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Recent work exploring the capabilities of pre-trained large language models (LLMs) has demonstrated their ability to act as general pattern machines by completing complex token sequences representing a wide array of tasks, including time-series prediction and robot control.
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LSTM can solve hard long time lag problems
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C. Piech, J. Bassen, J. Huang, S. Ganguli, M. Sahami, L. J. Guibas, and J. Sohl-Dickstein · 2015
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Intervention-BKT: Incorporating Instructional Interventions into Bayesian Knowledge Tracing
C. Lin and M. Chi · 2016
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Adaptive robot language tutoring based on Bayesian knowledge tracing and predictive decision-making
T. Schodde, K. Bergmann, and S. Kopp · 2017
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Attention is all you need
A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, L. Kaiser, and I. Polosukhin · 2017
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Dynamic Key-Value Memory Networks for Knowledge Tracing
J. Zhang, X. Shi, I. King, and D.-Y. Yeung · 2017
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BERT: Pre-training of deep bidirectional transformers for language understanding
J. Devlin, M.-W. Chang, K. Lee, and K. Toutanova · 2018
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Exercise-Enhanced Sequential Modeling for Student Performance Prediction
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G. Abdelrahman and Q. Wang · 2019
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S. Pandey and G. Karypis · 2019
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Language models are unsupervised multitask learners
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How to fine-tune BERT for text classification?
C. Sun, X. Qiu, Y. Xu, and X. Huang · 2019
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Language models are few-shot learners
T. Brown, B. Mann, N. Ryder, M. Subbiah, J. D. Kaplan, P. Dhariwal, A. Neelakantan, P. Shyam, G. Sastry, A. Askell, and others · 2020
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Towards an Appropriate Query, Key, and Value Computation for Knowledge Tracing
Y. Choi, Y. Lee, J. Cho, J. Baek, B. Kim, Y. Cha, D. Shin, C. Bae, and J. Heo · 2020
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When is deep learning the best approach to knowledge tracing?
T. Gervet, K. Koedinger, J. Schneider, T. Mitchell, and others · 2020
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Comparing BERT against traditional machine learning text classification
Large Language Models Are Zero-Shot Time Series Forecasters, Oct. 2023
N. Gruver, M. Finzi, S. Qiu, and A. G. Wilson · 2023
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Unlocking the potential of GPT-3 in education: opportunities, limitations, and recommendations for effective integration
S. Kikalishvili · 2023
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Large Language Models are Few-Shot Health Learners, May 2023
X. Liu, D. McDuff, G. Kovacs, I. Galatzer-Levy, J. Sunshine, J. Zhan, M.-Z. Poh, S. Liao, P. Di Achille, and S. Patel · 2023
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Can ChatGPT forecast stock price movements? return predictability and large language models
A. Lopez-Lira and Y. Tang · 2023
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Large Language Models as General Pattern Machines, Oct. 2023
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S. González-Carvajal and E. C. Garrido-Merchán · 2020
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Evaluating Large Language Models Trained on Code, July 2021
M. Chen, J. Tworek, H. Jun, Q. Yuan, H. P. d. O. Pinto, J. Kaplan, H. Edwards, Y. Burda, N. Joseph, G. Brockman, A. Ray, R. Puri, G. Krueger, M. Petrov, H. Khlaaf, G. Sastry, P. Mishkin, B. Chan, S. Gray, N. Ryder, M. Pavlov, A. Power, L. Kaiser, M. Bavarian, C. Winter, P. Tillet, F. P. Such, D. Cummings, M. Plappert, F. Chantzis, E. Barnes, A. Herbert-Voss, W. H. Guss, A. Nichol, A. Paino, N. Tezak, J. Tang, I. Babuschkin, S. Balaji, S. Jain, W. Saunders, C. Hesse, A. N. Carr, J. Leike, J. Achiam, V. Misra, E. Morikawa, A. Radford, M. Knight, M. Brundage, M. Murati, K. Mayer, P. Welinder, B. McGrew, D. Amodei, S. McCandlish, I. Sutskever, and W. Zaremba · 2021
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A deep transfer learning approach to modeling teacher discourse in the classroom
E. Jensen, S. L. Pugh, and S. K. D’Mello · 2021
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EKT: Exercise-Aware Knowledge Tracing for Student Performance Prediction
Q. Liu, Z. Huang, Y. Yin, E. Chen, H. Xiong, Y. Su, and G. Hu · 2021
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S. Sarsa, J. Leinonen, and A. Hellas · 2021
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Short answer questions generation by fine-tuning BERT and GPT-2
D. Tsai, W. Chang, and S. Yang · 2021
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Solving quantitative reasoning problems with language models
A. Lewkowycz, A. Andreassen, D. Dohan, E. Dyer, H. Michalewski, V. Ramasesh, A. Slone, C. Anil, I. Schlag, and T. Gutman-Solo · 2022
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S. Mirchandani, F. Xia, P. Florence, B. Ichter, D. Driess, M. G. Arenas, K. Rao, D. Sadigh, and A. Zeng · 2023
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A brief history of prompt: Leveraging language models
G. M. Muktadir · 2023
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Development and evaluation of a diagnostic exam for undergraduate biomedical engineering students using GPT language model-based virtual agents
A. I. P. Sanpablo · 2023
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Reviewriter: AI-generated instructions for peer review writing
X. Su, T. Wambsganss, R. Rietsche, S. P. Neshaei, and T. Käser · 2023
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Large language models in medicine
A. J. Thirunavukarasu, D. S. J. Ting, K. Elangovan, L. Gutierrez, T. F. Tan, and D. S. W. Ting · 2023
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LLaMA 2: Open Foundation and Fine-Tuned Chat Models, July 2023
H. Touvron, L. Martin, K. Stone, P. Albert, A. Almahairi, Y. Babaei, N. Bashlykov, S. Batra, P. Bhargava, S. Bhosale, D. Bikel, L. Blecher, C. C. Ferrer, M. Chen, G. Cucurull, D. Esiobu, J. Fernandes, J. Fu, W. Fu, B. Fuller, C. Gao, V. Goswami, N. Goyal, A. Hartshorn, S. Hosseini, R. Hou, H. Inan, M. Kardas, V. Kerkez, M. Khabsa, I. Kloumann, A. Korenev, P. S. Koura, M.-A. Lachaux, T. Lavril, J. Lee, D. Liskovich, Y. Lu, Y. Mao, X. Martinet, T. Mihaylov, P. Mishra, I. Molybog, Y. Nie, A. Poulton, J. Reizenstein, R. Rungta, K. Saladi, A. Schelten, R. Silva, E. M. Smith, R. Subramanian, X. E. Tan, B. Tang, R. Taylor, A. Williams, J. X. Kuan, P. Xu, Z. Yan, I. Zarov, Y. Zhang, A. Fan, M. Kambadur, S. Narang, A. Rodriguez, R. Stojnic, S. Edunov, and T. Scialom · 2023
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T. Wambsganss, X. Su, V. Swamy, S. P. Neshaei, R. Rietsche, and T. Käser · 2023
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Zero-shot cross-lingual summarization via large language models
J. Wang, Y. Liang, F. Meng, B. Zou, Z. Li, J. Qu, and J. Zhou · 2023
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Structured persuasive writing support in legal education: A model and tool for German legal case solutions
F. Weber, T. Wambsganss, S. P. Neshaei, and M. Soellner · 2023
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Chain-of-Thought Prompting Elicits Reasoning in Large Language Models, Jan. 2023
J. Wei, X. Wang, D. Schuurmans, M. Bosma, B. Ichter, F. Xia, E. Chi, Q. Le, and D. Zhou · 2023
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Zero-shot information extraction via chatting with ChatGPT
X. Wei, X. Cui, N. Cheng, X. Wang, X. Zhang, S. Huang, P. Xie, J. Xu, Y. Chen, M. Zhang, and others · 2023
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Assessment of chemistry knowledge in large language models that generate code
A. D. White, G. M. Hocky, H. A. Gandhi, M. Ansari, S. Cox, G. P. Wellawatte, S. Sasmal, Z. Yang, K. Liu, Y. Singh, and others · 2023
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A brief overview of ChatGPT: The history, status quo and potential future development
T. Wu, S. He, J. Liu, S. Sun, K. Liu, Q.-L. Han, and Y. Tang · 2023
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Utilizing a pretrained language model (BERT) to classify preservice physics teachers’ written reflections
P. Wulff, L. Mientus, A. Nowak, and A. Borowski · 2023
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Temporal data meets LLM–Explainable financial time series forecasting
X. Yu, Z. Chen, Y. Ling, S. Dong, Z. Liu, and Y. Lu · 2023
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One Fits All:Power General Time Series Analysis by Pretrained LM, Oct. 2023
T. Zhou, P. Niu, X. Wang, L. Sun, and R. Jin · 2023
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Solving math word problems concerning systems of equations with GPT-3
M. Zong and B. Krishnamachari · 2023
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LLM4TS: Aligning Pre-Trained LLMs as Data-Efficient Time-Series Forecasters, Jan. 2024
C. Chang, W.-Y. Wang, W.-C. Peng, and T.-F. Chen · 2024
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