---
title: "Who cites CheckEval: A reliable — 26 citing papers"
description: "26 papers of the Elamur Research library cite «CheckEval: A reliable LLM-as-a-Judge framework for evaluating text generation using…"
canonical: "https://research.elamur.ai/free/en/papers/lee-2025-checkeval-reliable-llm-as-judge/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/lee-2025-checkeval-reliable-llm-as-judge/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [CheckEval: A reliable LLM-as-a-Judge framework…](https://md.research.elamur.ai/free/en/papers/lee-2025-checkeval-reliable-llm-as-judge/) / cited by

# Who cites «CheckEval: A reliable LLM-as-a-Judge framework for evaluating text generation using checklists»

26 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 «CheckEval: A reliable LLM-as-a-Judge framework for evaluating text generation using checklists»](https://md.research.elamur.ai/free/en/papers/lee-2025-checkeval-reliable-llm-as-judge/)

1. **[Transforming Science with Large Language Models: A Survey on AI-assisted Scientific Discovery, Experimentation, Content Generation, and Evaluation](https://md.research.elamur.ai/free/en/papers/eger-2025-transforming-science-large-language-models/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Steffen Eger, Yong Cao, Jennifer D'Souza, et al.*2025 · 25 citations*
2. **[RubricBench: Aligning Model-Generated Rubrics with Human Standards](https://md.research.elamur.ai/free/en/papers/zhou-2026-rubricbench-aligning-model-generated-rubrics/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junyi Zhou, Qiyuan Zhang, Yufei Wang, et al.*2026 · 3 citations*
3. **[AnalystBench: Benchmarking professional long-form report generation with web-mined multimodal tasks](https://md.research.elamur.ai/free/en/papers/pham-2026-analystbench-benchmarking-professional-long-form/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chau Minh Pham, Zichao Wang, Puneet Mathur, et al.*2026*
4. **[Child-directed speech facilitates production, not comprehension, in BabyLMs](https://md.research.elamur.ai/free/en/papers/bunzeck-2026-child-directed-speech-facilitates-production/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Bastian Bunzeck, Sina Zarrieß*2026*
5. **[Evaluation Pitfalls and Sparsity Limitations in LLM-based Confidence Estimates for Classification](https://md.research.elamur.ai/free/en/papers/merdjanovska-2026-evaluation-pitfalls-sparsity-limitations-llm/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Elena Merdjanovska, Omar Zaidan, Andreas Rücklé*2026*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/lee-2025-checkeval-reliable-llm-as-judge/) — CheckEval: A reliable LLM-as-a-Judge framework for evaluating text generation using checklists