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In this work, we investigate the potential of large language models (LLMs) based agents to automate data science tasks, with the goal of comprehending task requirements, then building and training the best-fit machine learning models.
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Chase, H · 2022
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De Bie, T., De Raedt, L., Hernández-Orallo, J., Hoos, H. H., Smyth, P., and Williams, C. K · 2022
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OpenAI · 2022
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Rubin, O., Herzig, J., and Berant, J · 2022
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Boiko, D. A., MacKnight, R., Kline, B., and Gomes, G · 2023
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Chen, B., Shu, C., Shareghi, E., Collier, N., Narasimhan, K., and Yao, S · 2023
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Pangu-agent: A fine-tunable generalist agent with structured reasoning
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OpenAI · 2023
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Mathematical discoveries from program search with large language models
Romera-Paredes, B., Barekatain, M., Novikov, A., Balog, M., Kumar, M. P., Dupont, E., Ruiz, F. J., Ellenberg, J. S., Wang, P., Fawzi, O., et al · 2023
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Hugginggpt: Solving ai tasks with chatgpt and its friends in huggingface
Shen, Y., Song, K., Tan, X., Li, D., Lu, W., and Zhuang, Y · 2023
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K2: A foundation language model for geoscience knowledge understanding and utilization
Deng, C., Zhang, T., He, Z., Chen, Q., Shi, Y., Zhou, L., Fu, L., Zhang, W., Wang, X., Zhou, C., Lin, Z., and He, J · 2023
Cited alongside, same era.
Retrieval-augmented generation for large language models: A survey
Gao, Y., Xiong, Y., Gao, X., Jia, K., Pan, J., Bi, Y., Dai, Y., Sun, J., and Wang, H · 2023
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A case-based reasoning framework for adaptive prompting in cross-domain text-to-sql
Guo, C., Tian, Z., Tang, J., Wang, P., Wen, Z., Yang, K., and Wang, T · 2023
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Large language models for automated data science: Introducing caafe for context-aware automated feature engineering
Hollmann, N., Müller, S., and Hutter, F · 2023
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Benchmarking large language models as ai research agents
Huang, Q., Vora, J., Liang, P., and Leskovec, J · 2023
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Language models can solve computer tasks
Kim, G., Baldi, P., and McAleer, S. M · 2023
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Efficient memory management for large language model serving with pagedattention
Kwon, W., Li, Z., Zhuang, S., Sheng, Y., Zheng, L., Yu, C. H., Gonzalez, J., Zhang, H., and Stoica, I · 2023
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Reflexion: Language agents with verbal reinforcement learning
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Significant Gravitas · 2023
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Case-based reasoning with language models for classification of logical fallacies
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Is ChatGPT good at search? investigating large language models as re-ranking agents
Sun, W., Yan, L., Ma, X., Wang, S., Ren, P., Chen, Z., Yin, D., and Ren, Z · 2023
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Autogen: Enabling next-gen llm applications via multi-agent conversation framework
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End-to-end case-based reasoning for commonsense knowledge base completion
Yang, Z., Du, X., Cambria, E., and Cardie, C · 2023
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Agenttuning: Enabling generalized agent abilities for llms
Zeng, A., Liu, M., Lu, R., Wang, B., Liu, X., Dong, Y., and Tang, J · 2023
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Jiang, A. Q., Sablayrolles, A., Roux, A., Mensch, A., Savary, B., Bamford, C., Chaplot, D. S., Casas, D. d. l., Hanna, E. B., Bressand, F., et al · 2024
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Memory disagreement: A pseudo-labeling measure from training dynamics for semi-supervised graph learning
Pei, H., Xiong, Y., Wang, P., Tao, J., Liu, J., Deng, H., Ma, J., and Guan, X · 2024
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Expel: Llm agents are experiential learners
Zhao, A., Huang, D., Xu, Q., Lin, M., Liu, Y.-J., and Huang, G · 2024
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