Unverified50% confidenceOpinionExact time
Tev-27B, trained only on ALE-related data, can nonetheless generalize to Terminal-Bench, suggesting that it has learned some domain-agnostic long-horizon task execution capability rather than merely memorizing specific task solutions.
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Long-term
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10/14/2026
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UnverifiedSpecialized training for long-horizon tasks typically requires constructing supervised data containing complete task trajectories, rather than simple single-turn question-answer pairs.67% similarUnverifiedThe planner was trained via supervised fine-tuning (SFT) on outcome-selection trajectories from 140 training questions and 28 development questions.64% similarUnverified当任务要求访问模型训练截止日期之后的信息、精确数值计算或处理外部文件时，提示词工程无济于事，这是工具调用和RAG出现的根本原因64% similarUnverifiedAgent Tuning is a specialized direction of supervised fine-tuning (SFT), where training samples are complete task trajectories rather than traditional question-answer pairs.62% similarUnverifiedTerminal-Universe proposes that a more effective approach than directly training on terminal agent execution trajectories is to first reconstruct the complete working environment behind the trajectories, and then generate new verifiable tasks from that environment.62% similar
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