---
title: "Who cites CoAnnotating: — 52 citing papers — Elamur Research"
description: "52 papers of the Elamur Research library cite «CoAnnotating: Uncertainty-Guided Work Allocation between Human and Large Language…"
canonical: "https://research.elamur.ai/free/en/papers/li-2023-coannotating-uncertainty-guided-work-allocation/cited-by/"
---
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [CoAnnotating: Uncertainty-Guided Work Allocation…](https://md.research.elamur.ai/free/en/papers/li-2023-coannotating-uncertainty-guided-work-allocation/) / cited by

# Who cites «CoAnnotating: Uncertainty-Guided Work Allocation between Human and Large Language Models for Data Annotation»

52 papers of our library cite it (of the 141,840 whose bibliographies we read) · 2 with a page here, the most cited first · [← back to «CoAnnotating: Uncertainty-Guided Work Allocation between Human and Large Language Models for Data Annotation»](https://md.research.elamur.ai/free/en/papers/li-2023-coannotating-uncertainty-guided-work-allocation/)

1. **[Large Language Models for Data Annotation and Synthesis: A Survey](https://md.research.elamur.ai/free/en/papers/tan-2024-large-language-models-data-annotation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhen Tan, Dawei Li, Song Wang, et al.*2024 · 259 citations*
2. **[On LLMs-Driven Synthetic Data Generation, Curation, and Evaluation: A Survey](https://md.research.elamur.ai/free/en/papers/long-2024-llms-driven-synthetic-data-generation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Lin Long, Rui Wang, Ruixuan Xiao, et al.*2024 · 236 citations*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/li-2023-coannotating-uncertainty-guided-work-allocation/) — CoAnnotating: Uncertainty-Guided Work Allocation between Human and Large Language Models for Data Annotation
