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    <abstract>Generative search introduces failures in query matching, competitive ranking, and grounded generation, while conventional SEO and final mention metrics often cannot locate these failures. We present a controlled Stage-Isolated Evaluation framework that converts stage-specific errors into fact-grounded sitemap revisions. In an industrial study with an anonymized consumer-health company, each version is evaluated against nine fixed competitors using disjoint training, validation, and held-out test queries. The selected checkpoint improves the test score from 58.78 to 69.98, exceeding one-shot rewriting by 6.19 points and same-budget recursion without diagnostics by 3.07 points. Different stages favor different checkpoints, revealing non-monotonic trade-offs. Pilot online results and human annotation provide additional support for the framework as a reproducible diagnostic proxy for enterprise GEO.</abstract>
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%0 Conference Proceedings
%T Beyond Final Visibility: A Three-Stage Diagnostic Framework for Enterprise Generative Search Optimization
%Y Atanasova, Pepa
%Y Haffari, Gholamreza
%Y Wang, Minghan
%A Charming
%S Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing: Industry Track
%D 2026
%8 October
%I Association for Computational Linguistics
%C Budapest, Hungary
%@ 979-8-89176-460-6
%F charming-2026-beyond
%X Generative search introduces failures in query matching, competitive ranking, and grounded generation, while conventional SEO and final mention metrics often cannot locate these failures. We present a controlled Stage-Isolated Evaluation framework that converts stage-specific errors into fact-grounded sitemap revisions. In an industrial study with an anonymized consumer-health company, each version is evaluated against nine fixed competitors using disjoint training, validation, and held-out test queries. The selected checkpoint improves the test score from 58.78 to 69.98, exceeding one-shot rewriting by 6.19 points and same-budget recursion without diagnostics by 3.07 points. Different stages favor different checkpoints, revealing non-monotonic trade-offs. Pilot online results and human annotation provide additional support for the framework as a reproducible diagnostic proxy for enterprise GEO.
%U https://aclanthology.org/2026.emnlp-industry.96/
%P 1637-1647

Markdown (Informal)

[Beyond Final Visibility: A Three-Stage Diagnostic Framework for Enterprise Generative Search Optimization](https://aclanthology.org/2026.emnlp-industry.96/) (Charming, EMNLP 2026)

• Beyond Final Visibility: A Three-Stage Diagnostic Framework for Enterprise Generative Search Optimization (Charming, EMNLP 2026)

ACL

• Charming. 2026. Beyond Final Visibility: A Three-Stage Diagnostic Framework for Enterprise Generative Search Optimization. In Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing: Industry Track, pages 1637–1647, Budapest, Hungary. Association for Computational Linguistics.