Fetching the paper…
Reading the bibliography…
Multi-agent Large Language Model (LLM) systems have been leading the way in applied LLM research across a number of fields.
E. Letier, D. Stefan, and E. T. Barr, “Uncertainty, risk, and information value in software requirements and architecture,” in Proceedings of the 36th International Conference on Software Engineering , 2014, pp. 883–894
2014
Earlier work this paper cites.
A. Hussain, E. O. Mkpojiogu, and F. M. Kamal, “The role of requirements in the success or failure of software projects,” International Review of Management and Marketing , vol. 6, no. 7, pp. 306–311, 2016
2016
Earlier work this paper cites.
J. Shore and S. Warden, The art of agile development . ” O’Reilly Media, Inc.”, 2021
2021
Earlier work this paper cites.
M. C. et al., “Evaluating large language models trained on code,” 2021
2021
Earlier work this paper cites.
A. N. Meyer, E. T. Barr, C. Bird, and T. Zimmermann, “Today was a good day: The daily life of software developers,” IEEE Transactions on Software Engineering , vol. 47, no. 05, pp. 863–880, may 2021
2021
Earlier work this paper cites.
S. Alamir, P. Babkin, N. Navarro, and S. Shah, “AI for automated code updates,” in Proceedings of the 44th International Conference on Software Engineering: Software Engineering in Practice , 2022, pp. 25–26
2022
Earlier work this paper cites.
J. S. Park, J. O’Brien, C. J. Cai, M. R. Morris, P. Liang, and M. S. Bernstein, “Generative agents: Interactive simulacra of human behavior,” in Proceedings of the 36th annual acm symposium on user interface software and technology , 2023, pp. 1–22
2023
Earlier work this paper cites.
2023
Earlier work this paper cites.
2023
Earlier work this paper cites.
C. S. Xia, Y. Wei, and L. Zhang, “Automated program repair in the era of large pre-trained language models,” in 2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE) . IEEE, 2023, pp. 1482–1494
2023
Earlier work this paper cites.
M. Leung and G. Murphy, “On automated assistants for software development: The role of llms,” in 2023 38th IEEE/ACM International Conference on Automated Software Engineering (ASE) , 2023, pp. 1737–1741
2023
Cited alongside, same era.
V. Tawosi, S. Alamir, and X. Liu, Search-Based Optimisation of LLM Learning Shots for Story Point Estimation . Springer Nature Switzerland, Dec. 2023, p. 123–129. [Online]. Available: http://dx.doi.org/10.1007/978-3-031-48796-5_9
2023
Cited alongside, same era.
2024
Cited alongside, same era.
D. Nam, A. Macvean, V. Hellendoorn, B. Vasilescu, and B. Myers, “Using an llm to help with code understanding,” in Proceedings of the IEEE/ACM 46th International Conference on Software Engineering , 2024, pp. 1–13
2024
Cited alongside, same era.
2024
Later among the works it cites.
2024
Later among the works it cites.
R. I. T. Jensen, V. Tawosi, and S. Alamir, “Software vulnerability and functionality assessment using llms,” 2024
2024
Later among the works it cites.
I. Ong, A. Almahairi, V. Wu, W.-L. Chiang, T. Wu, J. E. Gonzalez, M. W. Kadous, and I. Stoica, “Routellm: Learning to route llms from preference data,” in The Thirteenth International Conference on Learning Representations , 2024
2024
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
2024
Cited alongside, same era.
2024
Cited alongside, same era.
2024
Cited alongside, same era.
G. Ryan, S. Jain, M. Shang, S. Wang, X. Ma, M. K. Ramanathan, and B. Ray, “Code-aware prompting: A study of coverage-guided test generation in regression setting using llm,” Proceedings of the ACM on Software Engineering , vol. 1, no. FSE, pp. 951–971, 2024
2024
Cited alongside, same era.
2024
Cited alongside, same era.
X. Li, S. Wang, S. Zeng, Y. Wu, and Y. Yang, “A survey on llm-based multi-agent systems: workflow, infrastructure, and challenges,” Vicinagearth , vol. 1, no. 1, p. 9, Oct 2024. [Online]. Available: https://doi.org/10.1007/s44336-024-00009-2
2024
Cited alongside, same era.
M. Becattini, R. Verdecchia, and E. Vicario, “Sallma: A software architecture for llm-based multi-agent systems,” in 2025 IEEE/ACM International Workshop New Trends in Software Architecture (SATrends) , 2025, pp. 5–8
2025
Closest in time.
2025
Closest in time.
2025
Closest in time.
2025
Closest in time.
K. Ramani, V. Tawosi, S. Alamir, and D. Borrajo, “Bridging llm planning agents and formal methods: A case study in plan verification,” in Proceedings of the 1st International Workshop on Autonomous Agents in Software Engineering (AgenticSE) , 2025
2025
Closest in time.