---
title: "Who cites Saba Sturua — 219 papers of our library"
description: "219 papers of the Elamur Research library cite the works of Saba Sturua, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/saba-sturua/cited-by/"
---
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# Who cites Saba Sturua

238 citations of their works from 219 papers of our library (of the 141,840 whose bibliographies we read) · 13 with a page here, the most cited first · [← Saba Sturua](https://md.research.elamur.ai/free/en/authors/saba-sturua/)

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. [**Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models arXiv:2506.05176**Yanzhao Zhang, Mingxin Li, Dingkun Long, et al.*2025 · 313 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2025-qwen3-embedding-advancing-text/)
3. **[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*
4. [**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/)
5. [**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/)
6. [**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/)
7. [**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/)
8. [**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/)
9. [**mmBERT: A Modern Multilingual Encoder with Annealed Language Learning arXiv:2509.06888**Marc Marone, Orion Weller, William Fleshman, et al.*2025 · 59 citations*](https://md.research.elamur.ai/free/en/papers/marone-2025-mmbert-modern-multilingual-encoder-annealed/)
10. **[New Encoders for German Trained from Scratch: Comparing ModernGBERT with Converted LLM2Vec Models](https://md.research.elamur.ai/free/en/papers/wunderle-2026-new-encoders-german-trained-scratch/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Julia Wunderle, Anton Ehrmanntraut, Jan Pfister, et al.*2026 · 7 citations*
11. **[A Recipe for Adapting Multilingual Embedders to OCR-Error Robustness and Historical Texts](https://md.research.elamur.ai/free/en/papers/michail-2026-recipe-adapting-multilingual-embedders-ocr/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Andrianos Michail, Stylianos Psychias, Juri Opitz, et al.*2026*
12. [**Grounding Arabic LLMs in the Doha Historical Dictionary: Retrieval-Augmented Understanding of Quran and Hadith arXiv:2603.23972**Somaya Eltanbouly, Samer Rashwani*2026*](https://md.research.elamur.ai/free/en/papers/eltanbouly-2026-grounding-arabic-llms-doha-historical/)
13. **[Modeling semantic association in self-paced reading with language model embeddings](https://md.research.elamur.ai/free/en/papers/ostergaard-2026-modeling-semantic-association-self-paced/) [Workshop on Cognitive Modeling and Computational Linguistics (CMCL)](https://md.research.elamur.ai/free/en/venues/cmcl/)**Sara Møller Østergaard, Kenneth Enevoldsen, Afra Alishahi, et al.*2026*

206 more citing papers of our library have no page here yet.

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