GeoGround: Uncertainty-Weighted Multi-Task Learning for Geo-Alignment and Address Defect Detection (2026.acl-industry)
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| Challenge: | Address intelligence in e-commerce requires precise geocoding and proactive defect detection under strict sub-50 ms latency constraints. |
| Approach: | They propose a multi-task learning framework that jointly models coordinate grounding and address defect detection. |
| Outcome: | The proposed model achieves 5.86 gains in address defect detection precision and 4.86 improvements in location prediction accuracy over strong encoder baselines while remaining 75 more efficient than decoder LLMs such as Qwen2-1.5B. |
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