The authors treat tool use as a system involving four connected components: the environment, the assigned task, the agent harness that manages interaction, and the evaluator that determines success.
Whole-system training improves general-purpose agents’ use of external tools
WEFT jointly evolves tool environments, tasks, agent harnesses and evaluators, then uses execution evidence to produce more reliable training signals.
Independent
Bo Mao · Hang He · Linting Wang · Lizhi Lin · Maosen Zhou · Guanming Liu · +14 more
Research Digest··2 min read
Mao and colleagues present WEFT, a framework for scaling tool-use post-training across the entire agent interaction system rather than generating more executable environments alone.
Why this paper
Independent
In one line
WEFT scales tool-use post-training for general-purpose agents by coupling whole-system interaction construction, execution-driven self-evolution, and stable post-training.
What we could check
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