FireWorldBench: Benchmarking Complex Physical World Intelligence through Coupled-Field Fire Dynamics
Understanding the physical world requires more than object recognition, scene description, and short-term visual prediction, as real-world physical systems involve multiple continuous fields, latent causal mechanisms, partial observations, and intervention-sensitive dynamics. We propose FireWorldBench, a benchmark for evaluating complex physical world intelligence in multimodal large language models and agents through coupled-field fire dynamics. Fire provides a canonical stress-test environment, where multiple interacting physical fields jointly shape observable states and temporal dynamics. FireWorldBench is organized along two complementary axes, a physical capability axis and a fire s...
| Authors | Qiang Chen, Hao Guo, Huatai Zhu et al. |
|---|---|
| Primary category | cs.AI |
| Published | 19 September 2026 |
| Last updated at source | 19 September 2026 |
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