LongWoF-Bench: Evaluating EvoMap Genes for Verifiable Long-Workflow Tasks
Large language models are increasingly expected to execute complex workflows whose success depends on maintaining interdependent constraints and producing artifacts that satisfy strict end-to-end verification. Yet successful execution experience is typically lost after a single run, forcing subsequent models to rediscover strategies and failure modes from scratch. We study whether such experience can instead be externalized and reused through EvoMap, where verifier-confirmed execution trajectories are consolidated into structured Gene. To evaluate this setting, we introduce the Long-Workflow Benchmark (LongWoF-Bench), comprising 778 machine-verifiable tasks across code generation, agent-e...
| Authors | Xiao Zhang, Qumeng Sun, Jiahao Li et al. |
|---|---|
| Primary category | cs.CL |
| Published | 24 August 2026 |
| Last updated at source | 17 September 2026 |
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