---
title: "Who cites Supporting Clustering with Contrastive Learning"
description: "54 papers of the Elamur Research library cite «Supporting Clustering with Contrastive Learning», found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/papers/zhang-2021-supporting-clustering-contrastive-learning/cited-by/"
---
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# Who cites «Supporting Clustering with Contrastive Learning»

54 papers of our library cite it (of the 141,840 whose bibliographies we read) · 3 with a page here, the most cited first · [← back to «Supporting Clustering with Contrastive Learning»](https://md.research.elamur.ai/free/en/papers/zhang-2021-supporting-clustering-contrastive-learning/)

1. **[CLIFF: Contrastive Learning for Improving Faithfulness and Factuality in Abstractive Summarization](https://md.research.elamur.ai/free/en/papers/cao-2021-cliff-contrastive-learning-improving-faithfulness/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Shuyang Cao, Lu Wang*2021 · 258 citations*
2. **[JointCL: A Joint Contrastive Learning Framework for Zero-Shot Stance Detection](https://md.research.elamur.ai/free/en/papers/liang-2022-jointcl-joint-contrastive-learning-framework/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bin Liang, Qinglin Zhu, Xiang Li, et al.*2022 · 119 citations*
3. **[Large Language Models Enable Few-Shot Clustering](https://md.research.elamur.ai/free/en/papers/viswanathan-2024-large-language-models-enable-few/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Vijay Viswanathan, Kiril Gashteovski, Carolin Lawrence, et al.*2024 · 109 citations*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/zhang-2021-supporting-clustering-contrastive-learning/) — Supporting Clustering with Contrastive Learning