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 …

Challenges and applications of large language models

J Kaddour, J Harris, M Mozes, H Bradley… - arxiv preprint arxiv …, 2023 - arxiv.org
Large Language Models (LLMs) went from non-existent to ubiquitous in the machine
learning discourse within a few years. Due to the fast pace of the field, it is difficult to identify …

A survey of large language models

WX Zhao, K Zhou, J Li, T Tang, X Wang, Y Hou… - arxiv preprint arxiv …, 2023 - arxiv.org
Language is essentially a complex, intricate system of human expressions governed by
grammatical rules. It poses a significant challenge to develop capable AI algorithms for …

Siren's song in the AI ocean: a survey on hallucination in large language models

Y Zhang, Y Li, L Cui, D Cai, L Liu, T Fu… - arxiv preprint arxiv …, 2023 - arxiv.org
While large language models (LLMs) have demonstrated remarkable capabilities across a
range of downstream tasks, a significant concern revolves around their propensity to exhibit …

Encouraging divergent thinking in large language models through multi-agent debate

T Liang, Z He, W Jiao, X Wang, Y Wang… - arxiv preprint arxiv …, 2023 - arxiv.org
Modern large language models (LLMs) like ChatGPT have shown remarkable performance
on general language tasks but still struggle on complex reasoning tasks, which drives the …

Program of thoughts prompting: Disentangling computation from reasoning for numerical reasoning tasks

W Chen, X Ma, X Wang, WW Cohen - arxiv preprint arxiv:2211.12588, 2022 - arxiv.org
Recently, there has been significant progress in teaching language models to perform step-
by-step reasoning to solve complex numerical reasoning tasks. Chain-of-thoughts prompting …

Survey on factuality in large language models: Knowledge, retrieval and domain-specificity

C Wang, X Liu, Y Yue, X Tang, T Zhang… - arxiv preprint arxiv …, 2023 - arxiv.org
This survey addresses the crucial issue of factuality in Large Language Models (LLMs). As
LLMs find applications across diverse domains, the reliability and accuracy of their outputs …

Large language models cannot self-correct reasoning yet

J Huang, X Chen, S Mishra, HS Zheng, AW Yu… - arxiv preprint arxiv …, 2023 - arxiv.org
Large Language Models (LLMs) have emerged as a groundbreaking technology with their
unparalleled text generation capabilities across various applications. Nevertheless …

Large legal fictions: Profiling legal hallucinations in large language models

M Dahl, V Magesh, M Suzgun… - Journal of Legal Analysis, 2024 - academic.oup.com
Do large language models (LLMs) know the law? LLMs are increasingly being used to
augment legal practice, education, and research, yet their revolutionary potential is …

Tora: A tool-integrated reasoning agent for mathematical problem solving

Z Gou, Z Shao, Y Gong, Y Shen, Y Yang… - arxiv preprint arxiv …, 2023 - arxiv.org
Large language models have made significant progress in various language tasks, yet they
still struggle with complex mathematics. In this paper, we propose ToRA a series of Tool …