🧑‍🔬 Who cites Chaitanya Shivade

199 citations of their works from 179 papers of our library (of the 141,840 whose bibliographies we read) · 17 with a page here, the most cited first · ← Chaitanya Shivade

1. Publicly Available Clinical BERT EmbeddingsarXiv:1904.03323Emily Alsentzer, John R. Murphy, Willie Boag, et al.2019 · 1,226 citations
   Transfer Learning in Biomedical Natural Language Processing: An Evaluation of BERT and ELMo on Ten Benchmarking DatasetsBioNLP Shared Task WorkshopYifan Peng, Shankai Yan, Zhiyong Lu2019 · 1,082 citations
2. Revealing the Dark Secrets of BERTarXiv:1908.08593Olga Kovaleva, Alexey Romanov, Anna Rogers, et al.2019 · 745 citations
3. The Flan Collection: Designing Data and Methods for Effective Instruction TuningarXiv:2301.13688Shayne Longpre, Le Hou, Tu Vu, et al.2023 · 592 citations
4. What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical ExamsarXiv:2009.13081Di Jin, Eileen Pan, Nassim Oufattole, et al.2020 · 546 citations
   Benchmarking Retrieval-Augmented Generation for MedicineFindings of the Association for Computational LinguisticsGuangzhi Xiong, Qiao Jin, Zhiyong Lu, et al.2024 · 426 citations
   Towards Mitigating LLM Hallucination via Self ReflectionFindings of the Association for Computational LinguisticsZiwei Ji, Tiezheng Yu, Yan Xu, et al.2023 · 352 citations
   Pretrained Language Models for Biomedical and Clinical Tasks: Understanding and Extending the State-of-the-ArtClinical Natural Language Processing WorkshopPatrick Lewis, Myle Ott, Jingfei Du, et al.2020 · 241 citations
   CharacterBERT: Reconciling ELMo and BERT for Word-Level Open-Vocabulary Representations From CharactersInternational Conference on Computational Linguistics (COLING)Hicham El Boukkouri, Olivier Ferret, Thomas Lavergne, et al.2020 · 204 citations
   The CoT Collection: Improving Zero-shot and Few-shot Learning of Language Models via Chain-of-Thought Fine-TuningConference on Empirical Methods in Natural Language Processing (EMNLP)Seungone Kim, Se Joo, Doyoung Kim, et al.2023 · 116 citations
   An Empirical Study on Model-agnostic Debiasing Strategies for Robust Natural Language InferenceConference on Computational Natural Language Learning (CoNLL)Tianyu Liu, Xin Zheng, Xiaoan Ding, et al.2020 · 36 citations
   MedNLI Is Not Immune: Natural Language Inference Artifacts in the Clinical DomainAnnual Meeting of the Association for Computational Linguistics (ACL)Christine Herlihy, Rachel Rudinger2021 · 30 citations
   Capture Human Disagreement Distributions by Calibrated Networks for Natural Language InferenceFindings of the Association for Computational LinguisticsYuxia Wang, Minghan Wang, Yimeng Chen, et al.2022 · 15 citations
   Partial-input baselines show that NLI models can ignore context, but they don't.Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)Neha Srikanth, Rachel Rudinger2022 · 13 citations
   Towards the Necessity for Debiasing Natural Language Inference DatasetsLanguage Resources and Evaluation Conference (LREC)Mithun Paul Panenghat, Sandeep Suntwal, Faiz Rafique, et al.2020 · 13 citations
5. ArNLI: Arabic Natural Language Inference for Entailment and Contradiction DetectionarXiv:2209.13953 · (2023) Computer Science, 24(2)Khloud Al Jallad, Nada Ghneim2022 · 9 citations
6. A guide to the dataset explosion in QA, NLI, and commonsense reasoningAnna Rogers, Anna Rumshisky2020 · 4 citations

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