---
title: "Who cites Contrastive Prompting Enhances — 7 citing papers"
description: "7 papers of the Elamur Research library cite «Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time…"
canonical: "https://research.elamur.ai/free/en/papers/cheng-2025-contrastive-prompting-enhances-sentence-embeddings/cited-by/"
---
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Contrastive Prompting Enhances Sentence…](https://md.research.elamur.ai/free/en/papers/cheng-2025-contrastive-prompting-enhances-sentence-embeddings/) / cited by

# Who cites «Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering»

7 papers of our library cite it (of the 149,439 whose bibliographies we read) · 2 with a page here, the most cited first · [← back to «Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering»](https://md.research.elamur.ai/free/en/papers/cheng-2025-contrastive-prompting-enhances-sentence-embeddings/)

1. **[Token Prepending: A Training-Free Approach for Eliciting Better Sentence Embeddings from LLMs](https://md.research.elamur.ai/free/en/papers/fu-2025-token-prepending-training-free-approach/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuchen Fu, Zifeng Cheng, Zhiwei Jiang, et al.*2025 · 10 citations*
2. **[Tiny Budgets, Big Gains: Parameter Placement Strategy in Parameter Super-Efficient Fine-Tuning](https://md.research.elamur.ai/free/en/papers/zhao-2025-tiny-budgets-big-gains-parameter/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jinman Zhao, Xueyan Zhang, Jiaru Li, et al.*2025 · 8 citations*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/cheng-2025-contrastive-prompting-enhances-sentence-embeddings/) — Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering
