A comprehensive survey of ai-generated content (aigc): A history of generative ai from gan to chatgpt

Y Cao, S Li, Y Liu, Z Yan, Y Dai, PS Yu… - arXiv preprint arXiv …, 2023 - arxiv.org
Recently, ChatGPT, along with DALL-E-2 and Codex, has been gaining significant attention
from society. As a result, many individuals have become interested in related resources and …

Challenges and applications of large language models

J Kaddour, J Harris, M Mozes, H Bradley… - arXiv preprint arXiv …, 2023 - arxiv.org
Large Language Models (LLMs) went from non-existent to ubiquitous in the machine
learning discourse within a few years. Due to the fast pace of the field, it is difficult to identify …

The flan collection: Designing data and methods for effective instruction tuning

S Longpre, L Hou, T Vu, A Webson… - International …, 2023 - proceedings.mlr.press
We study the design decision of publicly available instruction tuning methods, by
reproducing and breaking down the development of Flan 2022 (Chung et al., 2022) …

The rise and potential of large language model based agents: A survey

Z Xi, W Chen, X Guo, W He, Y Ding, B Hong… - arXiv preprint arXiv …, 2023 - arxiv.org
For a long time, humanity has pursued artificial intelligence (AI) equivalent to or surpassing
the human level, with AI agents considered a promising vehicle for this pursuit. AI agents are …

A categorical archive of chatgpt failures

A Borji - arXiv preprint arXiv:2302.03494, 2023 - arxiv.org
Large language models have been demonstrated to be valuable in different fields. ChatGPT,
developed by OpenAI, has been trained using massive amounts of data and simulates …

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 …

Red teaming language models to reduce harms: Methods, scaling behaviors, and lessons learned

D Ganguli, L Lovitt, J Kernion, A Askell, Y Bai… - arXiv preprint arXiv …, 2022 - arxiv.org
We describe our early efforts to red team language models in order to simultaneously
discover, measure, and attempt to reduce their potentially harmful outputs. We make three …

Training language models to follow instructions with human feedback

L Ouyang, J Wu, X Jiang, D Almeida… - Advances in neural …, 2022 - proceedings.neurips.cc
Making language models bigger does not inherently make them better at following a user's
intent. For example, large language models can generate outputs that are untruthful, toxic, or …

Lamda: Language models for dialog applications

R Thoppilan, D De Freitas, J Hall, N Shazeer… - arXiv preprint arXiv …, 2022 - arxiv.org
We present LaMDA: Language Models for Dialog Applications. LaMDA is a family of
Transformer-based neural language models specialized for dialog, which have up to 137B …

Evaluating large language models in generating synthetic hci research data: a case study

P Hämäläinen, M Tavast, A Kunnari - … of the 2023 CHI Conference on …, 2023 - dl.acm.org
Collecting data is one of the bottlenecks of Human-Computer Interaction (HCI) research.
Motivated by this, we explore the potential of large language models (LLMs) in generating …