Quan Zheng
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2026
Frozen-Response Recovery for Evidence-Linked Crisis Situation Reports
Quan Zheng | Ming Wang | Yuanhe Tian | Yan Song
Proceedings of the First Workshop on Language Technologies for Crisis Preparedness and Response
Quan Zheng | Ming Wang | Yuanhe Tian | Yan Song
Proceedings of the First Workshop on Language Technologies for Crisis Preparedness and Response
Structured crisis reports must preserve both information and its placement under canonical subsections. Merging reports generated from input chunks can omit subsections or duplicate their entries elsewhere. We introduce deterministic missing-subsection recovery and exact cross-title deduplication. The method reuses already generated model outputs, held fixed during postprocessing comparisons, without additional model calls. On 23 development cells, the combined postprocessor increased the official primary score from 0.4820 to 0.4890, a 1.45% relative gain over the baseline. Component comparisons attribute most of this development gain to recovery. On 117 test cells, all three submitted postprocessors scored 0.76–0.85% above the same baseline system on that split. Our primary system, GROUNDED, adds a fixed negative-template filter and placed fourth among nine teams; our highest-scoring submission also placed fourth in the best-system ranking. The results support structural correction of existing outputs, with small numerical differences between recovery policies across splits. They measure reference similarity, not factual entailment.