From google gemini to openai q*(q-star): A survey of reshaping the generative artificial intelligence (ai) research landscape

TR McIntosh, T Susnjak, T Liu, P Watters… - arXiv preprint arXiv …, 2023 - arxiv.org
This comprehensive survey explored the evolving landscape of generative Artificial
Intelligence (AI), with a specific focus on the transformative impacts of Mixture of Experts …

A survey on fairness in large language models

Y Li, M Du, R Song, X Wang, Y Wang - arXiv preprint arXiv:2308.10149, 2023 - arxiv.org
Large language models (LLMs) have shown powerful performance and development
prospect and are widely deployed in the real world. However, LLMs can capture social …

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 …

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 …

Ethics of large language models in medicine and medical research

H Li, JT Moon, S Purkayastha, LA Celi… - The Lancet Digital …, 2023 - thelancet.com
Large language models (LLMs) are a type of deep learning model that are trained on vast
amounts of text data with the goal of generating new text that closely resembles human …

On the opportunities and risks of foundation models

R Bommasani, DA Hudson, E Adeli, R Altman… - arXiv preprint arXiv …, 2021 - arxiv.org
AI is undergoing a paradigm shift with the rise of models (eg, BERT, DALL-E, GPT-3) that are
trained on broad data at scale and are adaptable to a wide range of downstream tasks. We …

Marked personas: Using natural language prompts to measure stereotypes in language models

M Cheng, E Durmus, D Jurafsky - arXiv preprint arXiv:2305.18189, 2023 - arxiv.org
To recognize and mitigate harms from large language models (LLMs), we need to
understand the prevalence and nuances of stereotypes in LLM outputs. Toward this end, we …

On the dangers of stochastic parrots: Can language models be too big?🦜

EM Bender, T Gebru, A McMillan-Major… - Proceedings of the 2021 …, 2021 - dl.acm.org
The past 3 years of work in NLP have been characterized by the development and
deployment of ever larger language models, especially for English. BERT, its variants, GPT …

Auto-debias: Debiasing masked language models with automated biased prompts

Y Guo, Y Yang, A Abbasi - … of the 60th Annual Meeting of the …, 2022 - aclanthology.org
Human-like biases and undesired social stereotypes exist in large pretrained language
models. Given the wide adoption of these models in real-world applications, mitigating such …

Chatgpt perpetuates gender bias in machine translation and ignores non-gendered pronouns: Findings across bengali and five other low-resource languages

S Ghosh, A Caliskan - Proceedings of the 2023 AAAI/ACM Conference …, 2023 - dl.acm.org
In this multicultural age, language translation is one of the most performed tasks, and it is
becoming increasingly AI-moderated and automated. As a novel AI system, ChatGPT claims …