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Klein, G. (2022). Snapshots of the mind. MIT Press.  
3/17/23, 8:28 PM
Gunning, D., & Aha, D. (2019). Darpa’s explainable artificial intelligence (xai) program. AI Magazine, 40(2), 44–58.  
3/17/23, 8:19 PM
Anantrasirichai, N., & Bull, D. (2022). Artificial intelligence in the creative industries: A review. Artificial Intelligence Review, 1–68.  
3/17/23, 8:13 PM
Naseem, U., Razzak, I., Khan, S. K., & Prasad, M. (2021). A comprehensive survey on word representation models: From classical to state-of-the-art word representation language models. Transactions on Asian and Low-Resource Language Information Processing, 20(5), 1–35.  
3/17/23, 7:42 PM
Wang, B., Xie, Q., Pei, J., Tiwari, P., Li, Z., & others. (2021). Pre-trained language models in biomedical domain: A systematic survey. arXiv preprint arXiv:2110.05006.  
3/16/23, 9:05 PM
Singhal, K., Azizi, S., Tu, T., Mahdavi, S. S., Wei, J., & Chung, H. W., et al.. (2022). Large language models encode clinical knowledge. arXiv preprint arXiv:2212.13138.  
3/16/23, 8:46 PM
Schmidt, D. C., Spencer-Smith, J., Fu, Q., & White, J. (2023). Cataloging prompt patterns to enhance the discipline of prompt engineering. Vanderbilt University forum.  
3/16/23, 7:38 PM
Oppenlaender, J. (2022). Prompt engineering for text-based generative art. arXiv preprint arXiv:2204.13988.  
3/16/23, 7:26 PM
Horvitz, E. 2022, On the horizon: Interactive and compositional deepfakes. Paper presented at Proceedings of the 2022 International Conference on Multimodal Interaction.  
3/16/23, 7:18 PM
Shen, X., Qu, Y., Backes, M., & Zhang, Y. (2023). Prompt stealing attacks against text-to-image generation models. arXiv preprint arXiv:2302.09923.  
2/28/23, 4:36 PM
Trautmann, D., Petrova, A., & Schilder, F. (2022). Legal prompt engineering for multilingual legal judgement prediction. arXiv preprint arXiv:2212.02199.  
2/28/23, 1:13 PM
Ruskov, M. (2023). Grimm in wonderland: Prompt engineering with midjourney to illustrate fairytales. arXiv preprint arXiv:2302.08961.  
2/28/23, 1:05 PM
Sorensen, T., Robinson, J., Rytting, C. M., Shaw, A. G., Rogers, K. J., & Delorey, A. P., et al.. (2022). An information-theoretic approach to prompt engineering without ground truth labels. arXiv preprint arXiv:2203.11364.  
2/28/23, 12:54 PM
Strobelt, H., Webson, A., Sanh, V., Hoover, B., Beyer, J., & Pfister, H., et al.. (2022). Interactive and visual prompt engineering for ad-hoc task adaptation with large language models. IEEE transactions on visualization and computer graphics, 29(1), 1146–1156.  
2/28/23, 12:50 PM
Denny, P., Kumar, V., & Giacaman, N. (2022). Conversing with copilot: Exploring prompt engineering for solving cs1 problems using natural language. arXiv preprint arXiv:2210.15157.  
2/28/23, 12:44 PM
Lim, S., & Schm"alzle, R. (2022). Artificial intelligence for health message generation: Theory, method, and an empirical study using prompt engineering. arXiv preprint arXiv:2212.07507.  
2/28/23, 12:39 PM
White, J., Fu, Q., Hays, S., Sandborn, M., Olea, C., & Gilbert, H., et al.. (2023). A prompt pattern catalog to enhance prompt engineering with chatgpt. arXiv preprint arXiv:2302.11382.  
2/28/23, 10:51 AM
Grieves, M., & Vickers, J. (2017). Digital twin: Mitigating unpredictable, undesirable emergent behavior in complex systems. Transdisciplinary perspectives on complex systems: New findings and approaches, 85–113.  
2/8/23, 10:35 AM
Glaessgen, E., & Stargel, D. 2012, The digital twin paradigm for future nasa and us air force vehicles. Paper presented at 53rd AIAA/ASME/ASCE/AHS/ASC structures, structural dynamics and materials conference 20th AIAA/ASME/AHS adaptive structures conference 14th AIAA.  
2/8/23, 10:22 AM
Dai, H.-N., Wang, H., Xu, G., Wan, J., & Imran, M. (2020). Big data analytics for manufacturing internet of things: Opportunities, challenges and enabling technologies. Enterprise Information Systems, 14(9-10), 1279–1303.  
2/8/23, 9:58 AM
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WIKINDX 6.7.0 | Total resources: 1470 | Username: -- | Bibliography: WIKINDX Master Bibliography | Style: American Psychological Association (APA)