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With the rapid development of Large Language Models (LLMs), LLM-based agents have been widely adopted in various fields, becoming essential for autonomous decision-making and interactive tasks.
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Fireact: Toward language agent fine-tuning
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Agentcoder: Multi-agent-based code generation with iterative testing and optimisation
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Recommender ai agent: Integrating large language models for interactive recommendations
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Paperqa: Retrieval-augmented generative agent for scientific research
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Toolllm: Facilitating large language models to master 16000+ real-world apis
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TPTU: large language model-based AI agents for task planning and tool usage
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Large language models encode clinical knowledge
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Toolalpaca: Generalized tool learning for language models with 3000 simulated cases
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Voyager: An open-ended embodied agent with large language models
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Autogen: Enabling next-gen llm applications via multi-agent conversation
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Chain-of-experts: When llms meet complex operations research problems. In The twelfth international conference on learning representations
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Doctorglm: Fine-tuning your chinese doctor is not a herculean task
Honglin Xiong, Sheng Wang, Yitao Zhu, Zihao Zhao, Yuxiao Liu, Linlin Huang, Qian Wang, and Dinggang Shen. 2023 · 2023
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Retroformer: Retrospective large language agents with policy gradient optimization
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Generate rather than retrieve: Large language models are strong context generators. In International Conference for Learning Representation (ICLR)
Wenhao Yu, Dan Iter, Shuohang Wang, Yichong Xu, Mingxuan Ju, Soumya Sanyal, Chenguang Zhu, Michael Zeng, and Meng Jiang. 2023 · 2023
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Agenttuning: Enabling generalized agent abilities for llms
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Instruction tuning for large language models: A survey
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Judging llm-as-a-judge with mt-bench and chatbot arena
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Lima: Less is more for alignment
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SciAgent: Tool-augmented Language Models for Scientific Reasoning. In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing . 15701–15736
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