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The disruptive technology provided by large-scale pre-trained language models (LLMs) such as ChatGPT or GPT-4 has received significant attention in several application domains, often with an emphasis on high-level opportunities and concerns.
“Tablegpt: Few-shot table-to-text generation with table structure reconstruction and content matching”
Gong, H., Y. Sun, X. Feng, B. Qin, W. Bi, X. Liu, and T. Liu. 2020 · 1988
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“World blindness and visual impairment: despite many successes, the problem is growing”
Ackland, P., S. Resnikoff, and R. Bourne. 2017 · 2017
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“Incorporation of implicit decision-maker preferences in multi-objective evolutionary optimization using a multi-criteria classification method”
Cruz-Reyes, L., E. Fernandez, P. Sanchez, C. A. C. Coello, and C. Gomez. 2017 · 2017
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“An interdisciplinary framework for participatory modeling design and evaluation—What makes models effective participatory decision tools?”
Falconi, S. M., and R. N. Palmer. 2017 · 2017
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“Computational modelling for decision-making: where, why, what, who and how”
Calder, M., C. Craig, D. Culley, R. De Cani, C. A. Donnelly, R. Douglas, B. Edmonds, J. Gascoigne, N. Gilbert, C. Hargrove et al. 2018 · 2018
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“Survey of the state of the art in natural language generation: Core tasks, applications and evaluation”
Gatt, A., and E. Krahmer. 2018 · 2018
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“Computational modelling of public policy: Reflections on practice”
Gilbert, N., P. Ahrweiler, P. Barbrook-Johnson, K. P. Narasimhan, and H. Wilkinson. 2018 · 2018
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“Symbiotic simulation system: Hybrid systems model meets big data analytics”
Onggo, B. S., N. Mustafee, A. Smart, A. A. Juan, and O. Molloy. 2018 · 2018
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“Co-designing social simulation models for policy advise: lessons learned from the INFSO-SKIN study”
Ahrweiler, P., D. Frank, and N. Gilbert. 2019 · 2019
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“Visualizing for the non-visual: Enabling the visually impaired to use visualization”
Choi, J., S. Jung, D. G. Park, J. Choo, and N. Elmqvist. 2019 · 2019
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“How can Machine Learning Support the Practice of Modeling and Simulation?—A Review and Directions for Future Research”
Elbattah, M. 2019 · 2019
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“Solving challenges at the interface of simulation and big data using machine learning”
Giabbanelli, P. J. 2019 · 2019
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“Abstractive summarization: An overview of the state of the art”
Gupta, S., and S. K. Gupta. 2019 · 2019
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“Bringing molecular dynamics simulation data into view”
Hildebrand, P. W., A. S. Rose, and J. K. Tiemann. 2019 · 2019
Earlier work this paper cites.
“Vapor: A visualization package tailored to analyze simulation data in earth system science”
Li, S., S. Jaroszynski, S. Pearse, L. Orf, and J. Clyne. 2019 · 2019
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“Agent-based model characterization using natural language processing”
Padilla, J. J., D. Shuttleworth, and K. O’Brien. 2019 · 2019
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“From social media to expert reports: The impact of source selection on automatically validating complex conceptual models of obesity”
Sandhu, M., P. J. Giabbanelli, and V. K. Mago. 2019 · 2019
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“Flood risk management in sponge cities: The role of integrated simulation and 3D visualization”
Wang, C., J. Hou, D. Miller, I. Brown, and Y. Jiang. 2019 · 2019
Earlier work this paper cites.
“What is a preattentive feature?”
Wolfe, J. M., and I. S. Utochkin. 2019 · 2019
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“Three questions to ask before using model outputs for decision support”
Grimm, V., A. S. Johnston, H.-H. Thulke, V. Forbes, and P. Thorbek. 2020 · 2020
Earlier work this paper cites.
“Exploring the limits of transfer learning with a unified text-to-text transformer”
Raffel, C., N. Shazeer, A. Roberts, K. Lee, S. Narang, M. Matena, Y. Zhou, W. Li, and P. J. Liu. 2020 · 2020
Earlier work this paper cites.
“How to translate a verbal theory into a formal model”
Smaldino, P. E. 2020 · 2020
Earlier work this paper cites.
“Improving text-to-text pre-trained models for the graph-to-text task”
Yang, Z., A. Einolghozati, H. Inan, K. Diedrick, A. Fan, P. Donmez, and S. Gupta. 2020 · 2020
Cited alongside, same era.
“Automated Insights on Visualizations with Natural Language Generation”
Brath, R., and C. Hagerman. 2021 · 2021
Cited alongside, same era.
“Accessible visualization via natural language descriptions: A four-level model of semantic content”
Lundgard, A., and A. Satyanarayan. 2021 · 2021
Cited alongside, same era.
“Towards table-to-text generation with numerical reasoning”
Suadaa, L. H., H. Kamigaito, K. Funakoshi, M. Okumura, and H. Takamura. 2021 · 2021
Cited alongside, same era.
“Table to text generation with accurate content copying”
Yang, Y., J. Cao, Y. Wen, and P. Zhang. 2021 · 2021
Cited alongside, same era.
“Deep reinforcement and transfer learning for abstractive text summarization: A review”
“Pre-Trained Language Models and Their Applications”
Wang, H., J. Li, H. Wu, E. Hovy, and Y. Sun. 2022 · 2022
Later among the works it cites.
“Rich screen reader experiences for accessible data visualization”
Zong, J., C. Lee, A. Lundgard, J. Jang, D. Hajas, and A. Satyanarayan. 2022 · 2022
Later among the works it cites.
“A categorical archive of ChatGPT failures”
Borji, A. 2023 · 2023
Closest in time.
“Parameter-efficient fine-tuning of large-scale pre-trained language models”
Ding, N., Y. Qin, G. Yang, F. Wei, Z. Yang, Y. Su, S. Hu, Y. Chen, C.-M. Chan, W. Chen et al. 2023 · 2023
Closest in time.
“Should ChatGPT be Biased? Challenges and Risks of Bias in Large Language Models”
Ferrara, E. 2023 · 2023
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Alomari, A., N. Idris, A. Q. M. Sabri, and I. Alsmadi. 2022 · 2022
Cited alongside, same era.
“Palm: Scaling language modeling with pathways”
Chowdhery, A., S. Narang, J. Devlin, M. Bosma, G. Mishra, A. Roberts, P. Barham, H. W. Chung, C. Sutton, S. Gehrmann et al. 2022 · 2022
Cited alongside, same era.
“Automatically Generating Scenarios from a Text Corpus: A Case Study on Electric Vehicles”
Davis, C. W., A. J. Jetter, and P. J. Giabbanelli. 2022 · 2022
Cited alongside, same era.
“A survey of natural language generation”
Dong, C., Y. Li, H. Gong, M. Chen, J. Li, Y. Shen, and M. Yang. 2022 · 2022
Cited alongside, same era.
“Predictability and surprise in large generative models”
Ganguli, D., D. Hernandez, L. Lovitt, A. Askell, Y. Bai, A. Chen, T. Conerly, N. Dassarma, D. Drain, N. Elhage et al. 2022 · 2022
Cited alongside, same era.
“Demonstration of the Feasibility of Real Time Application of Machine Learning to Production Scheduling”
Ghasemi, A., K. E. Kabak, and C. Heavey. 2022 · 2022
Cited alongside, same era.
“Pathways to suicide or collections of vicious cycles? Understanding the complexity of suicide through causal mapping”
Giabbanelli, P. J., K. L. Rice, M. C. Galgoczy, N. Nataraj, M. M. Brown, C. R. Harper, M. D. Nguyen, and R. Foy. 2022 · 2022
Cited alongside, same era.
“Human Factors in Leveraging Systems Science to Shape Public Policy for Obesity: A Usability Study”
Giabbanelli, P. J., and C. X. Vesuvala. 2023 · 2023
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“Few-Shot Table-to-Text Generation with Prompt-based Adapter”
Guo, Z., M. Yan, J. Qi, J. Zhou, Z. He, Z. Lin, G. Zheng, and X. Wang. 2023 · 2023
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“Using ChatGPT to conduct a literature review”
Haman, M., and M. Školník. 2023 · 2023
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“Explainable Automated Debugging via Large Language Model-driven Scientific Debugging”
Kang, S., B. Chen, S. Yoo, and J.-G. Lou. 2023 · 2023
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“ArguGPT: evaluating, understanding and identifying argumentative essays generated by GPT models”
Liu, Y., Z. Zhang, W. Zhang, S. Yue, X. Zhao, X. Cheng, Y. Zhang, and H. Hu. 2023 · 2023
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“Fully Autonomous Programming with Large Language Models”
Liventsev, V., A. Grishina, A. Härmä, and L. Moonen. 2023 · 2023
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“Can large language models build causal graphs?”
Long, S., T. Schuster, A. Piché, S. Research et al. 2023 · 2023
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“AI chatbots can boost scientific coding”
Merow, C., J. M. Serra-Diaz, B. J. Enquist, and A. M. Wilson. 2023 · 2023
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“Marketing with ChatGPT: Navigating the Ethical Terrain of GPT-Based Chatbot Technology”
Rivas, P., and L. Zhao. 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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“ChatGPT is fun, but not an author”
Thorp, H Holden 2023 · 2023
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“ChatGPT: five priorities for research”
van Dis, E. A., J. Bollen, W. Zuidema, R. van Rooij, and C. L. Bockting. 2023 · 2023
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“A prompt pattern catalog to enhance prompt engineering with chatgpt”
White, J., Q. Fu, S. Hays, M. Sandborn, C. Olea, H. Gilbert, A. Elnashar, J. Spencer-Smith, and D. C. Schmidt. 2023 · 2023
Closest in time.
“Understanding Causality with Large Language Models: Feasibility and Opportunities”
Zhang, C., S. Bauer, P. Bennett, J. Gao, W. Gong, A. Hilmkil, J. Jennings, C. Ma, T. Minka, N. Pawlowski et al. 2023 · 2023
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“Enhancing RDF Verbalization with Descriptive and Relational Knowledge”
Zhang, F., M. Zhang, S. Liu, Y. Sun, and N. Duan. 2023 · 2023
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“ChatGPT: Potential, prospects, and limitations”
Zhou, J., P. Ke, X. Qiu, M. Huang, and J. Zhang. 2023 · 2023
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“ChatGPT and environmental research”
Zhu, J.-J., J. Jiang, M. Yang, and Z. J. Ren. 2023 · 2023
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