The future landscape of large language models in medicine

J Clusmann, FR Kolbinger, HS Muti, ZI Carrero… - Communications …, 2023 - nature.com
Large language models (LLMs) are artificial intelligence (AI) tools specifically trained to
process and generate text. LLMs attracted substantial public attention after OpenAI's …

Combating misinformation in the age of llms: Opportunities and challenges

C Chen, K Shu - AI Magazine, 2024 - Wiley Online Library
Misinformation such as fake news and rumors is a serious threat for information ecosystems
and public trust. The emergence of large language models (LLMs) has great potential to …

Llama 2: Open foundation and fine-tuned chat models

H Touvron, L Martin, K Stone, P Albert… - arxiv preprint arxiv …, 2023 - arxiv.org
In this work, we develop and release Llama 2, a collection of pretrained and fine-tuned large
language models (LLMs) ranging in scale from 7 billion to 70 billion parameters. Our fine …

From pretraining data to language models to downstream tasks: Tracking the trails of political biases leading to unfair NLP models

S Feng, CY Park, Y Liu, Y Tsvetkov - arxiv preprint arxiv:2305.08283, 2023 - arxiv.org
Language models (LMs) are pretrained on diverse data sources, including news, discussion
forums, books, and online encyclopedias. A significant portion of this data includes opinions …

[PDF][PDF] Ai transparency in the age of llms: A human-centered research roadmap

QV Liao, JW Vaughan - arxiv preprint arxiv:2306.01941, 2023 - assets.pubpub.org
The rise of powerful large language models (LLMs) brings about tremendous opportunities
for innovation but also looming risks for individuals and society at large. We have reached a …

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 foundation model transparency index

R Bommasani, K Klyman, S Longpre, S Kapoor… - arxiv preprint arxiv …, 2023 - arxiv.org
Foundation models have rapidly permeated society, catalyzing a wave of generative AI
applications spanning enterprise and consumer-facing contexts. While the societal impact of …

Ssd-lm: Semi-autoregressive simplex-based diffusion language model for text generation and modular control

X Han, S Kumar, Y Tsvetkov - arxiv preprint arxiv:2210.17432, 2022 - arxiv.org
Despite the growing success of diffusion models in continuous-valued domains (eg,
images), similar efforts for discrete domains such as text have yet to match the performance …

Leak, cheat, repeat: Data contamination and evaluation malpractices in closed-source llms

S Balloccu, P Schmidtová, M Lango… - arxiv preprint arxiv …, 2024 - arxiv.org
Natural Language Processing (NLP) research is increasingly focusing on the use of Large
Language Models (LLMs), with some of the most popular ones being either fully or partially …

A survey on detection of llms-generated content

X Yang, L Pan, X Zhao, H Chen, L Petzold… - arxiv preprint arxiv …, 2023 - arxiv.org
The burgeoning capabilities of advanced large language models (LLMs) such as ChatGPT
have led to an increase in synthetic content generation with implications across a variety of …