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Who cites «“According to . . . “: Prompting Language Models Improves Quoting from Pre-Training Data»

41 papers of our library cite it (of the 149,439 whose bibliographies we read) · 9 with a page here, the most cited first · ← back to «“According to . . . “: Prompting Language Models Improves Quoting from Pre-Training Data»

  1. LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for CodearXiv:2403.07974Naman Jain, King Han, Alex Gu, et al.2024 · 578 citations
  2. Can LLMs Generate Novel Research Ideas? A Large-Scale Human Study with 100+ NLP ResearchersarXiv:2409.04109Chenglei Si, Diyi Yang, Tatsunori Hashimoto2024 · 196 citations
  3. Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-SpecificityarXiv:2310.07521Cunxiang Wang, Xiaoze Liu, Yuanhao Yue, et al.2023 · 171 citations
  4. In-context Learning with Retrieved Demonstrations for Language Models: A SurveyarXiv:2401.11624Man Luo, Xin Xu, Yue Liu, et al.2024 · 54 citations
  5. Source-Aware Training Enables Knowledge Attribution in Language ModelsarXiv:2404.01019Muhammad Khalifa, David Wadden, Emma Strubell, et al.2024 · 21 citations

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

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