--- title: "Who cites Compositional Exemplars for In-context Learning" description: "96 papers of the Elamur Research library cite «Compositional Exemplars for In-context Learning», found in their bibliographies; the most cited first." canonical: "https://research.elamur.ai/free/en/papers/ye-2023-compositional-exemplars-context-learning/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/ye-2023-compositional-exemplars-context-learning/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Compositional Exemplars for In-context Learning](https://md.research.elamur.ai/free/en/papers/ye-2023-compositional-exemplars-context-learning/) / cited by # Who cites «Compositional Exemplars for In-context Learning» 96 papers of our library cite it (of the 149,439 whose bibliographies we read) · 17 with a page here, the most cited first · [← back to «Compositional Exemplars for In-context Learning»](https://md.research.elamur.ai/free/en/papers/ye-2023-compositional-exemplars-context-learning/) 1. **[A Survey on RAG Meeting LLMs: Towards Retrieval-Augmented Large Language Models](https://md.research.elamur.ai/free/en/papers/fan-2024-survey-rag-meeting-llms-towards/) [ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)](https://md.research.elamur.ai/free/en/venues/acm-sigkdd-conference-on-knowledge-discovery-and-data-mining-kdd/)**Wenqi Fan; Yujuan Ding; Liangbo Ning; Shijie Wang; Hengyun Li; Dawei Yin; Tat-Seng Chua;, Qing Li*2024 · 1,010 citations* 2. [**A Survey on In-context Learning arXiv:2301.00234**Qingxiu Dong, Lei Li, Damai Dai, et al.*2023 · 978 citations*](https://md.research.elamur.ai/free/en/papers/dong-2023-survey-context-learning/) 3. **[Label Words are Anchors: An Information Flow Perspective for Understanding In-Context Learning](https://md.research.elamur.ai/free/en/papers/wang-2023-label-words-anchors-information-flow/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Lean Wang, Lei Li, Damai Dai, et al.*2023 · 153 citations* 4. **[Learning to Retrieve In-Context Examples for Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2024-learning-retrieve-context-examples-large/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Liang Wang, Nan Yang, Furu Wei*2024 · 106 citations* 5. [**A Survey on Data Selection for Language Models arXiv:2402.16827**Alon Albalak, Yanai Elazar, Sang Michael Xie, et al.*2024 · 95 citations*](https://md.research.elamur.ai/free/en/papers/albalak-2024-survey-data-selection-language-models/) 6. **[Finding Support Examples for In-Context Learning](https://md.research.elamur.ai/free/en/papers/li-2023-finding-support-examples-context-learning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiaonan Li, Xipeng Qiu*2023 · 78 citations* 7. **[Sensitivity, Performance, Robustness: Deconstructing the Effect of Sociodemographic Prompting](https://md.research.elamur.ai/free/en/papers/beck-2024-sensitivity-performance-robustness-deconstructing-effect/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Tilman Beck, Hendrik Schuff, Anne Lauscher, et al.*2024 · 69 citations* 8. [**In-context Learning with Retrieved Demonstrations for Language Models: A Survey arXiv:2401.11624**Man Luo, Xin Xu, Yue Liu, et al.*2024 · 54 citations*](https://md.research.elamur.ai/free/en/papers/luo-2024-context-learning-retrieved-demonstrations-language/) 9. **[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* 10. [**DQ-LoRe: Dual Queries with Low Rank Approximation Re-ranking for In-Context Learning arXiv:2310.02954**Jing Xiong, Zixuan Li, Chuanyang Zheng, et al.*2023 · 27 citations*](https://md.research.elamur.ai/free/en/papers/xiong-2023-dq-lore-dual-queries-low/) 11. **[SKIntern: Internalizing Symbolic Knowledge for Distilling Better CoT Capabilities into Small Language Models](https://md.research.elamur.ai/free/en/papers/liao-2025-skintern-internalizing-symbolic-knowledge-distilling/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Huanxuan Liao, Shizhu He, Yupu Hao, et al.*2025 · 12 citations* 12. **[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/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hui Liu, Wenya Wang, Hao Sun, et al.*2025 · 11 citations* 13. **[Enhancing the Safety of Medical Vision-Language Models by Synthetic Demonstrations](https://md.research.elamur.ai/free/en/papers/xue-2026-enhancing-safety-medical-vision-language/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Zhiyu Xue, Reza Abbasi-Asl, Ramtin Pedarsani*2026 · 1 citation* 14. **[Distilling Examples into Task Instructions: Enhanced In-Context Learning for Real-World B2B Conversations](https://md.research.elamur.ai/free/en/papers/rotman-2026-distilling-examples-into-task-instructions/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Guy Rotman, Adi Kopilov, Danit Berger Zalmanson, et al.*2026* 15. **[Task-Related In-Context Learning](https://md.research.elamur.ai/free/en/papers/wang-2026-task-related-context-learning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenqiang Wang, Peng Chen, Yan Xiao, et al.*2026* 16. **[Toward Robust In-Context Learning: Leveraging Out-of-distribution Proxies for Target Inaccessible Demonstration Retrieval](https://md.research.elamur.ai/free/en/papers/xu-2026-robust-context-learning-leveraging-out/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hao Xu, Rite Bo, Fausto Giunchiglia, et al.*2026* 17. **[UCS: Estimating Unseen Coverage for Improved In-Context Learning](https://md.research.elamur.ai/free/en/papers/xin-2026-ucs-estimating-unseen-coverage-improved/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiayi Xin, Xiang Li, Evan Qiang, et al.*2026* 79 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/ye-2023-compositional-exemplars-context-learning/) — Compositional Exemplars for In-context Learning