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The outstanding capabilities of large language models (LLMs) render them a crucial component in various autonomous agent systems.
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Chain-of-thought prompting elicits reasoning in large language models
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FireAct: Toward Language Agent Fine-tuning
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AgentTuning: Enabling Generalized Agent Abilities for LLMs
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Enhancing generative retrieval with reinforcement learning from relevance feedback. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing . 12481–12490
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Agent-FLAN: Designing Data and Methods of Effective Agent Tuning for Large Language Models
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Mind2web: Towards a generalist agent for the web
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Self-refine: Iterative refinement with self-feedback
Aman Madaan, Niket Tandon, Prakhar Gupta, Skyler Hallinan, Luyu Gao, Sarah Wiegreffe, Uri Alon, Nouha Dziri, Shrimai Prabhumoye, Yiming Yang, et al · 2024
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Reflexion: Language agents with verbal reinforcement learning
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Trial and Error: Exploration-Based Trajectory Optimization of LLM Agents. In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , Lun-Wei Ku, Andre Martins, and Vivek Srikumar (Eds.). Association for Computational Linguistics, Bangkok, Thailand, 7584–7600
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A survey on large language model based autonomous agents
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Tree of thoughts: Deliberate problem solving with large language models
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Agent Lumos: Unified and Modular Training for Open-Source Language Agents
Da Yin, Faeze Brahman, Abhilasha Ravichander, Khyathi Chandu, Kai-Wei Chang, Yejin Choi, and Bill Yuchen Lin. 2024 · 2024
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Metacognitive retrieval-augmented large language models. In Proceedings of the ACM on Web Conference 2024 . 1453–1463
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