Artificial Intelligence-Driven Sensing of Cross-Border Trade Risks Through Declaration-to-Physical-Fact Alignment and Evidence-Grounded Question Answering.
- DOI
- 10.3390/s26165272
- Published
- 2026 Aug 20
- Container
- Sensors (Basel, Switzerland)
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.3390/s26165272,
title = {Artificial Intelligence-Driven Sensing of Cross-Border Trade Risks Through Declaration-to-Physical-Fact Alignment and Evidence-Grounded Question Answering.},
author = {Chen M and Huang J and Zhou Z and Zhang Z and Lei K and Tang Y and Li M},
year = {2026},
journal = {Sensors (Basel, Switzerland)},
doi = {10.3390/s26165272},
url = {https://doi.org/10.3390/s26165272}
}RIS
TY - JOUR TI - Artificial Intelligence-Driven Sensing of Cross-Border Trade Risks Through Declaration-to-Physical-Fact Alignment and Evidence-Grounded Question Answering. AU - Chen M AU - Huang J AU - Zhou Z AU - Zhang Z AU - Lei K AU - Tang Y AU - Li M PY - 2026 JO - Sensors (Basel, Switzerland) DO - 10.3390/s26165272 UR - https://doi.org/10.3390/s26165272 ER -
APA
M, C., J, H., Z, Z., Z, Z., K, L., Y, T., & M, L. (2026). Artificial Intelligence-Driven Sensing of Cross-Border Trade Risks Through Declaration-to-Physical-Fact Alignment and Evidence-Grounded Question Answering.. Sensors (Basel, Switzerland). https://doi.org/10.3390/s26165272
Source records
- pubmed · retrieved 2026-09-25T02:11:12.131Z