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Large language models (LLMs) have recently taken the world by storm.
Methods for visual understanding of hierarchical system structures
Sugiyama K., Tagawa S., Toda M · 1981
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A technique for drawing directed graphs
Gansner E. R., Koutsofios E., North S. C., Vo K.-P · 1993
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Drawing directed acyclic graphs: An experimental study
Battista G. D., Garg A., Liotta G., Parise A., Tamassia R., Tassinari E., Vargiu F., Vismara L · 2000
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Metrics for graph drawing aesthetics
Purchase H. C · 2002
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Graph Drawing and Applications for Software and Knowledge Engineers
Sugiyama K · 2002
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Design considerations for optimizing StoryLine visualizations
liu Ma Y. T. K · 2012
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Hierarchical drawing algorithms
Healy P., Nikolov N. S · 2013
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Aesthetic discrimination of graph layouts
Klammler M., Mchedlidze T., Pak A · 2018
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BERT: Pre-training of deep bidirectional transformers for language understanding, May 2019
Devlin J., Chang M.-W., Lee K., Toutanova K · 2019
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Symmetry detection and classification in drawings of graphs
De Luca F., Hossain M. I., Kobourov S · 2019
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A deep generative model for graph layout
Kwon O.-H., Ma K.-L · 2019
Cited alongside, same era.
Language models are few-shot learners
Brown T., Mann B., Ryder N., Subbiah M., Kaplan J. D., 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., 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., Amodei D · 2020
Cited alongside, same era.
Language models are unsupervised multitask learners, 2020
Radford A., Wu J., Child R., Luan D., Amodei D., Sutskever I · 2020
Cited alongside, same era.
Evaluating large language models trained on code, July 2021
Chen M., Tworek J., Jun H., Yuan Q., Pinto H. P. d. O., Kaplan J., Edwards H., Burda Y., Joseph N., Brockman G., Ray A., Puri R., Krueger G., Petrov M., Khlaaf H., Sastry G., Mishkin P., Chan B., Gray S., Ryder N., Pavlov M., Power A., Kaiser L., Bavarian M., Winter C., Tillet P., Such F. P., Cummings D., Plappert M., Chantzis F., Barnes E., Herbert-Voss A., Guss W. H., Nichol A., Paino A., Tezak N., Tang J., Babuschkin I., Balaji S., Jain S., Saunders W., Hesse C., Carr A. N., Leike J., Achiam J., Misra V., Morikawa E., Radford A., Knight M., Brundage M., Murati M., Mayer K., Welinder P., McGrew B., Amodei D., McCandlish S., Sutskever I., Zaremba W · 2021
Cited alongside, same era.
Mapping language models to grounded conceptual spaces
Patel R., Pavlick E · 2022
Later among the works it cites.
An explanation of in-context learning as implicit Bayesian inference
Xie S. M., Raghunathan A., Liang P., Ma T · 2022
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Designing computational evaluations for graph layout algorithms: the state of the art, Mar 2023
Di Bartolomeo S., Crnovrsanin T., Saffo D., Dunne C · 2023
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Using GPT-3 to pathfind in random graphs
Jacob Brazeal · 2023
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ChatGPT: Jack of all trades, master of none, Feb. 2023
Kocoń J., Cichecki I., Kaszyca O., Kochanek M., Szydło D., Baran J., Bielaniewicz J., Gruza M., Janz A., Kanclerz K., Kocoń A., Koptyra B., Mieleszczenko-Kowszewicz W., Miłkowski P., Oleksy M., Piasecki M., Radliński Ł., Wojtasik K., Woźniak S., Kazienko P · 2023
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STRATISFIMAL LAYOUT: A modular optimization model for laying out layered node-link network visualizations
Di Bartolomeo S., Riedewald M., Gatterbauer W., Dunne C · 2021
Cited alongside, same era.
Deep neural network for DrawiNg networks
Giovannangeli L., Lalanne F., Auber D., Giot R., Bourqui R · 2021
Cited alongside, same era.
Liu P., Yuan W., Fu J., Jiang Z., Hayashi H., Neubig G · 2021
Cited alongside, same era.
Large language models are zero-shot reasoners
Kojima T., Gu S. S., Reid M., Matsuo Y., Iwasawa Y · 2022
Cited alongside, same era.
ChatGPT: Optimizing language models for dialogue, Nov. 2022
OpenAI · 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., Gray A., Schulman J., Hilton J., Kelton F., Miller L., Simens M., Askell A., Welinder P., Christiano P., Leike J., Lowe R · 2022
Cited alongside, same era.
Improving language understanding by generative pre-training
Radford A., Narasimhan K., Salimans T., Sutskever I
Cited in the paper.
Mahowald K., Ivanova A. A., Blank I. A., Kanwisher N., Tenenbaum J. B., Fedorenko E · 2023
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OpenAI API, 2023
OpenAI · 2023
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Doom or deliciousness: Challenges and opportunities for visualization in the age of generative models, Jan 2023
Schetinger V., Di Bartolomeo S., El-Assady M., McNutt A. M., Miller M., Adams J. L · 2023
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Emergent abilities of large language models
Wei J., Tay Y., Bommasani R., Raffel C., Zoph B., Borgeaud S., Yogatama D., Bosma M., Zhou D., Metzler D., Chi E. H., Hashimoto T., Vinyals O., Liang P., Dean J., Fedus W · 2023
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