba Token Hub · Alibaba Group

Research Digest··2 min read
The authors introduce reproducible environments for hybrid computer-use agents on Ubuntu, macOS, Windows, Android, and the Web.

The authors built RecreationWorld, a unified harness in which agents can operate graphical interfaces, write and run code, and visually inspect their outputs.

Why this paper

From Alibaba Token Hub and Alibaba Group · Part of Cross-Device Agent Benchmarks, now 3 papers

In one line

Training hybrid agents on RecreationWorld trajectories improves performance on out-of-distribution coding and hybrid benchmarks.

What we could check

  • ·No code link found
  • ·No weights link found
  • ·No dataset link found
  • ·No compute details found
  • ·No stated limitations found
  • ·No benchmark numbers found

Observed from the paper text and links we have. Absence here means we did not find it, not that it does not exist.

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