🧑‍🔬 Who cites Jared Fernandez

135 citations of their works from 134 papers of our library (of the 141,840 whose bibliographies we read) · 23 with a page here, the most cited first · ← Jared Fernandez

1. Recent Advances in Natural Language Processing via Large Pre-Trained Language Models: A SurveyACM Computing SurveysBonan Min, Hayley Ross, Elior Sulem, et al.2021 · 1,552 citations
2. BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and GenerationarXiv:2201.12086Junnan Li, Dongxu Li, Caiming Xiong, et al.2022 · 1,469 citations
3. Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?Conference on Empirical Methods in Natural Language Processing (EMNLP)Sewon Min, Xinxi Lyu, Ari Holtzman, et al.2022 · 1,425 citations
4. A Survey of Data Augmentation Approaches for NLParXiv:2105.03075Steven Y. Feng, Varun Gangal, Jason Wei, et al.2021 · 937 citations
5. True Few-Shot Learning with Language ModelsarXiv:2105.11447Ethan Perez, Douwe Kiela, Kyunghyun Cho2021 · 404 citations
6. Unnatural Instructions: Tuning Language Models with (Almost) No Human LaborAnnual Meeting of the Association for Computational Linguistics (ACL)Or Honovich, Thomas Scialom, Omer Levy, et al.2023 · 358 citations
7. Symbolic Knowledge Distillation: from General Language Models to Commonsense ModelsConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Peter West, Chandra Bhagavatula, Jack Hessel, et al.2022 · 344 citations
8. An Empirical Survey of Data Augmentation for Limited Data Learning in NLPTransactions of the Association for Computational Linguistics (TACL)Jiaao Chen, Derek Tam, Colin Raffel, et al.2023 · 253 citations
9. Generating Datasets with Pretrained Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Timo Schick, Hinrich Schutze2021 · 250 citations
10. Generating Training Data with Language Models: Towards Zero-Shot Language UnderstandingarXiv:2202.04538Yu Meng, Jiaxin Huang, Yu Zhang, et al.2022 · 207 citations
11. Generative Data Augmentation for Commonsense ReasoningFindings of the Association for Computational LinguisticsYiben Yang, Chaitanya Malaviya, Jared Fernandez, et al.2020 · 195 citations
12. Explanations for CommonsenseQA: New Dataset and ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Shourya Aggarwal, Divyanshu Mandowara, Vishwajeet Agrawal, et al.2021 · 163 citations
13. Leveraging Large Language Models for Multiple Choice Question AnsweringarXiv:2210.12353Joshua Robinson, Christopher Michael Rytting, David Wingate2022 · 157 citations
14. Revisiting DocRED - Addressing the False Negative Problem in Relation ExtractionConference on Empirical Methods in Natural Language Processing (EMNLP)Qingyu Tan, Lu Xu, Lidong Bing, et al.2022 · 151 citations
15. Is GPT-3 a Good Data Annotator?arXiv:2212.10450Bosheng Ding, Chengwei Qin, Linlin Liu, et al.2022 · 145 citations
16. Common Sense Beyond English: Evaluating and Improving Multilingual Language Models for Commonsense ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Bill Yuchen Lin, Seyeon Lee, Xiaoyang Qiao, et al.2021 · 106 citations
17. Generating Data to Mitigate Spurious Correlations in Natural Language Inference DatasetsAnnual Meeting of the Association for Computational Linguistics (ACL)Yuxiang Wu, Matt Gardner, Pontus Stenetorp, et al.2022 · 98 citations
18. English Machine Reading Comprehension Datasets: A SurveyDaria Dzendzik, Jennifer Foster, Carl Vogel2021 · 54 citations
19. Coreference Reasoning in Machine Reading ComprehensionAnnual Meeting of the Association for Computational Linguistics (ACL)Mingzhu Wu, Nafise Sadat Moosavi, Dan Roth, et al.2021 · 11 citations
20. An Empirical Study of Synthetic Data Generation for Implicit Discourse Relation RecognitionLanguage Resources and Evaluation Conference (LREC)Kazumasa Omura, Fei Cheng, Sadao Kurohashi2024 · 8 citations
21. SC-Ques: A Sentence Completion Question Dataset for English as a Second Language LearnersLecture notes in computer scienceQiongqiong Liu, Yaying Huang, Zitao Liu, et al.2022 · 1 citation
22. EIFFEL: a novel benchmark to measure bias of English heavy training on French idiomatic expressionsAnnual Meeting of the Association for Computational Linguistics (ACL)Charlotte Noel, Nicholas Asher, Olivier Gouvert, et al.2026
23. Generation of Instruction and Preference Dataset for Improving Japanese Instruction Following in LLMsLanguage Resources and Evaluation Conference (LREC)Kei Moriyama, Takashi Kodama, Kouta Nakayama2026

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