--- title: "Who cites SeaKR: Self-aware Knowledge — 29 citing papers" description: "29 papers of the Elamur Research library cite «SeaKR: Self-aware Knowledge Retrieval for Adaptive Retrieval Augmented Generation»…" canonical: "https://research.elamur.ai/free/en/papers/yao-2025-seakr-self-aware-knowledge-retrieval/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/yao-2025-seakr-self-aware-knowledge-retrieval/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [SeaKR: Self-aware Knowledge Retrieval for…](https://md.research.elamur.ai/free/en/papers/yao-2025-seakr-self-aware-knowledge-retrieval/) / cited by # Who cites «SeaKR: Self-aware Knowledge Retrieval for Adaptive Retrieval Augmented Generation» 29 papers of our library cite it (of the 149,439 whose bibliographies we read) · 10 with a page here, the most cited first · [← back to «SeaKR: Self-aware Knowledge Retrieval for Adaptive Retrieval Augmented Generation»](https://md.research.elamur.ai/free/en/papers/yao-2025-seakr-self-aware-knowledge-retrieval/) 1. [**Retrieval-Augmented Generation with Graphs (GraphRAG) arXiv:2501.00309**Haoyu Han, Yu Wang, Harry Shomer, et al.*2025 · 87 citations*](https://md.research.elamur.ai/free/en/papers/han-2025-retrieval-augmented-generation-graphs-graphrag/) 2. **[Knowledge Boundary of Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/li-2025-knowledge-boundary-large-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Moxin Li, Yong Zhao, Wenxuan Zhang, et al.*2025 · 30 citations* 3. **[Adaptive Retrieval Without Self-Knowledge? Bringing Uncertainty Back Home](https://md.research.elamur.ai/free/en/papers/moskvoretskii-2025-adaptive-retrieval-without-self-knowledge/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Viktor Moskvoretskii, Maria Marina, Mikhail Salnikov, et al.*2025 · 21 citations* 4. **[Test-time Corpus Feedback: From Retrieval to RAG](https://md.research.elamur.ai/free/en/papers/rathee-2026-test-time-corpus-feedback-retrieval/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mandeep Rathee, Venktesh V, Sean MacAvaney, et al.*2026 · 4 citations* 5. **[UniversalRAG: Retrieval-Augmented Generation over Corpora of Diverse Modalities and Granularities](https://md.research.elamur.ai/free/en/papers/yeo-2026-universalrag-retrieval-augmented-generation-over/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Woongyeong Yeo, Kangsan Kim, Soyeong Jeong, et al.*2026 · 4 citations* 6. **[QuCo-RAG: Quantifying Uncertainty from the Pre-training Corpus for Dynamic Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/min-2026-quco-rag-quantifying-uncertainty-pre/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Dehai Min, Kailin Zhang, Tongtong Wu, et al.*2026 · 2 citations* 7. **[ACR: Adaptive Context Refactoring via Context Refactoring Operators for Multi-Turn Dialogue](https://md.research.elamur.ai/free/en/papers/shen-2026-acr-adaptive-context-refactoring-context/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiawei Shen, Jia Zhu, Hanghui Guo, et al.*2026* 8. **[CIRAG: Construction–Integration Retrieval and Adaptive Generation for Multi-hop Question Answering](https://md.research.elamur.ai/free/en/papers/wei-2026-cirag-construction-integration-retrieval-adaptive/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zili Wei, Yilin Wang, Xiaocui Yang, et al.*2026* 9. **[LCR-RAG: Enhancing Logical Consistency in Retrieval-Augmented Generation via Neuro-symbolic Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/zheng-2026-lcr-rag-enhancing-logical-consistency/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenxiang Zheng, Guo Tang, Shixin Jiang, et al.*2026* 10. **[RAG in the Wild: On the (In)effectiveness of LLMs with Mixture-of-Knowledge Retrieval Augmentation](https://md.research.elamur.ai/free/en/papers/xu-2026-rag-wild-effectiveness-llms-mixture/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ran Xu, Yuchen Zhuang, Yue Yu, et al.*2026* 19 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/yao-2025-seakr-self-aware-knowledge-retrieval/) — SeaKR: Self-aware Knowledge Retrieval for Adaptive Retrieval Augmented Generation