--- title: "Who cites Self-Adaptive In-Context — 87 citing papers" description: "87 papers of the Elamur Research library cite «Self-Adaptive In-Context Learning: An Information Compression Perspective for In-Context…" canonical: "https://research.elamur.ai/free/en/papers/wu-2022-self-adaptive-context-learning-information/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/wu-2022-self-adaptive-context-learning-information/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Self-Adaptive In-Context Learning: An Information…](https://md.research.elamur.ai/free/en/papers/wu-2022-self-adaptive-context-learning-information/) / cited by # Who cites «Self-Adaptive In-Context Learning: An Information Compression Perspective for In-Context Example Selection and Ordering» 87 papers of our library cite it (of the 149,439 whose bibliographies we read) · 18 with a page here, the most cited first · [← back to «Self-Adaptive In-Context Learning: An Information Compression Perspective for In-Context Example Selection and Ordering»](https://md.research.elamur.ai/free/en/papers/wu-2022-self-adaptive-context-learning-information/) 1. **[A Survey of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhao-2023-survey-large-language-models/) [Frontiers of Computer Science](https://md.research.elamur.ai/free/en/venues/frontiers-of-computer-science/)**Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.*2023 · 2,875 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. [**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/) 4. **[Are Large Language Models Really Good Logical Reasoners? A Comprehensive Evaluation and Beyond](https://md.research.elamur.ai/free/en/papers/xu-2023-large-language-models-really-good/) [IEEE Transactions on Knowledge and Data Engineering](https://md.research.elamur.ai/free/en/venues/ieee-transactions-on-knowledge-and-data-engineering/)**Fangzhi Xu, Qika Lin, Jiawei Han, et al.*2023 · 142 citations* 5. [**Long-context LLMs Struggle with Long In-context Learning arXiv:2404.02060**Tianle Li, Ge Zhang, Quy Duc Do, et al.*2024 · 138 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-long-context-llms-struggle-long/) 6. [**Compositional Exemplars for In-context Learning arXiv:2302.05698**Jiacheng Ye, Zhiyong Wu, Jiangtao Feng, et al.*2023 · 120 citations*](https://md.research.elamur.ai/free/en/papers/ye-2023-compositional-exemplars-context-learning/) 7. [**INSTRUCTEVAL: Towards Holistic Evaluation of Instruction-Tuned Large Language Models arXiv:2306.04757**Yew Ken Chia, Pengfei Hong, Lidong Bing, et al.*2023 · 96 citations*](https://md.research.elamur.ai/free/en/papers/chia-2023-instructeval-towards-holistic-evaluation-instruction/) 8. **[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* 9. [**OS-Copilot: Towards Generalist Computer Agents with Self-Improvement arXiv:2402.07456**Zhiyong Wu, Chengcheng Han, Zichen Ding, et al.*2024 · 61 citations*](https://md.research.elamur.ai/free/en/papers/wu-2024-os-copilot-towards-generalist-computer/) 10. **[MCS-SQL: Leveraging Multiple Prompts and Multiple-Choice Selection For Text-to-SQL Generation](https://md.research.elamur.ai/free/en/papers/lee-2025-mcs-sql-leveraging-multiple-prompts/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Dongjun Lee, Choongwon Park, Jaehyuk Kim, et al.*2025 · 42 citations* 11. [**BHASA: A Holistic Southeast Asian Linguistic and Cultural Evaluation Suite for Large Language Models arXiv:2309.06085**Wei Qi Leong, Jian Gang Ngui, Yosephine Susanto, et al.*2023 · 33 citations*](https://md.research.elamur.ai/free/en/papers/leong-2023-bhasa-holistic-southeast-asian-linguistic/) 12. **[TACO: Enhancing Multimodal In-context Learning via Task Mapping-Guided Sequence Configuration](https://md.research.elamur.ai/free/en/papers/li-2025-taco-enhancing-multimodal-context-learning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yanshu Li, Jianjiang Yang, Tian Yun, et al.*2025 · 22 citations* 13. **[Automatic Combination of Sample Selection Strategies for Few-Shot Learning](https://md.research.elamur.ai/free/en/papers/pecher-2026-automatic-combination-sample-selection-strategies/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Branislav Pecher, Ivan Srba, Maria Bielikova, et al.*2026 · 15 citations* 14. **[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* 15. **[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* 16. **[From Fake to Real: Mitigating Out-of-Distribution Bias in In-Context Learning via Feedback Supervision from Large Language Models](https://md.research.elamur.ai/free/en/papers/song-2026-fake-real-mitigating-out-distribution/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Rui Song, Yingji Li, Jian Li, et al.*2026* 17. **[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* 18. **[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* 69 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/wu-2022-self-adaptive-context-learning-information/) — Self-Adaptive In-Context Learning: An Information Compression Perspective for In-Context Example Selection and Ordering