A comprehensive survey on pretrained foundation models: A history from bert to chatgpt

C Zhou, Q Li, C Li, J Yu, Y Liu, G Wang… - International Journal of …, 2024‏ - Springer
Abstract Pretrained Foundation Models (PFMs) are regarded as the foundation for various
downstream tasks across different data modalities. A PFM (eg, BERT, ChatGPT, GPT-4) is …

[HTML][HTML] A survey of GPT-3 family large language models including ChatGPT and GPT-4

KS Kalyan - Natural Language Processing Journal, 2024‏ - Elsevier
Large language models (LLMs) are a special class of pretrained language models (PLMs)
obtained by scaling model size, pretraining corpus and computation. LLMs, because of their …

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 …

Parameter-efficient fine-tuning of large-scale pre-trained language models

N Ding, Y Qin, G Yang, F Wei, Z Yang, Y Su… - Nature Machine …, 2023‏ - nature.com
With the prevalence of pre-trained language models (PLMs) and the pre-training–fine-tuning
paradigm, it has been continuously shown that larger models tend to yield better …

Zhong**g: Enhancing the chinese medical capabilities of large language model through expert feedback and real-world multi-turn dialogue

S Yang, H Zhao, S Zhu, G Zhou, H Xu, Y Jia… - Proceedings of the AAAI …, 2024‏ - ojs.aaai.org
Abstract Recent advances in Large Language Models (LLMs) have achieved remarkable
breakthroughs in understanding and responding to user intents. However, their performance …

A comprehensive survey of continual learning: theory, method and application

L Wang, X Zhang, H Su, J Zhu - IEEE Transactions on Pattern …, 2024‏ - ieeexplore.ieee.org
To cope with real-world dynamics, an intelligent system needs to incrementally acquire,
update, accumulate, and exploit knowledge throughout its lifetime. This ability, known as …

Revisiting class-incremental learning with pre-trained models: Generalizability and adaptivity are all you need

DW Zhou, ZW Cai, HJ Ye, DC Zhan, Z Liu - arxiv preprint arxiv …, 2023‏ - arxiv.org
Class-incremental learning (CIL) aims to adapt to emerging new classes without forgetting
old ones. Traditional CIL models are trained from scratch to continually acquire knowledge …

Recommendation as instruction following: A large language model empowered recommendation approach

J Zhang, R **e, Y Hou, X Zhao, L Lin… - ACM Transactions on …, 2023‏ - dl.acm.org
In the past decades, recommender systems have attracted much attention in both research
and industry communities. Existing recommendation models mainly learn the underlying …

Enhancing chat language models by scaling high-quality instructional conversations

N Ding, Y Chen, B Xu, Y Qin, Z Zheng, S Hu… - arxiv preprint arxiv …, 2023‏ - arxiv.org
Fine-tuning on instruction data has been widely validated as an effective practice for
implementing chat language models like ChatGPT. Scaling the diversity and quality of such …

Auditing large language models: a three-layered approach

J Mökander, J Schuett, HR Kirk, L Floridi - AI and Ethics, 2024‏ - Springer
Large language models (LLMs) represent a major advance in artificial intelligence (AI)
research. However, the widespread use of LLMs is also coupled with significant ethical and …