DIALGEN: collaborative human-lm generated dialogues for improved understanding of human-human...

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The rise and potential of large language model based agents: A survey

Z Xi, W Chen, X Guo, W He, Y Ding, B Hong… - arXiv preprint arXiv …, 2023 - arxiv.org
For a long time, humanity has pursued artificial intelligence (AI) equivalent to or surpassing
the human level, with AI agents considered a promising vehicle for this pursuit. AI agents are …
被引用次数：345 相关文章 所有 4 个版本
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Data augmentation using llms: Data perspectives, learning paradigms and challenges

B Ding, C Qin, R Zhao, T Luo, X Li, G Chen… - arXiv preprint arXiv …, 2024 - arxiv.org
In the rapidly evolving field of machine learning (ML), data augmentation (DA) has emerged
as a pivotal technique for enhancing model performance by diversifying training examples …
被引用次数：14 相关文章 所有 3 个版本
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Llm-powered hierarchical language agent for real-time human-ai coordination

J Liu, C Yu, J Gao, Y Xie, Q Liao, Y Wu… - arXiv preprint arXiv …, 2023 - arxiv.org
AI agents powered by Large Language Models (LLMs) have made significant advances,
enabling them to assist humans in diverse complex tasks and leading to a revolution in …
被引用次数：8 相关文章 所有 6 个版本
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Encode Once and Decode in Parallel: Efficient Transformer Decoding

BR Lu, N Haduong, CY Lin, H Cheng, NA Smith… - arXiv preprint arXiv …, 2024 - arxiv.org
Transformer-based NLP models are powerful but have high computational costs that limit
deployment scenarios. Finetuned encoder-decoder models are popular in specialized …
相关文章 所有 2 个版本
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Tapilot-Crossing: Benchmarking and Evolving LLMs Towards Interactive Data Analysis Agents

J Li, N Huo, Y Gao, J Shi, Y Zhao, G Qu, Y Wu… - arXiv preprint arXiv …, 2024 - arxiv.org
Interactive Data Analysis, the collaboration between humans and LLM agents, enables real-
time data exploration for informed decision-making. The challenges and costs of collecting …
被引用次数：2 相关文章 所有 2 个版本
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Prompt Framework for Role-playing: Generation and Evaluation

X Liu, Z Ni - arXiv preprint arXiv:2406.00627, 2024 - arxiv.org
Large language models (LLM) have demonstrated remarkable abilities in generating natural
language, understanding user instruction, and mimicking human language use. These …
相关文章 所有 2 个版本