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 …

When large language models meet personalization: Perspectives of challenges and opportunities

J Chen, Z Liu, X Huang, C Wu, Q Liu, G Jiang, Y Pu… - World Wide Web, 2024 - Springer
The advent of large language models marks a revolutionary breakthrough in artificial
intelligence. With the unprecedented scale of training and model parameters, the capability …

Gemini: a family of highly capable multimodal models

G Team, R Anil, S Borgeaud, JB Alayrac, J Yu… - arxiv preprint arxiv …, 2023 - arxiv.org
This report introduces a new family of multimodal models, Gemini, that exhibit remarkable
capabilities across image, audio, video, and text understanding. The Gemini family consists …

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 …

Palm 2 technical report

R Anil, AM Dai, O Firat, M Johnson, D Lepikhin… - arxiv preprint arxiv …, 2023 - arxiv.org
We introduce PaLM 2, a new state-of-the-art language model that has better multilingual and
reasoning capabilities and is more compute-efficient than its predecessor PaLM. PaLM 2 is …

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 …

Large language models struggle to learn long-tail knowledge

N Kandpal, H Deng, A Roberts… - International …, 2023 - proceedings.mlr.press
The Internet contains a wealth of knowledge—from the birthdays of historical figures to
tutorials on how to code—all of which may be learned by language models. However, while …

Inner monologue: Embodied reasoning through planning with language models

W Huang, F **a, T **ao, H Chan, J Liang… - arxiv preprint arxiv …, 2022 - arxiv.org
Recent works have shown how the reasoning capabilities of Large Language Models
(LLMs) can be applied to domains beyond natural language processing, such as planning …

Glm-130b: An open bilingual pre-trained model

A Zeng, X Liu, Z Du, Z Wang, H Lai, M Ding… - arxiv preprint arxiv …, 2022 - arxiv.org
We introduce GLM-130B, a bilingual (English and Chinese) pre-trained language model
with 130 billion parameters. It is an attempt to open-source a 100B-scale model at least as …

Gpt-ner: Named entity recognition via large language models

S Wang, X Sun, X Li, R Ouyang, F Wu, T Zhang… - arxiv preprint arxiv …, 2023 - arxiv.org
Despite the fact that large-scale Language Models (LLM) have achieved SOTA
performances on a variety of NLP tasks, its performance on NER is still significantly below …