STT-Arena: A More Realistic Environment for Tool-Using with Spatio-Temporal Dynamics
Large language models (LLMs) deployed in real-world agentic applications must be capable of replanning and adapting when mid-task disruptions invalidate their prior decisions. Existing dynamic benchmarks primarily measure whether LLMs can detect temporal changes in a timely manner, leaving the complementary challenge of adaptive replanning under spatio-temporal dynamics largely unexplored. We introduce STT-Arena (Spatio-Temporal Tool-Use Arena), a benchmark of 227 high-quality interactive tasks spanning nine spatio-temporal conflict types and four solvability levels. Each task is grounded in a realistic, executable environment equipped with injected spatio-temporal triggers that can abrup...
| Authors | Tingfeng Hui, Hao Xu, Pengyu Zhu et al. |
|---|---|
| Primary category | cs.CL |
| Published | 18 May 2026 |
| Last updated at source | 18 May 2026 |
Models and datasets referencing this paper
- Miaow-Lab/STT-ArenaDataset
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