---
title: "Who cites Trust or Escalate: LLM Judges — 19 citing papers"
description: "19 papers of the Elamur Research library cite «Trust or Escalate: LLM Judges with Provable Guarantees for Human Agreement», found in their…"
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---
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# Who cites «Trust or Escalate: LLM Judges with Provable Guarantees for Human Agreement»

19 papers of our library cite it (of the 149,439 whose bibliographies we read) · 5 with a page here, the most cited first · [← back to «Trust or Escalate: LLM Judges with Provable Guarantees for Human Agreement»](https://md.research.elamur.ai/free/en/papers/jung-2024-trust-escalate-llm-judges-provable/)

1. [**LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods arXiv:2412.05579**Haitao Li, Qian Dong, Junjie Chen, et al.*2024 · 195 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-llms-judges-comprehensive-survey-llm/)
2. **[The Alternative Annotator Test for LLM-as-a-Judge: How to Statistically Justify Replacing Human Annotators with LLMs](https://md.research.elamur.ai/free/en/papers/calderon-2025-alternative-annotator-test-llm-as/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Nitay Calderon, Roi Reichart, Rotem Dror*2025 · 52 citations*
3. [**A Survey of Frontiers in LLM Reasoning: Inference Scaling, Learning to Reason, and Agentic Systems arXiv:2504.09037**Zixuan Ke, Fangkai Jiao, Yifei Ming, et al.*2025 · 39 citations*](https://md.research.elamur.ai/free/en/papers/ke-2025-survey-frontiers-llm-reasoning-inference/)
4. **[When One LLM Drools, Multi-LLM Collaboration Rules](https://md.research.elamur.ai/free/en/papers/feng-2026-when-one-llm-drools-multi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shangbin Feng, Wenxuan Ding, Alisa Liu, et al.*2026 · 14 citations*
5. **[Calibrating LLM Judges: Linear Probes for Fast and Reliable Uncertainty Estimation](https://md.research.elamur.ai/free/en/papers/radharapu-2026-calibrating-llm-judges-linear-probes/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bhaktipriya Radharapu, Eshika Saxena, Kenneth Li, et al.*2026*

14 more papers of our library cite it; they have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/jung-2024-trust-escalate-llm-judges-provable/) — Trust or Escalate: LLM Judges with Provable Guarantees for Human Agreement