---
title: "Who cites Dense X Retrieval: What Retrieval — 70 citing papers"
description: "70 papers of the Elamur Research library cite «Dense X Retrieval: What Retrieval Granularity Should We Use?», found in their bibliographies…"
canonical: "https://research.elamur.ai/free/en/papers/chen-2024-dense-x-retrieval-what-retrieval/cited-by/"
---
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# Who cites «Dense X Retrieval: What Retrieval Granularity Should We Use?»

70 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 «Dense X Retrieval: What Retrieval Granularity Should We Use?»](https://md.research.elamur.ai/free/en/papers/chen-2024-dense-x-retrieval-what-retrieval/)

1. [**Retrieval-Augmented Generation for Large Language Models: A Survey arXiv:2312.10997**Yunfan Gao, Yun Xiong, Xinyu Gao, et al.*2023 · 1,648 citations*](https://md.research.elamur.ai/free/en/papers/gao-2023-retrieval-augmented-generation-large-language/) **[HippoRAG: Neurobiologically Inspired Long-Term Memory for Large Language Models](https://md.research.elamur.ai/free/en/papers/gutierrez-2024-hipporag-neurobiologically-inspired-long-term/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Bernal Jimenez Gutierrez, Yiheng Shu, Yu Gu, et al.*2024 · 264 citations* [**LongMemEval: Benchmarking Chat Assistants on Long-Term Interactive Memory arXiv:2410.10813**Di Wu, Hongwei Wang, Wenhao Yu, et al.*2024 · 91 citations*](https://md.research.elamur.ai/free/en/papers/wu-2024-longmemeval-benchmarking-chat-assistants-long/) **[From Articles to Premises: Building PrimeFacts, an Extraction Methodology and Resource for Fact-Checking Evidence](https://md.research.elamur.ai/free/en/papers/sahitaj-2026-articles-premises-building-primefacts-extraction/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Premtim Sahitaj, Jawan Kolanowski, Ariana Sahitaj, et al.*2026 · 1 citation* **[Bounded Conversational Memory with Hybrid Retrieval and Evidence Highlighting for Multi-Session Dialogue Systems](https://md.research.elamur.ai/free/en/papers/mudunuri-2026-bounded-conversational-memory-hybrid-retrieval/) [Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL)](https://md.research.elamur.ai/free/en/venues/sigdial/)**Manasa Mudunuri, Chandra Kiran Guntupalli, Shiraj Pokharel, et al.*2026*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/chen-2024-dense-x-retrieval-what-retrieval/) — Dense X Retrieval: What Retrieval Granularity Should We Use?