🔗 Who cites «Representing Numbers in NLP: a Survey and a Vision»

64 papers of our library cite it (of the 149,439 whose bibliographies we read) · 14 with a page here, the most cited first · ← back to «Representing Numbers in NLP: a Survey and a Vision»

1. Survey of Hallucination in Natural Language GenerationACM Computing SurveysZiwei Ji, Nayeon Lee, Rita Frieske, et al.2022 · 5,974 citations
2. Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language modelsarXiv:2206.04615 · Transactions on Machine Learning Research, May/2022, https://openreview.net/forum?id=uyTL5BvosjAarohi Srivastava, Abhinav Rastogi, Abhishek Rao, et al.2022 · 1,756 citations
3. Impact of Pretraining Term Frequencies on Few-Shot Numerical ReasoningFindings of the Association for Computational LinguisticsYasaman Razeghi, Robert L Logan IV, Matt Gardner, et al.2022 · 165 citations
4. How does GPT-2 compute greater-than?: Interpreting mathematical abilities in a pre-trained language modelConference on Neural Information Processing Systems (NeurIPS)Michael Hanna, Ollie Liu, Alexandre Variengien2023 · 151 citations
5. HiTab: A Hierarchical Table Dataset for Question Answering and Natural Language GenerationarXiv:2108.06712Zhoujun Cheng, Haoyu Dong, Zhiruo Wang, et al.2021 · 108 citations
6. Teaching Algorithmic Reasoning via In-context LearningarXiv:2211.09066Hattie Zhou, Azade Nova, Hugo Larochelle, et al.2022 · 96 citations
7. Investigating the Limitations of Transformers with Simple Arithmetic TasksarXiv:2102.13019Rodrigo Nogueira, Zhiying Jiang, Jimmy Lin2021 · 96 citations
8. A Causal Framework to Quantify the Robustness of Mathematical Reasoning with Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Alessandro Stolfo, Zhijing Jin, Kumar Shridhar, et al.2023 · 65 citations
9. MLCopilot: Unleashing the Power of Large Language Models in Solving Machine Learning TasksConference of the European Chapter of the Association for Computational Linguistics (EACL)Lei Zhang, Yuge Zhang, Kan Ren, et al.2024 · 52 citations
10. Getting the most out of your tokenizer for pre-training and domain adaptationarXiv:2402.01035Gautier Dagan, Gabriel Synnaeve, Baptiste Roziere2024 · 47 citations
11. Exploring the Numerical Reasoning Capabilities of Language Models: A Comprehensive Analysis on Tabular DataFindings of the Association for Computational LinguisticsMubashara Akhtar, Abhilash Shankarampeta, Vivek Gupta, et al.2023 · 38 citations
12. Evaluating Transformer Language Models on Arithmetic Operations Using Number DecompositionLanguage Resources and Evaluation Conference (LREC)Matteo Muffo, Aldo Cocco, Enrico Bertino2022 · 19 citations
13. Evaluating Numeracy of Language Models as a Natural Language Inference TaskFindings of the Association for Computational LinguisticsRahmad Mahendra, Damiano Spina, Lawrence Cavedon, et al.2025 · 4 citations
14. Survey on Hallucinations in Large Language Models (大语言模型的幻觉问题研究综述)Journal of SoftwareZeyuan Liu (刘泽垣), Pengjiang Wang (王鹏江), Xiaobin Song (宋晓斌), et al.2024

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

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