🔗 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»

1. A Survey of Large Language ModelsFrontiers of Computer ScienceWayne Xin Zhao, Kun Zhou, Junyi Li, et al.2023 · 2,875 citations
2. A Survey on In-context LearningarXiv:2301.00234Qingxiu Dong, Lei Li, Damai Dai, et al.2023 · 978 citations
3. LongLLMLingua: Accelerating and Enhancing LLMs in Long Context Scenarios via Prompt CompressionarXiv:2310.06839Huiqiang Jiang, Qianhui Wu, Xufang Luo, et al.2023 · 158 citations
4. Are Large Language Models Really Good Logical Reasoners? A Comprehensive Evaluation and BeyondIEEE Transactions on Knowledge and Data EngineeringFangzhi Xu, Qika Lin, Jiawei Han, et al.2023 · 142 citations
5. Long-context LLMs Struggle with Long In-context LearningarXiv:2404.02060Tianle Li, Ge Zhang, Quy Duc Do, et al.2024 · 138 citations
6. Compositional Exemplars for In-context LearningarXiv:2302.05698Jiacheng Ye, Zhiyong Wu, Jiangtao Feng, et al.2023 · 120 citations
7. INSTRUCTEVAL: Towards Holistic Evaluation of Instruction-Tuned Large Language ModelsarXiv:2306.04757Yew Ken Chia, Pengfei Hong, Lidong Bing, et al.2023 · 96 citations
8. Finding Support Examples for In-Context LearningFindings of the Association for Computational LinguisticsXiaonan Li, Xipeng Qiu2023 · 78 citations
9. OS-Copilot: Towards Generalist Computer Agents with Self-ImprovementarXiv:2402.07456Zhiyong Wu, Chengcheng Han, Zichen Ding, et al.2024 · 61 citations
10. MCS-SQL: Leveraging Multiple Prompts and Multiple-Choice Selection For Text-to-SQL GenerationInternational Conference on Computational Linguistics (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 ModelsarXiv:2309.06085Wei Qi Leong, Jian Gang Ngui, Yosephine Susanto, et al.2023 · 33 citations
12. TACO: Enhancing Multimodal In-context Learning via Task Mapping-Guided Sequence ConfigurationConference on Empirical Methods in Natural Language Processing (EMNLP)Yanshu Li, Jianjiang Yang, Tian Yun, et al.2025 · 22 citations
13. Automatic Combination of Sample Selection Strategies for Few-Shot LearningFindings of the Association for Computational LinguisticsBranislav Pecher, Ivan Srba, Maria Bielikova, et al.2026 · 15 citations
14. Incomplete In-context LearningAnnual Meeting of the Association for Computational Linguistics (ACL)Wenqiang Wang, Wen Yujia, Yan Xiao, et al.2026 · 2 citations
15. Enhancing the Safety of Medical Vision-Language Models by Synthetic DemonstrationsConference of the European Chapter of the Association for Computational Linguistics (EACL)Zhiyu Xue, Reza Abbasi-Asl, Ramtin Pedarsani2026 · 1 citation
16. From Fake to Real: Mitigating Out-of-Distribution Bias in In-Context Learning via Feedback Supervision from Large Language ModelsFindings of the Association for Computational LinguisticsRui Song, Yingji Li, Jian Li, et al.2026
17. Task-Related In-Context LearningFindings of the Association for Computational LinguisticsWenqiang Wang, Peng Chen, Yan Xiao, et al.2026
18. UCS: Estimating Unseen Coverage for Improved In-Context LearningFindings of the Association for Computational LinguisticsJiayi Xin, Xiang Li, Evan Qiang, et al.2026

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