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Recently, Large Language Models (LLMs) have demonstrated outstanding performance across a wide range of downstream language tasks.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al. 2020 · 1901
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Multi-style generative reading comprehension
Kyosuke Nishida, Itsumi Saito, Kosuke Nishida, Kazutoshi Shinoda, Atsushi Otsuka, Hisako Asano, and Junji Tomita. 2019 · 1901
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Bidirectional attentive memory networks for question answering over knowledge bases
Yu Chen, Lingfei Wu, and Mohammed J Zaki. 2019 · 1903
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Lost in translation: Loss and decay of linguistic richness in machine translation
Eva Vanmassenhove, Dimitar Shterionov, and Andy Way. 2019 · 1906
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A mathematical theory of communication
Claude Elwood Shannon. 1948 · 1948
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A learning algorithm for boltzmann machines
David H Ackley, Geoffrey E Hinton, and Terrence J Sejnowski. 1985 · 1985
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Entropy: A new definition and its applications
Nikhil R Pal and Sankar K Pal. 1991 · 1991
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Rouge: A package for automatic evaluation of summaries
Chin-Yew Lin. 2004 · 2004
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Token-level adaptive training for neural machine translation
Shuhao Gu, Jinchao Zhang, Fandong Meng, Yang Feng, Wanying Xie, Jie Zhou, and Dong Yu. 2020 · 2010
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Ms marco: A human generated machine reading comprehension dataset
Payal Bajaj, Daniel Campos, Nick Craswell, Li Deng, Jianfeng Gao, Xiaodong Liu, Rangan Majumder, Andrew McNamara, Bhaskar Mitra, Tri Nguyen, et al. 2016 · 2016
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Show, ask, attend, and answer: A strong baseline for visual question answering
Vahid Kazemi and Ali Elqursh. 2017 · 2017
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Paraphrase generation with deep reinforcement learning
Zichao Li, Xin Jiang, Lifeng Shang, and Hang Li. 2017 · 2017
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QuAC: Question answering in context
Eunsol Choi, He He, Mohit Iyyer, Mark Yatskar, Wen-tau Yih, Yejin Choi, Percy Liang, and Luke Zettlemoyer. 2018 · 2018
Cited alongside, same era.
A call for clarity in reporting bleu scores
Matt Post. 2018 · 2018
Cited alongside, same era.
Spanbert: Improving pre-training by representing and predicting spans
Mandar Joshi, Danqi Chen, Yinhan Liu, Daniel S Weld, Luke Zettlemoyer, and Omer Levy. 2020 · 2020
Cited alongside, same era.
On the importance of diversity in question generation for qa
Md Arafat Sultan, Shubham Chandel, Ramón Fernandez Astudillo, and Vittorio Castelli. 2020 · 2020
Cited alongside, same era.
Focus attention: Promoting faithfulness and diversity in summarization
Rahul Aralikatte, Shashi Narayan, Joshua Maynez, Sascha Rothe, and Ryan McDonald. 2021 · 2021
Cited alongside, same era.
Evaluating the factual consistency of large language models through summarization
Derek Tam, Anisha Mascarenhas, Shiyue Zhang, Sarah Kwan, Mohit Bansal, and Colin Raffel. 2022 · 2022
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Kl-divergence guided temperature sampling
Chung-Ching Chang, David Reitter, Renat Aksitov, and Yun-Hsuan Sung. 2023 · 2023
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Can large language models be an alternative to human evaluations?
Cheng-Han Chiang and Hung-yi Lee. 2023 · 2023
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Palm: Scaling language modeling with pathways
Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, Maarten Bosma, Gaurav Mishra, Adam Roberts, Paul Barham, Hyung Won Chung, Charles Sutton, Sebastian Gehrmann, et al. 2023 · 2023
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alphaXiv searches the wider corpus for related work and actual follow-ups.
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Tahmid Hasan, Abhik Bhattacharjee, Md Saiful Islam, Kazi Samin, Yuan-Fang Li, Yong-Bin Kang, M Sohel Rahman, and Rifat Shahriyar. 2021 · 2021
Cited alongside, same era.
Lora: Low-rank adaptation of large language models
Edward J Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen. 2021 · 2021
Cited alongside, same era.
Mixup decoding for diverse machine translation
Jicheng Li, Pengzhi Gao, Xuanfu Wu, Yang Feng, Zhongjun He, Hua Wu, and Haifeng Wang. 2021 · 2021
Cited alongside, same era.
mface: Multilingual summarization with factual consistency evaluation
Roee Aharoni, Shashi Narayan, Joshua Maynez, Jonathan Herzig, Elizabeth Clark, and Mirella Lapata. 2022 · 2022
Cited alongside, same era.
Community question answering entity linking via leveraging auxiliary data
Yuhan Li, Wei Shen, Jianbo Gao, and Yadong Wang. 2022 · 2022
Cited alongside, same era.
Unsupervised question answering via answer diversifying
Yuxiang Nie, Heyan Huang, Zewen Chi, and Xian-Ling Mao. 2022 · 2022
Cited alongside, same era.
Long document summarization with top-down and bottom-up inference
Bo Pang, Erik Nijkamp, Wojciech Kryściński, Silvio Savarese, Yingbo Zhou, and Caiming Xiong. 2022 · 2022
Cited alongside, same era.
John Joon Young Chung, Ece Kamar, and Saleema Amershi. 2023 · 2023
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Llama factory
hiyouga. 2023 · 2023
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Generating with confidence: Uncertainty quantification for black-box large language models
Zhen Lin, Shubhendu Trivedi, and Jimeng Sun. 2023 · 2023
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Llmatic: Neural architecture search via large language models and quality-diversity optimization
Muhammad U Nasir, Sam Earle, Julian Togelius, Steven James, and Christopher Cleghorn. 2023 · 2023
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Llm is like a box of chocolates: the non-determinism of chatgpt in code generation
Shuyin Ouyang, Jie M Zhang, Mark Harman, and Meng Wang. 2023 · 2023
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Llama 2: Open foundation and fine-tuned chat models
Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, et al. 2023 · 2023
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A survey of large language models
Wayne Xin Zhao, Kun Zhou, Junyi Li, Tianyi Tang, Xiaolei Wang, Yupeng Hou, Yingqian Min, Beichen Zhang, Junjie Zhang, Zican Dong, et al. 2023 · 2023
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Representation engineering: A top-down approach to ai transparency
Andy Zou, Long Phan, Sarah Chen, James Campbell, Phillip Guo, Richard Ren, Alexander Pan, Xuwang Yin, Mantas Mazeika, Ann-Kathrin Dombrowski, et al. 2023 · 2023
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