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Large language models (LLMs) have shown the potential to be integrated into human daily lives.
SuperGlue: Learning Feature Matching with Graph Neural Networks
Sarlin, P.; DeTone, D.; Malisiewicz, T.; and Rabinovich, A. 2019 · 1911
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The Proof and Measurement of Association between Two Things
Spearman, C. 1987 · 1987
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Thirteen ways to look at the correlation coefficient
Lee Rodgers, J.; and Nicewander, W. A. 1988 · 1988
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Language Models are Few-Shot Learners
Brown, T. B.; Mann, B.; Ryder, N.; Subbiah, M.; Kaplan, J.; Dhariwal, P.; Neelakantan, A.; Shyam, P.; Sastry, G.; Askell, A.; Agarwal, S.; Herbert-Voss, A.; Krueger, G.; Henighan, T.; Child, R.; Ramesh, A.; Ziegler, D. M.; Wu, J.; Winter, C.; Hesse, C.; Chen, M.; Sigler, E.; Litwin, M.; Gray, S.; Chess, B.; Clark, J.; Berner, C.; McCandlish, S.; Radford, A.; Sutskever, I.; and Amodei, D. 2020 · 2005
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Automatically Constructing a Corpus of Sentential Paraphrases
Dolan, W. B.; and Brockett, C. 2005 · 2005
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Measuring Massive Multitask Language Understanding
Hendrycks, D.; Burns, C.; Basart, S.; Zou, A.; Mazeika, M.; Song, D.; and Steinhardt, J. 2020 · 2009
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Recursive deep models for semantic compositionality over a sentiment treebank
Socher, R.; Perelygin, A.; Wu, J.; Chuang, J.; Manning, C. D.; Ng, A. Y.; and Potts, C. 2013 · 2013
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Squad: 100,000+ questions for machine comprehension of text
Rajpurkar, P.; Zhang, J.; Lopyrev, K.; and Liang, P. 2016 · 2016
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GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding
Wang, A.; Singh, A.; Michael, J.; Hill, F.; Levy, O.; and Bowman, S. 2018 · 2018
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A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference
Williams, A.; Nangia, N.; and Bowman, S. 2018 · 2018
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BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Devlin, J.; Chang, M.-W.; Lee, K.; and Toutanova, K. 2019 · 2019
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CLUE: A Chinese Language Understanding Evaluation Benchmark
Xu, L.; Hu, H.; Zhang, X.; Li, L.; Cao, C.; Li, Y.; Xu, Y.; Sun, K.; Yu, D.; Yu, C.; Tian, Y.; Dong, Q.; Liu, W.; Shi, B.; Cui, Y.; Li, J.; Zeng, J.; Wang, R.; Xie, W.; Li, Y.; Patterson, Y.; Tian, Z.; Zhang, Y.; Zhou, H.; Liu, S.; Zhao, Z.; Zhao, Q.; Yue, C.; Zhang, X.; Yang, Z.; Richardson, K.; and Lan, Z. 2020 · 2020
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A Robustly Optimized BERT Pre-training Approach with Post-training
Zhuang, L.; Wayne, L.; Ya, S.; and Jun, Z. 2021 · 2021
Cited alongside, same era.
GLM: General Language Model Pretraining with Autoregressive Blank Infilling
Du, Z.; Qian, Y.; Liu, X.; Ding, M.; Qiu, J.; Yang, Z.; and Tang, J. 2022 · 2022
Cited alongside, same era.
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models
Lewkowycz, A.; Slone, A.; Andreassen, A.; Freeman, D.; Dyer, E. S.; Mishra, G.; Gur-Ari, G.; Lee, J.; Sohl-dickstein, J.; Chiafullo, K.; Fedus, L. B.; Fiedel, N.; Liu, R.; Misra, V.; and Ramasesh, V. V. 2022 · 2022
Cited alongside, same era.
Holistic Evaluation of Language Models
Liang, P.; Bommasani, R.; Lee, T.; Tsipras, D.; Soylu, D.; Yasunaga, M.; Zhang, Y.; Narayanan, D.; Wu, Y.; Kumar, A.; Newman, B.; Yuan, B.; Yan, B.; Zhang, C.; Cosgrove, C.; Manning, C. D.; Ré, C.; Acosta-Navas, D.; Hudson, D. A.; Zelikman, E.; Durmus, E.; Ladhak, F.; Rong, F.; Ren, H.; Yao, H.; Wang, J.; Santhanam, K.; Orr, L.; Zheng, L.; Yuksekgonul, M.; Suzgun, M.; Kim, N.; Guha, N.; Chatterji, N.; Khattab, O.; Henderson, P.; Huang, Q.; Chi, R.; Xie, S. M.; Santurkar, S.; Ganguli, S.; Hashimoto, T.; Icard, T.; Zhang, T.; Chaudhary, V.; Wang, W.; Li, X.; Mai, Y.; Zhang, Y.; and Koreeda, Y. 2022 · 2022
Cited alongside, same era.
C-Eval: A Multi-Level Multi-Discipline Chinese Evaluation Suite for Foundation Models
Huang, Y.; Bai, Y.; Zhu, Z.; Zhang, J.; Zhang, J.; Su, T.; Liu, J.; Lv, C.; Zhang, Y.; Lei, J.; Fu, Y.; Sun, M.; and He, J. 2023 · 2023
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ChatGPT for Good? On Opportunities and Challenges of Large Language Models for Education
Kasneci, E.; Seßler, K.; Küchemann, S.; Bannert, M.; Dementieva, D.; Fischer, F.; Gasser, U.; Groh, G.; Günnemann, S.; Hüllermeier, E.; and et al. 2023 · 2023
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AlpacaEval: An Automatic Evaluator of Instruction-following Models
Li, X.; Zhang, T.; Dubois, Y.; Taori, R.; Gulrajani, I.; Guestrin, C.; Liang, P.; and Hashimoto, T. B. 2023 · 2023
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Putting ChatGPT’s Medical Advice to the (Turing) Test
Nov, O.; Singh, N.; and Mann, D. 2023 · 2023
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Training language models to follow instructions with human feedback
Ouyang, L.; Wu, J.; Jiang, X.; Almeida, D.; Wainwright, C. L.; Mishkin, P.; Zhang, C.; Agarwal, S.; Slama, K.; Ray, A.; Schulman, J.; Hilton, J.; Kelton, F.; Miller, L.; Simens, M.; Askell, A.; Welinder, P.; Christiano, P.; Leike, J.; and Lowe, R. 2022 · 2022
Cited alongside, same era.
Fengshenbang 1.0: Being the Foundation of Chinese Cognitive Intelligence
Wang, J.; Zhang, Y.; Zhang, L.; Yang, P.; Gao, X.; Wu, Z.; Dong, X.; He, J.; Zhuo, J.; Yang, Q.; Huang, Y.; Li, X.; Wu, Y.; Lu, J.; Zhu, X.; Chen, W.; Han, T.; Pan, K.; Wang, R.; Wang, H.; Wu, X.; Zeng, Z.; Chen, C.; Gan, R.; and Zhang, J. 2022 · 2022
Cited alongside, same era.
Glm-130b: An open bilingual pre-trained model
Zeng, A.; Liu, X.; Du, Z.; Wang, Z.; Lai, H.; Ding, M.; Yang, Z.; Xu, Y.; Zheng, W.; Xia, X.; et al. 2022 · 2022
Cited alongside, same era.
OPT: Open Pre-trained Transformer Language Models
Zhang, S.; Roller, S.; Goyal, N.; Artetxe, M.; Chen, M.; Chen, S.; Dewan, C.; Diab, M.; Li, X.; Lin, X. V.; Mihaylov, T.; Ott, M.; Shleifer, S.; Shuster, K.; Simig, D.; Koura, P. S.; Sridhar, A.; Wang, T.; and Zettlemoyer, L. 2022 · 2022
Cited alongside, same era.
Vicuna: An Open-Source Chatbot Impressing GPT-4 with 90%* ChatGPT Quality
Chiang, W.-L.; Li, Z.; Lin, Z.; Sheng, Y.; Wu, Z.; Zhang, H.; Zheng, L.; Zhuang, S.; Zhuang, Y.; Gonzalez, J. E.; Stoica, I.; and Xing, E. P. 2023 · 2023
Cited alongside, same era.
News Summarization and Evaluation in the Era of GPT-3
Goyal, T.; Li, J. J.; and Durrett, G. 2023 · 2023
Cited alongside, same era.
Xiezhi: An Ever-Updating Benchmark for Holistic Domain Knowledge Evaluation
Gu, Z.; Zhu, X.; Ye, H.; Zhang, L.; Wang, J.; Jiang, S.; Xiong, Z.; Li, Z.; He, Q.; Xu, R.; Huang, W.; Wang, Z.; Wang, S.; Zheng, W.; Feng, H.; and Xiao, Y. 2023 · 2023
Cited alongside, same era.
OpenAI. 2023 · 2023
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ChatGPT utility in healthcare education, research, and practice: systematic review on the promising perspectives and valid concerns
Sallam, M. 2023 · 2023
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MOSS: Training Conversational Language Models from Synthetic Data
Sun, T.; Zhang, X.; He, Z.; Li, P.; Cheng, Q.; Yan, H.; Liu, X.; Shao, Y.; Tang, Q.; Zhao, X.; Chen, K.; Zheng, Y.; Zhou, Z.; Li, R.; Zhan, J.; Zhou, Y.; Li, L.; Yang, X.; Wu, L.; Yin, Z.; Huang, X.; and Qiu, X. 2023 · 2023
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LLaMA: Open and Efficient Foundation Language Models
Touvron, H.; Lavril, T.; Izacard, G.; Martinet, X.; Lachaux, M.-A.; Lacroix, T.; Rozière, B.; Goyal, N.; Hambro, E.; Azhar, F.; Rodriguez, A.; Joulin, A.; Grave, E.; and Lample, G. 2023 · 2023
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Measuring Massive Multitask Chinese Understanding
Zeng, H. 2023 · 2023
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Judging LLM-as-a-judge with MT-Bench and Chatbot Arena
Zheng, L.; Chiang, W.-L.; Sheng, Y.; Zhuang, S.; Wu, Z.; Zhuang, Y.; Lin, Z.; Li, Z.; Li, D.; Xing, E. P.; Zhang, H.; Gonzalez, J. E.; and Stoica, I. 2023 · 2023
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AGIEval: A Human-Centric Benchmark for Evaluating Foundation Models
Zhong, W.; Cui, R.; Guo, Y.; Liang, Y.; Lu, S.; Wang, Y.; Saied, A. S. S.; Chen, W.; and Duan, N. 2023 · 2023
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