Toward explainable traffic crash liability analysis via neural-symbolic multimodal reasoning: Integrating visual perception with legal knowledge graphs
- DOI
- 10.1016/j.aap.2026.108813
- Published
- 2027-01
- Container
- Accident Analysis & Prevention
- Publisher
- Elsevier BV
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.aap.2026.108813,
title = {Toward explainable traffic crash liability analysis via neural-symbolic multimodal reasoning: Integrating visual perception with legal knowledge graphs},
author = {Jingyun Xu and Yuzhi Chen and Xiaoxi Hu and Yuanchang Xie and Xinyu Zhang and Jialun Yin and Chen Wang},
year = {2027},
journal = {Accident Analysis \& Prevention},
doi = {10.1016/j.aap.2026.108813},
url = {https://doi.org/10.1016/j.aap.2026.108813}
}RIS
TY - JOUR TI - Toward explainable traffic crash liability analysis via neural-symbolic multimodal reasoning: Integrating visual perception with legal knowledge graphs AU - Jingyun Xu AU - Yuzhi Chen AU - Xiaoxi Hu AU - Yuanchang Xie AU - Xinyu Zhang AU - Jialun Yin AU - Chen Wang PY - 2027 JO - Accident Analysis & Prevention DO - 10.1016/j.aap.2026.108813 UR - https://doi.org/10.1016/j.aap.2026.108813 ER -
APA
Xu, J., Chen, Y., Hu, X., Xie, Y., Zhang, X., Yin, J., & Wang, C. (2027). Toward explainable traffic crash liability analysis via neural-symbolic multimodal reasoning: Integrating visual perception with legal knowledge graphs. Accident Analysis & Prevention. https://doi.org/10.1016/j.aap.2026.108813
Source records
- crossref · retrieved 2026-11-10T12:10:22.817Z