Large-Language-Model-Powered Agent-Based Framework for Misinformation and Disinformation Research: Opportunities and Open Challenges

doi:10.1145/3305260

K. Sharma, F. Qian, H. Jiang, N. Ruchansky, M. Zhang, Y. Liu, Combating fake news: A survey on identification and mitigation techniques, ACM Trans. Intell. Syst. Technol. 10 (3) (apr 2019) · 2019

Earlier work this paper cites.

doi:10.1109/WSC40007.2019.9004942

D. M. Beskow, K. M. Carley, Agent based simulation of bot disinformation maneuvers in twitter, in: 2019 Winter Simulation Conference (WSC), 2019, pp. 750–761 · 2019

Earlier work this paper cites.

doi:10.1109/TNSM.2020.3031573

J. Pastor-Galindo, M. Zago, P. Nespoli, S. L. Bernal, A. H. Celdrán, M. G. Pérez, J. A. Ruipérez-Valiente, G. M. Pérez, F. G. Mármol, Spotting political social bots in twitter: A use case of the 2019 spanish general election, IEEE Transactions on Network and Service Management 17 (4) (2020) 2156–2170 · 2020

Earlier work this paper cites.

arXiv:2301.04655

Original

R. Gozalo-Brizuela, E. C. Garrido-Merchan, ChatGPT is not all you need. A State of the Art Review of large Generative AI models (2023) · 2023

Earlier work this paper cites.

arXiv:2305.03514

Original

C. Ziems, W. Held, O. Shaikh, J. Chen, Z. Zhang, D. Yang, Can large language models transform computational social science? (2023) · 2023

Earlier work this paper cites.

doi:10.1145/3586183.3606763

J. S. Park, J. O’Brien, C. J. Cai, M. R. Morris, P. Liang, M. S. Bernstein, Generative agents: Interactive simulacra of human behavior, in: Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology, UIST ’23, Association for Computing Machinery, New York, NY, USA, 2023 · 2023

Cited alongside, same era.

arXiv:2309.02427

Original

T. R. Sumers, S. Yao, K. Narasimhan, T. L. Griffiths, Cognitive architectures for language agents (2023) · 2023

Cited alongside, same era.

arXiv:2307.14984

Original

C. Gao, X. Lan, Z. Lu, J. Mao, J. Piao, H. Wang, D. Jin, Y. Li, S 3 : Social-network simulation system with large language model-empowered agents (2023) · 2023

Cited alongside, same era.

arXiv:2305.02547

Original

H. Jiang, X. Zhang, X. Cao, J. Kabbara, Personallm: Investigating the ability of gpt-3.5 to express personality traits and gender differences (2023) · 2023

Cited alongside, same era.

doi:10.1145/3560815

P. Liu, W. Yuan, J. Fu, Z. Jiang, H. Hayashi, G. Neubig, Pre-train, prompt, and predict: A systematic survey of prompting methods in natural language processing, ACM Computing Surveys 55 (1 2023) · 2023

Closest in time.

doi:doi.org/10.1080/15228053.2023.2233814

F. Fui-Hoon Nah, R. Zheng, J. Cai, K. Siau, L. Chen, Generative AI and ChatGPT: Applications, challenges, and AI-human collaboration, Journal of Information Technology Case and Application Research 25 (3) (2023) 277–304 · 2023

Closest in time.

doi:10.1109/EuroSPW59978.2023.00055

M. Sharma, K. Singh, P. Aggarwal, V. Dutt, How well does gpt phish people? an investigation involving cognitive biases and feedback, in: 2023 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW), IEEE Computer Society, Los Alamitos, CA, USA, 2023, pp. 451–457 · 2023

Closest in time.

R. G.-B. Alejo José G. Sison, Marco Tulio Daza, E. C. Garrido-Merchán, ChatGPT: More Than a “Weapon of Mass Deception” Ethical Challenges and Responses from the Human-Centered Artificial Intelligence (HCAI) Perspective, International Journal of Human–Computer Interaction (2023) 1–20 doi:10.1080/10447318.2023.2225931

2023

Closest in time.