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

Z **, W Chen, X Guo, W He, Y Ding, B Hong… - Science China …, 2025 - Springer
For a long time, researchers have sought artificial intelligence (AI) that matches or exceeds
human intelligence. AI agents, which are artificial entities capable of sensing the …

A survey on large language model based autonomous agents

L Wang, C Ma, X Feng, Z Zhang, H Yang… - Frontiers of Computer …, 2024 - Springer
Autonomous agents have long been a research focus in academic and industry
communities. Previous research often focuses on training agents with limited knowledge …

Trustllm: Trustworthiness in large language models

Y Huang, L Sun, H Wang, S Wu, Q Zhang, Y Li… - arxiv preprint arxiv …, 2024 - arxiv.org
Large language models (LLMs), exemplified by ChatGPT, have gained considerable
attention for their excellent natural language processing capabilities. Nonetheless, these …

[HTML][HTML] Position: TrustLLM: Trustworthiness in large language models

Y Huang, L Sun, H Wang, S Wu… - International …, 2024 - proceedings.mlr.press
Large language models (LLMs) have gained considerable attention for their excellent
natural language processing capabilities. Nonetheless, these LLMs present many …

Agentbench: Evaluating llms as agents

X Liu, H Yu, H Zhang, Y Xu, X Lei, H Lai, Y Gu… - arxiv preprint arxiv …, 2023 - arxiv.org
Large Language Models (LLMs) are becoming increasingly smart and autonomous,
targeting real-world pragmatic missions beyond traditional NLP tasks. As a result, there has …

Tool learning with large language models: A survey

C Qu, S Dai, X Wei, H Cai, S Wang, D Yin, J Xu… - Frontiers of Computer …, 2025 - Springer
Recently, tool learning with large language models (LLMs) has emerged as a promising
paradigm for augmenting the capabilities of LLMs to tackle highly complex problems …

Evaluating large language models: A comprehensive survey

Z Guo, R **, C Liu, Y Huang, D Shi, L Yu, Y Liu… - arxiv preprint arxiv …, 2023 - arxiv.org
Large language models (LLMs) have demonstrated remarkable capabilities across a broad
spectrum of tasks. They have attracted significant attention and been deployed in numerous …

Controlllm: Augment language models with tools by searching on graphs

Z Liu, Z Lai, Z Gao, E Cui, Z Li, X Zhu, L Lu… - … on Computer Vision, 2024 - Springer
We present ControlLLM, a novel framework that enables large language models (LLMs) to
utilize multi-modal tools for solving complex real-world tasks. Despite the remarkable …

Metatool benchmark for large language models: Deciding whether to use tools and which to use

Y Huang, J Shi, Y Li, C Fan, S Wu, Q Zhang… - arxiv preprint arxiv …, 2023 - arxiv.org
Large language models (LLMs) have garnered significant attention due to their impressive
natural language processing (NLP) capabilities. Recently, many studies have focused on …

Dynamic llm-agent network: An llm-agent collaboration framework with agent team optimization

Z Liu, Y Zhang, P Li, Y Liu, D Yang - arxiv preprint arxiv:2310.02170, 2023 - arxiv.org
Large language model (LLM) agents have been shown effective on a wide range of tasks,
and by ensembling multiple LLM agents, their performances could be further improved …