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Large language models (LLMs) have shown promise for generative and knowledge-intensive tasks including question-answering (QA) tasks.
Language models are few-shot learners
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Chin-Yew Lin. 2004 · 2004
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Rapidly bootstrapping a question answering dataset for covid-19
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Machine reading of biomedical texts about alzheimers disease
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George Tsatsaronis, Georgios Balikas, Prodromos Malakasiotis, Ioannis Partalas, Matthias Zschunke, Michael R Alvers, Dirk Weissenborn, Anastasia Krithara, Sergios Petridis, Dimitris Polychronopoulos, et al. 2015 · 2015
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A corpus for research in text processing for evidence based medicine
Diego Mollá, María Elena Santiago-Martínez, Abeed Sarker, and Cécile Paris. 2016 · 2016
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Overview of the medical question answering task at trec 2017 liveqa
Asma Ben Abacha, Eugene Agichtein, Yuval Pinter, and Dina Demner-Fushman. 2017 · 2017
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Simple and effective semi-supervised question answering
Bhuwan Dhingra, Danish Danish, and Dheeraj Rajagopal. 2018 · 2018
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emrqa: A large corpus for question answering on electronic medical records
Anusri Pampari, Preethi Raghavan, Jennifer Liang, and Jian Peng. 2018 · 2018
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Know what you don’t know: Unanswerable questions for squad
Pranav Rajpurkar, Robin Jia, and Percy Liang. 2018 · 2018
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Clicr: A dataset of clinical case reports for machine reading comprehension
Simon Šuster and Walter Daelemans. 2018 · 2018
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Constructing Datasets for Multi-hop Reading Comprehension Across Documents
Johannes Welbl, Pontus Stenetorp, and Sebastian Riedel. 2018 · 2018
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Overview of the mediqa 2019 shared task on textual inference, question entailment and question answering
Asma Ben Abacha, Chaitanya Shivade, and Dina Demner-Fushman. 2019 · 2019
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Publicly available clinical bert embeddings
Emily Alsentzer, John Murphy, William Boag, Wei-Hung Weng, Di Jindi, Tristan Naumann, and Matthew McDermott. 2019 · 2019
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A question-entailment approach to question answering
Asma Ben Abacha and Dina Demner-Fushman. 2019 · 2019
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Overview of the mediqa 2019 shared task on textual inference, question entailment and question answering
Asma Ben Abacha, Chaitanya Shivade, and Dina Demner-Fushman. 2019 · 2019
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PubMedQA: A dataset for biomedical research question answering
Qiao Jin, Bhuwan Dhingra, Zhengping Liu, William Cohen, and Xinghua Lu. 2019 · 2019
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Sentence-bert: Sentence embeddings using siamese bert-networks
Nils Reimers and Iryna Gurevych. 2019 · 2019
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Question answering with long multiple-span answers
Ming Zhu, Aman Ahuja, Da-Cheng Juan, Wei Wei, and Chandan K. Reddy. 2020 · 2019
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Retrieval augmented language model pre-training
Kelvin Guu, Kenton Lee, Zora Tung, Panupong Pasupat, and Mingwei Chang. 2020 · 2020
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Biomedical question answering: A survey of methods and datasets
Zakaria Kaddari, Youssef Mellah, Jamal Berrich, Toumi Bouchentouf, and Mohammed G. Belkasmi. 2020 · 2020
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Retrieval-augmented generation for knowledge-intensive nlp tasks
Patrick Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen-tau Yih, Tim Rocktäschel, et al. 2020 · 2020
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Covid-qa: A question answering dataset for covid-19
Timo Möller, Anthony Reina, Raghavan Jayakumar, and Malte Pietsch. 2020 · 2020
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The ethics of ai in health care: a mapping review
Jessica Morley, Caio CV Machado, Christopher Burr, Josh Cowls, Indra Joshi, Mariarosaria Taddeo, and Luciano Floridi. 2020 · 2020
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How much knowledge can you pack into the parameters of a language model?
Adam Roberts, Colin Raffel, and Noam Shazeer. 2020 · 2020
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A pre-trained language model for medical question answering based on domain adaption
Lang Liu, Junxiang Ren, Yuejiao Wu, Ruilin Song, Zhen Cheng, and Sibo Wang. 2022 · 2022
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Rethinking the role of demonstrations: What makes in-context learning work?
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Training language models to follow instructions with human feedback
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Read before generate! faithful long form question answering with machine reading
Dan Su, Xiaoguang Li, Jindi Zhang, Lifeng Shang, Xin Jiang, Qun Liu, and Pascale Fung. 2022 · 2022
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Max Savery, Asma Ben Abacha, Soumya Gayen, and Dina Demner-Fushman. 2020 · 2020
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KPQA: A metric for generative question answering using keyphrase weights
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Mlec-qa: A chinese multi-choice biomedical question answering dataset
Jing Li, Shangping Zhong, and Kaizhi Chen. 2021b · 2021
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Truthfulqa: Measuring how models mimic human falsehoods
Stephanie Lin, Jacob Hilton, and Owain Evans. 2021 · 2021
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Webgpt: Browser-assisted question-answering with human feedback
Reiichiro Nakano, Jacob Hilton, Suchir Balaji, Jeff Wu, Long Ouyang, Christina Kim, Christopher Hesse, Shantanu Jain, Vineet Kosaraju, William Saunders, et al. 2021 · 2021
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Kilt: a benchmark for knowledge intensive language tasks
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