--- title: "Who cites Repetition Improves Language Model Embeddings" description: "71 papers of the Elamur Research library cite «Repetition Improves Language Model Embeddings», found in their bibliographies; the most cited first." canonical: "https://research.elamur.ai/free/en/papers/springer-2024-repetition-improves-language-model-embeddings/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/springer-2024-repetition-improves-language-model-embeddings/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Repetition Improves Language Model Embeddings](https://md.research.elamur.ai/free/en/papers/springer-2024-repetition-improves-language-model-embeddings/) / cited by # Who cites «Repetition Improves Language Model Embeddings» 71 papers of our library cite it (of the 149,439 whose bibliographies we read) · 15 with a page here, the most cited first · [← back to «Repetition Improves Language Model Embeddings»](https://md.research.elamur.ai/free/en/papers/springer-2024-repetition-improves-language-model-embeddings/) 1. [**LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders arXiv:2404.05961**Parishad BehnamGhader, Vaibhav Adlakha, Marius Mosbach, et al.*2024 · 213 citations*](https://md.research.elamur.ai/free/en/papers/behnamghader-2024-llm2vec-large-language-models-secretly/) 2. [**Gecko: Versatile Text Embeddings Distilled from Large Language Models arXiv:2403.20327**Jinhyuk Lee, Zhuyun Dai, Xiaoqi Ren, et al.*2024 · 74 citations*](https://md.research.elamur.ai/free/en/papers/lee-2024-gecko-versatile-text-embeddings-distilled/) 3. [**Can Long-Context Language Models Subsume Retrieval, RAG, SQL, and More? arXiv:2406.13121**Jinhyuk Lee, Anthony Chen, Zhuyun Dai, et al.*2024 · 53 citations*](https://md.research.elamur.ai/free/en/papers/lee-2024-long-context-language-models-subsume/) 4. **[DRAMA: Diverse Augmentation from Large Language Models to Smaller Dense Retrievers](https://md.research.elamur.ai/free/en/papers/ma-2025-drama-diverse-augmentation-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xueguang Ma, Xi Victoria Lin, Barlas Oguz, et al.*2025 · 13 citations* 5. **[Diffusion vs. Autoregressive Language Models: A Text Embedding Perspective](https://md.research.elamur.ai/free/en/papers/zhang-2025-diffusion-vs-autoregressive-language-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Siyue Zhang, Yilun Zhao, Liyuan Geng, et al.*2025 · 10 citations* 6. **[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* 7. **[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/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zifeng Cheng, Zhonghui Wang, Yuchen Fu, et al.*2025 · 8 citations* 8. [**Just read twice: closing the recall gap for recurrent language models arXiv:2407.05483**Simran Arora; Aman Timalsina; Aaryan Singhal; Benjamin Spector; Sabri Eyuboglu; Xinyi Zhao; Ashish Rao; Atri Rudra;, Christopher Re*2024 · 8 citations*](https://md.research.elamur.ai/free/en/papers/arora-2024-just-read-twice-closing-recall/) 9. **[Transforming Causal LLM into MLM Encoder for Detecting Social Media Manipulation in Telegram](https://md.research.elamur.ai/free/en/papers/bazdyrev-2025-transforming-causal-llm-into-mlm/) [Ukrainian Natural Language Processing Workshop](https://md.research.elamur.ai/free/en/venues/unlp/)**Anton Bazdyrev, Ivan Bashtovyi, Ivan Havlytskyi, et al.*2025 · 2 citations* 10. **[KV-Embedding: Training-free Text Embedding via Internal KV Re-routing in Decoder-only LLMs](https://md.research.elamur.ai/free/en/papers/tang-2026-kv-embedding-training-free-text/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yixuan Tang, Yi Yang*2026 · 1 citation* 11. **[Representation-Aware Prompting for Zero-Shot Marathi Text Classification: IPA, Romanization, Repetition](https://md.research.elamur.ai/free/en/papers/tran-2026-representation-aware-prompting-zero-shot/) [Workshop on Language Models for Low-Resource Languages](https://md.research.elamur.ai/free/en/venues/loreslm/)**Van-Hien Tran, Huy Hien Vu, Hideki Tanaka, et al.*2026 · 1 citation* 12. **[Uncertainty-Aware Contrastive Sentence Embedding With Local Context Representation for Text Classification](https://md.research.elamur.ai/free/en/papers/liu-2026-uncertainty-aware-contrastive-sentence-embedding/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Han Liu, Jiaqing Zhan, Zhichao Chen, et al.*2026 · 1 citation* 13. **[AEA: Adaptive Expert Allocation Improves Sentence Embeddings from Mixture-of-Experts LLM](https://md.research.elamur.ai/free/en/papers/yang-2026-aea-adaptive-expert-allocation-improves/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shufan Yang, Zifeng Cheng, Zhiwei Jiang, et al.*2026* 14. **[Chameleons and Guardians: Unveiling the Divergence in Personality Plasticity and Cognitive Resistance across LLMs](https://md.research.elamur.ai/free/en/papers/wu-2026-chameleons-guardians-unveiling-divergence-personality/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiaxin Wu, Jie Zhao, Huangxinrong, et al.*2026* 15. **[Parallel-SFT: Improving Zero-Shot Cross-Programming-Language Transfer for Code RL](https://md.research.elamur.ai/free/en/papers/wu-2026-parallel-sft-improving-zero-shot/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhaofeng Wu, Shiqi Wang, Boya Peng, et al.*2026* 56 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/springer-2024-repetition-improves-language-model-embeddings/) — Repetition Improves Language Model Embeddings