A brief overview of ChatGPT: The history, status quo and potential future development

T Wu, S He, J Liu, S Sun, K Liu… - IEEE/CAA Journal of …, 2023 - ieeexplore.ieee.org
ChatGPT, an artificial intelligence generated content (AIGC) model developed by OpenAI,
has attracted world-wide attention for its capability of dealing with challenging language …

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 …

Dinov2: Learning robust visual features without supervision

M Oquab, T Darcet, T Moutakanni, H Vo… - arxiv preprint arxiv …, 2023 - arxiv.org
The recent breakthroughs in natural language processing for model pretraining on large
quantities of data have opened the way for similar foundation models in computer vision …

Run, don't walk: chasing higher FLOPS for faster neural networks

J Chen, S Kao, H He, W Zhuo, S Wen… - Proceedings of the …, 2023 - openaccess.thecvf.com
To design fast neural networks, many works have been focusing on reducing the number of
floating-point operations (FLOPs). We observe that such reduction in FLOPs, however, does …

Camel: Communicative agents for" mind" exploration of large language model society

G Li, H Hammoud, H Itani… - Advances in Neural …, 2023 - proceedings.neurips.cc
The rapid advancement of chat-based language models has led to remarkable progress in
complex task-solving. However, their success heavily relies on human input to guide the …

[HTML][HTML] Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustworthy Artificial Intelligence

S Ali, T Abuhmed, S El-Sappagh, K Muhammad… - Information fusion, 2023 - Elsevier
Artificial intelligence (AI) is currently being utilized in a wide range of sophisticated
applications, but the outcomes of many AI models are challenging to comprehend and trust …

Scaling vision transformers to 22 billion parameters

M Dehghani, J Djolonga, B Mustafa… - International …, 2023 - proceedings.mlr.press
The scaling of Transformers has driven breakthrough capabilities for language models. At
present, the largest large language models (LLMs) contain upwards of 100B parameters …

H2o: Heavy-hitter oracle for efficient generative inference of large language models

Z Zhang, Y Sheng, T Zhou, T Chen… - Advances in …, 2023 - proceedings.neurips.cc
Abstract Large Language Models (LLMs), despite their recent impressive accomplishments,
are notably cost-prohibitive to deploy, particularly for applications involving long-content …

Self-instruct: Aligning language models with self-generated instructions

Y Wang, Y Kordi, S Mishra, A Liu, NA Smith… - arxiv preprint arxiv …, 2022 - arxiv.org
Large" instruction-tuned" language models (ie, finetuned to respond to instructions) have
demonstrated a remarkable ability to generalize zero-shot to new tasks. Nevertheless, they …

A survey on model compression for large language models

X Zhu, J Li, Y Liu, C Ma, W Wang - Transactions of the Association for …, 2024 - direct.mit.edu
Abstract Large Language Models (LLMs) have transformed natural language processing
tasks successfully. Yet, their large size and high computational needs pose challenges for …