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Recently, there has been growing interest in using Large Language Models (LLMs) for scientific research.
Pubmedqa: A dataset for biomedical research question answering
Jin, Q.; Dhingra, B.; Liu, Z.; Cohen, W. W.; and Lu, X. 2019 · 1909
Earlier work this paper cites.
A revision of Bloom’s taxonomy: An overview
Krathwohl, D. R. 2002 · 2002
Earlier work this paper cites.
Bleu: a method for automatic evaluation of machine translation
Papineni, K.; Roukos, S.; Ward, T.; and Zhu, W.-J. 2002 · 2002
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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
Earlier work this paper cites.
Bloom’s taxonomy
Forehand, M. 2010 · 2010
Earlier work this paper cites.
Measuring mathematical problem solving with the math dataset
Hendrycks, D.; Burns, C.; Kadavath, S.; Arora, A.; Basart, S.; Tang, E.; Song, D.; and Steinhardt, J. 2021 · 2021
Earlier work this paper cites.
What disease does this patient have? a large-scale open domain question answering dataset from medical exams
Jin, D.; Pan, E.; Oufattole, N.; Weng, W.-H.; Fang, H.; and Szolovits, P. 2021 · 2021
Earlier work this paper cites.
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
Earlier work this paper cites.
Neural scaling of deep chemical models
Frey, N.; Soklaski, R.; Axelrod, S.; Samsi, S.; Gomez-Bombarelli, R.; Coley, C.; and Gadepally, V. 2022 · 2022
Earlier work this paper cites.
Large language models are zero-shot reasoners
Kojima, T.; Gu, S. S.; Reid, M.; Matsuo, Y.; and Iwasawa, Y. 2022 · 2022
Earlier work this paper cites.
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.; et al. 2022 · 2022
Cited alongside, same era.
Learn to explain: Multimodal reasoning via thought chains for science question answering
Lu, P.; Mishra, S.; Xia, T.; Qiu, L.; Chang, K.-W.; Zhu, S.-C.; Tafjord, O.; Clark, P.; and Kalyan, A. 2022 · 2022
Cited alongside, same era.
BioGPT: generative pre-trained transformer for biomedical text generation and mining
Luo, R.; Sun, L.; Xia, Y.; Qin, T.; Zhang, S.; Poon, H.; and Liu, T.-Y. 2022 · 2022
Cited alongside, same era.
Training language models to follow instructions with human feedback
Ouyang, L.; Wu, J.; Jiang, X.; Almeida, D.; Wainwright, C.; Mishkin, P.; Zhang, C.; Agarwal, S.; Slama, K.; Ray, A.; et al. 2022 · 2022
Cited alongside, same era.
ChatGPT: Optimizing language models for dialogue
Schulman, J.; Zoph, B.; Kim, C.; Hilton, J.; Menick, J.; Weng, J.; Uribe, J. F. C.; Fedus, L.; Metz, L.; Pokorny, M.; et al. 2022 · 2022
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.; et al. 2023 · 2023
Closest in time.
OpenAI. 2023 · 2023
Closest in time.
Large language models encode clinical knowledge
Singhal, K.; Azizi, S.; Tu, T.; Mahdavi, S. S.; Wei, J.; Chung, H. W.; Scales, N.; Tanwani, A.; Cole-Lewis, H.; Pfohl, S.; et al. 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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Stanford alpaca: An instruction-following llama model
Taori, R.; Gulrajani, I.; Zhang, T.; Dubois, Y.; Li, X.; Guestrin, C.; Liang, P.; and Hashimoto, T. B. 2023 · 2023
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Cited alongside, same era.
Beyond the imitation game: Quantifying and extrapolating the capabilities of language models
Srivastava, A.; Rastogi, A.; Rao, A.; Shoeb, A. A. M.; Abid, A.; Fisch, A.; Brown, A. R.; Santoro, A.; Gupta, A.; Garriga-Alonso, A.; et al. 2022 · 2022
Cited alongside, same era.
GALACTICA: A Large Language Model for Science
Taylor, R.; Kardas, M.; Cucurull, G.; Scialom, T.; Hartshorn, A.; Saravia, E.; Poulton, A.; Kerkez, V.; and Stojnic, R. 2022 · 2022
Cited alongside, same era.
The role of ai in drug discovery: challenges, opportunities, and strategies
Blanco-Gonzalez, A.; Cabezon, A.; Seco-Gonzalez, A.; Conde-Torres, D.; Antelo-Riveiro, P.; Pineiro, A.; and Garcia-Fandino, R. 2023 · 2023
Cited alongside, same era.
A survey on evaluation of large language models
Chang, Y.; Wang, X.; Wang, J.; Wu, Y.; Zhu, K.; Chen, H.; Yang, L.; Yi, X.; Wang, C.; Wang, Y.; et al. 2023 · 2023
Cited alongside, same era.
What indeed can GPT models do in chemistry? A comprehensive benchmark on eight tasks
Guo, T.; Guo, K.; Liang, Z.; Guo, Z.; Chawla, N. V.; Wiest, O.; Zhang, X.; et al. 2023 · 2023
Cited alongside, same era.
Closest in time.
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.; et al. 2023 · 2023
Closest in time.
Novel Paradigm for AI-driven Scientific Research: From AI4S to Intelligent Science
WANG, F.; and MIAO, Q. 2023 · 2023
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SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language Models
Wang, X.; Hu, Z.; Lu, P.; Zhu, Y.; Zhang, J.; Subramaniam, S.; Loomba, A. R.; Zhang, S.; Sun, Y.; and Wang, W. 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.; et al. 2023 · 2023
Closest in time.
Agieval: A human-centric benchmark for evaluating foundation models
Zhong, W.; Cui, R.; Guo, Y.; Liang, Y.; Lu, S.; Wang, Y.; Saied, A.; Chen, W.; and Duan, N. 2023 · 2023
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