NeSy-Route: A Neuro-Symbolic Benchmark for Constrained Route Planning in Remote Sensing
Remote sensing underpins crucial applications such as disaster relief and ecological field surveys, where systems must understand complex scenes and constraints and make reliable decisions. Current remote-sensing benchmarks mainly focus on evaluating perception and reasoning capabilities of multimodal large language models (MLLMs). They fail to assess planning capability, stemming either from the difficulty of curating and validating planning tasks at scale or from evaluation protocols that are inaccurate and inadequate. To address these limitations, we introduce NeSy-Route, a large-scale neuro-symbolic benchmark for constrained route planning in remote sensing. Within this benchmark, we ...
| Authors | Ming Yang, Zhi Zhou, Shi-Yu Tian et al. |
|---|---|
| Primary category | cs.AI |
| Published | 17 March 2026 |
| Last updated at source | 15 July 2026 |
Models and datasets referencing this paper
- Ming1010/NeSy-RouteDataset
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