When to Trust: Margin-Calibrated Routing Between LLM-as-a-Judge and Human Experts

Xinran Zhang; Ping Nie; Michelle Lok-yee Chan; Joshua L. Mason; Arash Sadati; Tate Sterling Avery

When to Trust: Margin-Calibrated Routing Between LLM-as-a-Judge and Human Experts

Xinran Zhang, Ping Nie, Michelle Lok-yee Chan, Joshua L. Mason, Arash Sadati, Tate Sterling Avery

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Anthology ID:: 2026.emnlp-industry.201
Volume:: Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing: Industry Track
Month:: October
Year:: 2026
Address:: Budapest, Hungary
Editors:: Pepa Atanasova, Gholamreza Haffari, Minghan Wang
Venue:: EMNLP
SIG:: SIGDAT
Publisher:: Association for Computational Linguistics
Note:
Pages:: 3376–3390
Language:
URL:: https://aclanthology.org/2026.emnlp-industry.201/
DOI:
Bibkey:
Cite (ACL):: Xinran Zhang, Ping Nie, Michelle Lok-yee Chan, Joshua L. Mason, Arash Sadati, and Tate Sterling Avery. 2026. When to Trust: Margin-Calibrated Routing Between LLM-as-a-Judge and Human Experts. In Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing: Industry Track, pages 3376–3390, Budapest, Hungary. Association for Computational Linguistics.
Cite (Informal):: When to Trust: Margin-Calibrated Routing Between LLM-as-a-Judge and Human Experts (Zhang et al., EMNLP 2026)
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PDF:: https://aclanthology.org/2026.emnlp-industry.201.pdf

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@inproceedings{zhang-etal-2026-trust,
    title = "When to Trust: Margin-Calibrated Routing Between {LLM}-as-a-Judge and Human Experts",
    author = "Zhang, Xinran  and
      Nie, Ping  and
      Chan, Michelle Lok-yee  and
      Mason, Joshua L.  and
      Sadati, Arash  and
      Avery, Tate Sterling",
    editor = "Atanasova, Pepa  and
      Haffari, Gholamreza  and
      Wang, Minghan",
    booktitle = "Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing: Industry Track",
    month = oct,
    year = "2026",
    address = "Budapest, Hungary",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2026.emnlp-industry.201/",
    pages = "3376--3390",
    ISBN = "979-8-89176-460-6"
}

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%0 Conference Proceedings
%T When to Trust: Margin-Calibrated Routing Between LLM-as-a-Judge and Human Experts
%A Zhang, Xinran
%A Nie, Ping
%A Chan, Michelle Lok-yee
%A Mason, Joshua L.
%A Sadati, Arash
%A Avery, Tate Sterling
%Y Atanasova, Pepa
%Y Haffari, Gholamreza
%Y Wang, Minghan
%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 zhang-etal-2026-trust
%U https://aclanthology.org/2026.emnlp-industry.201/
%P 3376-3390

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Markdown (Informal)

[When to Trust: Margin-Calibrated Routing Between LLM-as-a-Judge and Human Experts](https://aclanthology.org/2026.emnlp-industry.201/) (Zhang et al., EMNLP 2026)

When to Trust: Margin-Calibrated Routing Between LLM-as-a-Judge and Human Experts (Zhang et al., EMNLP 2026)

ACL

Xinran Zhang, Ping Nie, Michelle Lok-yee Chan, Joshua L. Mason, Arash Sadati, and Tate Sterling Avery. 2026. When to Trust: Margin-Calibrated Routing Between LLM-as-a-Judge and Human Experts. In Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing: Industry Track, pages 3376–3390, Budapest, Hungary. Association for Computational Linguistics.