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Recent advances in large language models (LLMs) have shown impressive performance in mathematical reasoning and code generation.
Evaluating large language models trained on code
Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Ponde De Oliveira Pinto, Jared Kaplan, Harri Edwards, Yuri Burda, Nicholas Joseph, Greg Brockman, et al · 2021
Earlier work this paper cites.
Slgpt: Using transfer learning to directly generate simulink model files and find bugs in the simulink toolchain
Sohil Lal Shrestha and Christoph Csallner · 2021
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Competition-level code generation with alphacode
Yujia Li, David Choi, Junyoung Chung, Nate Kushman, Julian Schrittwieser, Rémi Leblond, Tom Eccles, James Keeling, Felix Gimeno, Agustin Dal Lago, et al · 2022
Earlier work this paper cites.
Chain-of-thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Fei Xia, Ed Chi, Quoc V Le, Denny Zhou, et al · 2022
Earlier work this paper cites.
Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al · 2023
Earlier work this paper cites.
Camel: Communicative agents for" mind" exploration of large language model society
Guohao Li, Hasan Hammoud, Hani Itani, Dmitrii Khizbullin, and Bernard Ghanem · 2023
Earlier work this paper cites.
Codegen: An open large language model for code with multi-turn program synthesis
Erik Nijkamp, Bo Pang, Hiroaki Hayashi, Lifu Tu, Huan Wang, Yingbo Zhou, Silvio Savarese, and Caiming Xiong · 2023
Earlier work this paper cites.
A survey of large language models for code: Evolution, benchmarking, and future trends
Zibin Zheng, Kaiwen Ning, Yanlin Wang, Jingwen Zhang, Dewu Zheng, Mingxi Ye, and Jiachi Chen · 2023
Earlier work this paper cites.
Generative artificial intelligence for model-based graphical programming in automotive function development
Abdelrahman Abdalla, Harsh Pandey, Behzad Shomali, Joschka Schaub, Arne Müller, Markus Eisenbarth, and Jakob Andert · 2024
Earlier work this paper cites.
Extending context window of large language models via semantic compression
Weizhi Fei, Xueyan Niu, Pingyi Zhou, Lu Hou, Bo Bai, Lei Deng, and Wei Han · 2024
Earlier work this paper cites.
Budgetmlagent: A cost-effective llm multi-agent system for automating machine learning tasks
Shubham Gandhi, Manasi Patwardhan, Lovekesh Vig, and Gautam Shroff · 2024
Cited alongside, same era.
CRITIC: Large language models can self-correct with tool-interactive critiquing
Zhibin Gou, Zhihong Shao, Yeyun Gong, yelong shen, Yujiu Yang, Nan Duan, and Weizhu Chen · 2024
Cited alongside, same era.
DS-agent: Automated data science by empowering large language models with case-based reasoning
Siyuan Guo, Cheng Deng, Ying Wen, Hechang Chen, Yi Chang, and Jun Wang · 2024
Cited alongside, same era.
Data interpreter: An llm agent for data science
Sirui Hong, Yizhang Lin, Bang Liu, Bangbang Liu, Binhao Wu, Ceyao Zhang, Chenxing Wei, Danyang Li, Jiaqi Chen, Jiayi Zhang, et al · 2024
Cited alongside, same era.
Aaron Hurst, Adam Lerer, Adam P Goucher, Adam Perelman, Aditya Ramesh, Aidan Clark, AJ Ostrow, Akila Welihinda, Alan Hayes, Alec Radford, et al · 2024
ChatDev: Communicative agents for software development
Chen Qian, Wei Liu, Hongzhang Liu, Nuo Chen, Yufan Dang, Jiahao Li, Cheng Yang, Weize Chen, Yusheng Su, Xin Cong, Juyuan Xu, Dahai Li, Zhiyuan Liu, and Maosong Sun · 2024
Later among the works it cites.
CodeAgent: Autonomous communicative agents for code review
Xunzhu Tang, Kisub Kim, Yewei Song, Cedric Lothritz, Bei Li, Saad Ezzini, Haoye Tian, Jacques Klein, and Tegawendé F. Bissyandé · 2024
Later among the works it cites.
Swe-agent: Agent-computer interfaces enable automated software engineering
John Yang, Carlos E Jimenez, Alexander Wettig, Kilian Lieret, Shunyu Yao, Karthik Narasimhan, and Ofir Press · 2024
Later among the works it cites.
Ke Yang, Jiateng Liu, John Wu, Chaoqi Yang, Yi R Fung, Sha Li, Zixuan Huang, Xu Cao, Xingyao Wang, Yiquan Wang, et al · 2024
Later among the works it cites.
Chain of agents: Large language models collaborating on long-context tasks
Yusen Zhang, Ruoxi Sun, Yanfei Chen, Tomas Pfister, Rui Zhang, and Sercan Arik · 2024
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Cited alongside, same era.
Swe-bench: Can language models resolve real-world github issues?
Carlos E Jimenez, John Yang, Alexander Wettig, Shunyu Yao, Kexin Pei, Ofir Press, and Karthik R Narasimhan · 2024
Cited alongside, same era.
Long-context llms struggle with long in-context learning
Tianle Li, Ge Zhang, Quy Duc Do, Xiang Yue, and Wenhu Chen · 2024
Cited alongside, same era.
Toward automated simulation research workflow through llm prompt engineering design
Zhihan Liu, Yubo Chai, and Jianfeng Li · 2024
Cited alongside, same era.
Towards fully autonomous research powered by llms: Case study on simulations
Zhihan Liu, Yubo Chai, and Jianfeng Li · 2024
Cited alongside, same era.
Requirements-driven slicing of simulink models using llms
Dipeeka Luitel, Shiva Nejati, and Mehrdad Sabetzadeh · 2024
Cited alongside, same era.
Later among the works it cites.
DSBench: How far are data science agents from becoming data science experts?
Liqiang Jing, Zhehui Huang, Xiaoyang Wang, Wenlin Yao, Wenhao Yu, Kaixin Ma, Hongming Zhang, Xinya Du, and Dong Yu · 2025
Closest in time.
Autokaggle: A multi-agent framework for autonomous data science competitions
Ziming Li, Qianbo Zang, David Ma, Jiawei Guo, Tianyu Zheng, Minghao Liu, Xinyao Niu, Yue Wang, Jian Yang, Jiaheng Liu, Wanjun Zhong, Wangchunshu Zhou, Stephen Huang, and Ge Zhang · 2025
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Hm-rag: Hierarchical multi-agent multimodal retrieval augmented generation
Pei Liu, Xin Liu, Ruoyu Yao, Junming Liu, Siyuan Meng, Ding Wang, and Jun Ma · 2025
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Simulink - simulation and model-based design, 2025
MathWorks · 2025
Closest in time.