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 …

Graph of thoughts: Solving elaborate problems with large language models

M Besta, N Blach, A Kubicek, R Gerstenberger… - Proceedings of the …, 2024 - ojs.aaai.org
Abstract We introduce Graph of Thoughts (GoT): a framework that advances prompting
capabilities in large language models (LLMs) beyond those offered by paradigms such as …

Rolellm: Benchmarking, eliciting, and enhancing role-playing abilities of large language models

ZM Wang, Z Peng, H Que, J Liu, W Zhou, Y Wu… - arxiv preprint arxiv …, 2023 - arxiv.org
The advent of Large Language Models (LLMs) has paved the way for complex tasks such as
role-playing, which enhances user interactions by enabling models to imitate various …

Llms for knowledge graph construction and reasoning: Recent capabilities and future opportunities

Y Zhu, X Wang, J Chen, S Qiao, Y Ou, Y Yao, S Deng… - World Wide Web, 2024 - Springer
This paper presents an exhaustive quantitative and qualitative evaluation of Large
Language Models (LLMs) for Knowledge Graph (KG) construction and reasoning. We …

Tptu: Task planning and tool usage of large language model-based ai agents

J Ruan, Y Chen, B Zhang, Z Xu, T Bao… - … Models for Decision …, 2023 - openreview.net
With recent advancements in natural language processing, Large Language Models (LLMs)
have emerged as powerful tools for various real-world applications. Despite their prowess …

A bi-step grounding paradigm for large language models in recommendation systems

K Bao, J Zhang, W Wang, Y Zhang, Z Yang… - ACM Transactions on …, 2023 - dl.acm.org
As the focus on Large Language Models (LLMs) in the field of recommendation intensifies,
the optimization of LLMs for recommendation purposes (referred to as LLM4Rec) assumes a …

[HTML][HTML] Making knowledge graphs work for smart manufacturing: Research topics, applications and prospects

Y Wan, Y Liu, Z Chen, C Chen, X Li, F Hu… - Journal of Manufacturing …, 2024 - Elsevier
Smart manufacturing (SM) confronts several challenges inherently suited to knowledge
graphs (KGs) capabilities. The first key challenge lies in the synthesis of complex and varied …

Artificial intelligence for science in quantum, atomistic, and continuum systems

X Zhang, L Wang, J Helwig, Y Luo, C Fu, Y **e… - arxiv preprint arxiv …, 2023 - arxiv.org
Advances in artificial intelligence (AI) are fueling a new paradigm of discoveries in natural
sciences. Today, AI has started to advance natural sciences by improving, accelerating, and …

Swiftsage: A generative agent with fast and slow thinking for complex interactive tasks

BY Lin, Y Fu, K Yang, F Brahman… - Advances in …, 2024 - proceedings.neurips.cc
We introduce SwiftSage, a novel agent framework inspired by the dual-process theory of
human cognition, designed to excel in action planning for complex interactive reasoning …

Lampilot: An open benchmark dataset for autonomous driving with language model programs

Y Ma, C Cui, X Cao, W Ye, P Liu, J Lu… - Proceedings of the …, 2024 - openaccess.thecvf.com
Autonomous driving (AD) has made significant strides in recent years. However existing
frameworks struggle to interpret and execute spontaneous user instructions such as" …