🔗 Who cites «An Information-theoretic Approach to Prompt Engineering Without Ground Truth Labels»

69 papers of our library cite it (of the 141,840 whose bibliographies we read) · 6 with a page here, the most cited first · ← back to «An Information-theoretic Approach to Prompt Engineering Without Ground Truth Labels»

1. A Survey on In-context LearningarXiv:2301.00234Qingxiu Dong, Lei Li, Damai Dai, et al.2023 · 959 citations
   Security and Privacy Challenges of Large Language Models: A SurveyACM Computing SurveysBadhan Chandra Das, M. Hadi Amini, Yanzhao Wu2024 · 422 citations
2. Prompting Large Language Model for Machine Translation: A Case StudyarXiv:2301.07069Biao Zhang, Barry Haddow, Alexandra Birch2023 · 293 citations
3. The Prompt Report: A Systematic Survey of Prompt Engineering TechniquesarXiv:2406.06608Sander Schulhoff, Michael Ilie, Nishant Balepur, et al.2024 · 187 citations
4. Leveraging Large Language Models for Multiple Choice Question AnsweringarXiv:2210.12353Joshua Robinson, Christopher Michael Rytting, David Wingate2022 · 157 citations
   Mitigating Label Biases for In-context LearningAnnual Meeting of the Association for Computational Linguistics (ACL)Yu Fei, Yifan Hou, Zeming Chen, et al.2023 · 79 citations

63 more papers of our library cite it; they have no page here yet.

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