---
title: "Who cites Jared Fernandez — 134 papers of our library"
description: "134 papers of the Elamur Research library cite the works of Jared Fernandez, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/jared-fernandez/cited-by/"
---
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# 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](https://md.research.elamur.ai/free/en/authors/jared-fernandez/)

1. **[Recent Advances in Natural Language Processing via Large Pre-Trained Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/min-2021-recent-advances-natural-language-processing/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Bonan Min, Hayley Ross, Elior Sulem, et al.*2021 · 1,552 citations*
2. [**BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation arXiv:2201.12086**Junnan Li, Dongxu Li, Caiming Xiong, et al.*2022 · 1,469 citations*](https://md.research.elamur.ai/free/en/papers/li-2022-blip-bootstrapping-language-image-pre/)
3. **[Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?](https://md.research.elamur.ai/free/en/papers/min-2022-rethinking-role-demonstrations-what-makes/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Sewon Min, Xinxi Lyu, Ari Holtzman, et al.*2022 · 1,425 citations*
4. [**A Survey of Data Augmentation Approaches for NLP arXiv:2105.03075**Steven Y. Feng, Varun Gangal, Jason Wei, et al.*2021 · 937 citations*](https://md.research.elamur.ai/free/en/papers/feng-2021-survey-data-augmentation-approaches-nlp/)
5. [**True Few-Shot Learning with Language Models arXiv:2105.11447**Ethan Perez, Douwe Kiela, Kyunghyun Cho*2021 · 404 citations*](https://md.research.elamur.ai/free/en/papers/perez-2021-true-few-shot-learning-language/)
6. **[Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor](https://md.research.elamur.ai/free/en/papers/honovich-2023-unnatural-instructions-tuning-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Or Honovich, Thomas Scialom, Omer Levy, et al.*2023 · 358 citations*
7. **[Symbolic Knowledge Distillation: from General Language Models to Commonsense Models](https://md.research.elamur.ai/free/en/papers/west-2022-symbolic-knowledge-distillation-general-language/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Peter West, Chandra Bhagavatula, Jack Hessel, et al.*2022 · 344 citations*
8. **[An Empirical Survey of Data Augmentation for Limited Data Learning in NLP](https://md.research.elamur.ai/free/en/papers/chen-2023-empirical-survey-data-augmentation-limited/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Jiaao Chen, Derek Tam, Colin Raffel, et al.*2023 · 253 citations*
9. **[Generating Datasets with Pretrained Language Models](https://md.research.elamur.ai/free/en/papers/schick-2021-generating-datasets-pretrained-language-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Timo Schick, Hinrich Schutze*2021 · 250 citations*
10. [**Generating Training Data with Language Models: Towards Zero-Shot Language Understanding arXiv:2202.04538**Yu Meng, Jiaxin Huang, Yu Zhang, et al.*2022 · 207 citations*](https://md.research.elamur.ai/free/en/papers/meng-2022-generating-training-data-language-models/)
11. **[Generative Data Augmentation for Commonsense Reasoning](https://md.research.elamur.ai/free/en/papers/yang-2020-generative-data-augmentation-commonsense-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yiben Yang, Chaitanya Malaviya, Jared Fernandez, et al.*2020 · 195 citations*
12. **[Explanations for CommonsenseQA: New Dataset and Models](https://md.research.elamur.ai/free/en/papers/aggarwal-2021-explanations-commonsenseqa-new-dataset-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shourya Aggarwal, Divyanshu Mandowara, Vishwajeet Agrawal, et al.*2021 · 163 citations*
13. [**Leveraging Large Language Models for Multiple Choice Question Answering arXiv:2210.12353**Joshua Robinson, Christopher Michael Rytting, David Wingate*2022 · 157 citations*](https://md.research.elamur.ai/free/en/papers/robinson-2022-leveraging-large-language-models-multiple/)
14. **[Revisiting DocRED - Addressing the False Negative Problem in Relation Extraction](https://md.research.elamur.ai/free/en/papers/tan-2022-revisiting-docred-addressing-false-negative/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Qingyu Tan, Lu Xu, Lidong Bing, et al.*2022 · 151 citations*
15. [**Is GPT-3 a Good Data Annotator? arXiv:2212.10450**Bosheng Ding, Chengwei Qin, Linlin Liu, et al.*2022 · 145 citations*](https://md.research.elamur.ai/free/en/papers/ding-2022-gpt-3-good-data-annotator/)
16. **[Common Sense Beyond English: Evaluating and Improving Multilingual Language Models for Commonsense Reasoning](https://md.research.elamur.ai/free/en/papers/lin-2021-common-sense-beyond-english-evaluating/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bill Yuchen Lin, Seyeon Lee, Xiaoyang Qiao, et al.*2021 · 106 citations*
17. **[Generating Data to Mitigate Spurious Correlations in Natural Language Inference Datasets](https://md.research.elamur.ai/free/en/papers/wu-2022-generating-data-mitigate-spurious-correlations/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuxiang Wu, Matt Gardner, Pontus Stenetorp, et al.*2022 · 98 citations*
18. [**English Machine Reading Comprehension Datasets: A Survey**Daria Dzendzik, Jennifer Foster, Carl Vogel*2021 · 54 citations*](https://md.research.elamur.ai/free/en/papers/dzendzik-2021-english-machine-reading-comprehension-datasets/)
19. **[Coreference Reasoning in Machine Reading Comprehension](https://md.research.elamur.ai/free/en/papers/wu-2021-coreference-reasoning-machine-reading-comprehension/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/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 Recognition](https://md.research.elamur.ai/free/en/papers/omura-2024-empirical-study-synthetic-data-generation/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Kazumasa Omura, Fei Cheng, Sadao Kurohashi*2024 · 8 citations*
21. **[SC-Ques: A Sentence Completion Question Dataset for English as a Second Language Learners](https://md.research.elamur.ai/free/en/papers/liu-2022-sc-ques-sentence-completion-question/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Qiongqiong 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 expressions](https://md.research.elamur.ai/free/en/papers/noel-2026-eiffel-novel-benchmark-measure-bias/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Charlotte Noel, Nicholas Asher, Olivier Gouvert, et al.*2026*
23. **[Generation of Instruction and Preference Dataset for Improving Japanese Instruction Following in LLMs](https://md.research.elamur.ai/free/en/papers/moriyama-2026-generation-instruction-preference-dataset-improving/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Kei Moriyama, Takashi Kodama, Kouta Nakayama*2026*

111 more citing papers of our library have no page here yet.

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