---
title: "Who cites Jina Embeddings 2: 8192-Token — 62 citing papers"
description: "62 papers of the Elamur Research library cite «Jina Embeddings 2: 8192-Token General-Purpose Text Embeddings for Long Documents»…"
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---
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# Who cites «Jina Embeddings 2: 8192-Token General-Purpose Text Embeddings for Long Documents»

62 papers of our library cite it (of the 141,840 whose bibliographies we read) · 7 with a page here, the most cited first · [← back to «Jina Embeddings 2: 8192-Token General-Purpose Text Embeddings for Long Documents»](https://md.research.elamur.ai/free/en/papers/gunther-2023-jina-embeddings-2-8192-token/)

1. [**M3-Embedding: Multi-Linguality, Multi-Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillation arXiv:2402.03216**Jianlv Chen, Shitao Xiao, Peitian Zhang, et al.*2024 · 1,196 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-m3-embedding-multi-linguality/)
2. **[mGTE: Generalized Long-Context Text Representation and Reranking Models for Multilingual Text Retrieval](https://md.research.elamur.ai/free/en/papers/zhang-2024-mgte-generalized-long-context-text/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xin Zhang, Yanzhao Zhang, Dingkun Long, et al.*2024 · 236 citations*
3. [**Generative Representational Instruction Tuning arXiv:2402.09906**Niklas Muennighoff, Hongjin Su, Liang Wang, et al.*2024 · 165 citations*](https://md.research.elamur.ai/free/en/papers/muennighoff-2024-generative-representational-instruction-tuning/)
4. [**LongLLMLingua: Accelerating and Enhancing LLMs in Long Context Scenarios via Prompt Compression arXiv:2310.06839**Huiqiang Jiang, Qianhui Wu, Xufang Luo, et al.*2023 · 158 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2023-longllmlingua-accelerating-enhancing-llms-long/)
5. [**Nomic Embed: Training a Reproducible Long Context Text Embedder arXiv:2402.01613**Zach Nussbaum, John X. Morris, Brandon Duderstadt, et al.*2024 · 123 citations*](https://md.research.elamur.ai/free/en/papers/nussbaum-2024-nomic-embed-training-reproducible-long/)
6. [**MultiHop-RAG: Benchmarking Retrieval-Augmented Generation for Multi-Hop Queries arXiv:2401.15391**Yixuan Tang, Yi Yang*2024 · 103 citations*](https://md.research.elamur.ai/free/en/papers/tang-2024-multihop-rag-benchmarking-retrieval-augmented/)
7. [**A Comprehensive Survey on Long Context Language Modeling arXiv:2503.17407**Jiaheng Liu, Dawei Zhu, Zhiqi Bai, et al.*2025 · 64 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-comprehensive-survey-long-context-language/)

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

- [← back to](https://md.research.elamur.ai/free/en/papers/gunther-2023-jina-embeddings-2-8192-token/) — Jina Embeddings 2: 8192-Token General-Purpose Text Embeddings for Long Documents