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Numerous large language model (LLM) agents have been built for different tasks like web navigation and online shopping due to LLM's wide knowledge and text-understanding ability.
Pddl| the planning domain definition language
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Mind2Web: Towards a Generalist Agent for the Web. In Proceedings of the 37th Advances in Neural Information Processing Systems (NeurIPS)
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LLM+P: Empowering large language models with optimal planning proficiency
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Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, Aurelien Rodriguez, Armand Joulin, Edouard Grave, and Guillaume Lample. 2023 · 2023
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A survey on large language model based autonomous agents
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Self-Adaptive In-Context Learning: An Information Compression Perspective for In-Context Example Selection and Ordering. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (ACL) . 1423–1436
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Large Language Models are Versatile Decomposers: Decomposing Evidence and Questions for Table-based Reasoning. In Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) . 174–184
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Least-to-Most Prompting Enables Complex Reasoning in Large Language Models. In The 11th International Conference on Learning Representations (ICLR)
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Large language models for information retrieval: A survey
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A Real-World WebAgent with Planning, Long Context Understanding, and Program Synthesis. In Proceedings of The 12th International Conference on Learning Representations (ICLR)
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Generative Relevance Feedback with Large Language Models. In Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) . 2026–2031
Iain Mackie, Shubham Chatterjee, and Jeffrey Dalton. 2023 · 2031
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