--- title: "Who cites Unraveling the Mechanics of — 9 citing papers" description: "9 papers of the Elamur Research library cite «Unraveling the Mechanics of Learning-Based Demonstration Selection for In-Context Learning»…" canonical: "https://research.elamur.ai/free/en/papers/liu-2025-unraveling-mechanics-learning-based-demonstration/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/liu-2025-unraveling-mechanics-learning-based-demonstration/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Unraveling the Mechanics of Learning-Based…](https://md.research.elamur.ai/free/en/papers/liu-2025-unraveling-mechanics-learning-based-demonstration/) / cited by # Who cites «Unraveling the Mechanics of Learning-Based Demonstration Selection for In-Context Learning» 9 papers of our library cite it (of the 149,439 whose bibliographies we read) · 2 with a page here, the most cited first · [← back to «Unraveling the Mechanics of Learning-Based Demonstration Selection for In-Context Learning»](https://md.research.elamur.ai/free/en/papers/liu-2025-unraveling-mechanics-learning-based-demonstration/) 1. **[Incomplete In-context Learning](https://md.research.elamur.ai/free/en/papers/wang-2026-incomplete-context-learning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenqiang Wang, Wen Yujia, Yan Xiao, et al.*2026 · 2 citations* 2. **[Domain-Specific Data Generation Framework for RAG Adaptation](https://md.research.elamur.ai/free/en/papers/tian-2026-domain-specific-data-generation-framework/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chris Xing Tian, Weihao Xie, Zhen Chen, et al.*2026* 7 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/liu-2025-unraveling-mechanics-learning-based-demonstration/) — Unraveling the Mechanics of Learning-Based Demonstration Selection for In-Context Learning