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 …

Retrieval-augmented generation for natural language processing: A survey

S Wu, Y **ong, Y Cui, H Wu, C Chen, Y Yuan… - arxiv preprint arxiv …, 2024‏ - arxiv.org
Large language models (LLMs) have demonstrated great success in various fields,
benefiting from their huge amount of parameters that store knowledge. However, LLMs still …

Agent hospital: A simulacrum of hospital with evolvable medical agents

J Li, Y Lai, W Li, J Ren, M Zhang, X Kang… - arxiv preprint arxiv …, 2024‏ - arxiv.org
The recent rapid development of large language models (LLMs) has sparked a new wave of
technological revolution in medical artificial intelligence (AI). While LLMs are designed to …

A survey on the memory mechanism of large language model based agents

Z Zhang, X Bo, C Ma, R Li, X Chen, Q Dai, J Zhu… - arxiv preprint arxiv …, 2024‏ - arxiv.org
Large language model (LLM) based agents have recently attracted much attention from the
research and industry communities. Compared with original LLMs, LLM-based agents are …

Dataset regeneration for sequential recommendation

M Yin, H Wang, W Guo, Y Liu, S Zhang… - Proceedings of the 30th …, 2024‏ - dl.acm.org
The sequential recommender (SR) system is a crucial component of modern recommender
systems, as it aims to capture the evolving preferences of users. Significant efforts have …

The landscape of emerging ai agent architectures for reasoning, planning, and tool calling: A survey

T Masterman, S Besen, M Sawtell, A Chao - arxiv preprint arxiv …, 2024‏ - arxiv.org
This survey paper examines the recent advancements in AI agent implementations, with a
focus on their ability to achieve complex goals that require enhanced reasoning, planning …

Hallucination detection in foundation models for decision-making: A flexible definition and review of the state of the art

N Chakraborty, M Ornik, K Driggs-Campbell - ACM Computing Surveys, 2025‏ - dl.acm.org
Autonomous systems are soon to be ubiquitous, spanning manufacturing, agriculture,
healthcare, entertainment, and other industries. Most of these systems are developed with …

From text to insight: large language models for materials science data extraction

M Schilling-Wilhelmi, M Ríos-García, S Shabih… - arxiv preprint arxiv …, 2024‏ - arxiv.org
The vast majority of materials science knowledge exists in unstructured natural language,
yet structured data is crucial for innovative and systematic materials design. Traditionally, the …

Large language models as urban residents: An llm agent framework for personal mobility generation

J Wang, R Jiang, C Yang, Z Wu, M Onizuka… - arxiv preprint arxiv …, 2024‏ - arxiv.org
This paper introduces a novel approach using Large Language Models (LLMs) integrated
into an agent framework for flexible and effective personal mobility generation. LLMs …

Exploring user retrieval integration towards large language models for cross-domain sequential recommendation

T Shen, H Wang, J Zhang, S Zhao, L Li, Z Chen… - arxiv preprint arxiv …, 2024‏ - arxiv.org
Cross-Domain Sequential Recommendation (CDSR) aims to mine and transfer users'
sequential preferences across different domains to alleviate the long-standing cold-start …