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Recently, as Large Language Models (LLMs) have shown impressive emerging capabilities and gained widespread popularity, research on LLM-based search agents has proliferated.
C. Wang, N. Duan, M. Zhou, and M. Zhang, “Paraphrasing adaptation for web search ranking,” in Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers) , 2013, pp. 41-46
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2018
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P. Lewis et al., “Retrieval-augmented generation for knowledge-intensive NLP tasks,” Advances in Neural Information Processing Systems, vol. 33, pp. 9459–9474, 2020
2020
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2021
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2022
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2022
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J. Wei et al., “Chain-of-thought prompting elicits reasoning in large language models,” Advances in Neural Information Processing Systems, vol. 35, pp. 24824–24837, 2022
2022
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Q. Dong et al., “A survey on in-context learning,” arXiv:2301.00234, 2022
2022
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2022
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A. Mallen, A. Asai, V. Zhong, R. Das, H. Hajishirzi, and D. Khashabi, “When not to trust language models: Investigating effectiveness and limitations of parametric and non-parametric memories,” arXiv preprint , 2022
2022
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2023
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2023
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F. Shi et al., “Large language models can be easily distracted by irrelevant context,” in Proc. Int. Conf. Mach. Learn., PMLR, 2023, pp. 31210–31227
2023
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2024
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S. Hong et al., “Data Interpreter: a LLM Agent For Data Science,” arXiv:2402.18679, 2024
2024
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Cognition Labs, “Introducing Devin: The First AI Software Engineer,” 2024. [Online]. Available: https://www.cognition-labs.com/introducing-devin
2024
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PRAW, “Python Reddit API Wrapper,” GitHub repository, 2024. [Online]. Available: https://github.com/praw-dev/praw
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2023
Cited alongside, same era.
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Cited alongside, same era.
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Cited alongside, same era.
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Cited alongside, same era.
2023
Cited alongside, same era.
2023
Cited alongside, same era.
Y. Zhou, Z. Liu, J. Jin, J. Y. Nie, and Z. Dou, “Metacognitive retrieval-augmented large language models,” in Proc. ACM Web Conf. 2024, 2024, pp. 1453–1463
2024
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2024
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Google, “Gemma 2 model” Hugging Face, 2024. [Online]. Available: https://huggingface.co/google/gemma-2-2b-it
2024
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AI@Meta, “Llama 3 Model,” GitHub Repository, 2024. [Online]. Available: https://github.com/meta-llama/llama3/tree/main
2024
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Mistral AI Team, “Model Card for Mistral-7B-Instruct-v0.3,” Hugging Face, 2024. [Online]. Available: https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3
2024
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Tavily AI, “Tavily Search API,” GitHub Repository, 2024. [Online]. Available: https://github.com/tavily-ai/tavily-python
2024
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SerpAPI, “SerpAPI: Real-time search engine results API,” SerpAPI, 2024. [Online]. Available: https://serpapi.com/
2024
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Google, “Custom Search JSON API,” Google Developers, 2024. [Online]. Available: https://developers.google.com/custom-search/v1/overview
2024
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Tavily, “Tavily API Documentation,” Tavily Documentation, 2024. [Online]. Available: https://docs.tavily.com/docs/welcome
2024
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N. F. Liu et al., “Lost in the middle: How language models use long contexts,” Trans. Assoc. Comput. Linguistics, vol. 12, pp. 157-173, 2024
2024
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