TerminalTraj: Scalable Pipeline Generates 50K Verified Terminal Trajectories for Agentic Training
Researchers introduce TerminalTraj, a scalable pipeline that filters high-quality repositories to construct Dockerized execution environments and generates verified terminal trajectories for training AI agents. The pipeline curated 32,000 Docker images and produced 50,733 verified trajectories across eight domains. Models trained on this data achieved up to 20% improvement on TerminalBench 1.0 and 10% on TerminalBench 2.0 benchmarks, demonstrating notable performance gains over previous backbones.
Why it matters: TerminalTraj addresses the challenge of data scarcity for training terminal-based AI agents by providing a scalable method to generate large-scale, executable, and verifiable training data.
Full story at: arXiv Computation and Language ↗