🧑‍🔬 Who cites Filip Ilievski

129 citations of their works from 127 papers of our library (of the 149,439 whose bibliographies we read) · 18 with a page here, the most cited first · ← Filip Ilievski

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. ChatGPT Is a Knowledgeable but Inexperienced Solver: An Investigation of Commonsense Problem in Large Language ModelsLanguage Resources and Evaluation Conference (LREC)Ning Bian, Xianpei Han, Le Sun, et al.2024 · 106 citations
7. Teaching Algorithmic Reasoning via In-context LearningarXiv:2211.09066Hattie Zhou, Azade Nova, Hugo Larochelle, et al.2022 · 96 citations
8. Investigating the Limitations of Transformers with Simple Arithmetic TasksarXiv:2102.13019Rodrigo Nogueira, Zhiying Jiang, Jimmy Lin2021 · 96 citations
9. 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
10. 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
11. Getting the most out of your tokenizer for pre-training and domain adaptationarXiv:2402.01035Gautier Dagan, Gabriel Synnaeve, Baptiste Roziere2024 · 47 citations
12. 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
13. Evaluating Transformer Language Models on Arithmetic Operations Using Number DecompositionLanguage Resources and Evaluation Conference (LREC)Matteo Muffo, Aldo Cocco, Enrico Bertino2022 · 19 citations
14. LiTEx: A Linguistic Taxonomy of Explanations for Understanding Within-Label Variation in Natural Language InferenceConference on Empirical Methods in Natural Language Processing (EMNLP)Pingjun Hong, Beiduo Chen, Siyao Peng, et al.2025 · 8 citations
15. 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
16. Social Perceptions of English Spelling Variation on Twitter: A Comparative Analysis of Human and LLM ResponsesarXiv:2511.23041Dong Nguyen, Laura Rosseel2025
17. 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
18. Survey on Commonsense Question Answering (常识问答研究综述)Journal of SoftwareYifan Fan (范怡帆), Bowei Zou (邹博伟), Qingting Xu (徐庆婷), et al.2023

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