347 citations · 1k across the 30 of their papers we have counts for
6 papers · 1 filter
Into the LAIONs Den: Investigating Hate in Multimodal Datasets
Abeba Birhane, Vinay Prabhu, Sang Han +2
'Scale the model, scale the data, scale the compute' is the reigning sentiment in the world of generative AI today. While the impact of model scaling has been extensively studied,…
Position: Key Claims in LLM Research Have a Long Tail of Footnotes
Anna Rogers, Alexandra Sasha Luccioni
Much of the recent discourse within the ML community has been centered around Large Language Models (LLMs), their functionality and potential -- yet not only do we not have a worki…
Evaluating the Social Impact of Generative AI Systems in Systems and Society
Irene Solaiman, Zeerak Talat, William Agnew +28
Generative AI systems across modalities, ranging from text (including code), image, audio, and video, have broad social impacts, but there is no official standard for means of eval…
Stable Bias: Analyzing Societal Representations in Diffusion Models
Alexandra Sasha Luccioni, Christopher Akiki, Margaret Mitchell +1
As machine learning-enabled Text-to-Image (TTI) systems are becoming increasingly prevalent and seeing growing adoption as commercial services, characterizing the social biases the…
The ROOTS Search Tool: Data Transparency for LLMs
Aleksandra Piktus, Christopher Akiki, Paulo Villegas +5
ROOTS is a 1.6TB multilingual text corpus developed for the training of BLOOM, currently the largest language model explicitly accompanied by commensurate data governance efforts.…
Counting Carbon: A Survey of Factors Influencing the Emissions of Machine Learning
Alexandra Sasha Luccioni, Alex Hernandez-Garcia
Machine learning (ML) requires using energy to carry out computations during the model training process. The generation of this energy comes with an environmental cost in terms of…