Gender bias perpetuation and mitigation in AI technologies: challenges and opportunities

S O'Connor, H Liu - AI & SOCIETY, 2024 - Springer
Across the world, artificial intelligence (AI) technologies are being more widely employed in
public sector decision-making and processes as a supposedly neutral and an efficient …

[HTML][HTML] Gender bias in transformers: A comprehensive review of detection and mitigation strategies

P Nemani, YD Joel, P Vijay, FF Liza - Natural Language Processing …, 2024 - Elsevier
Gender bias in artificial intelligence (AI) has emerged as a pressing concern with profound
implications for individuals' lives. This paper presents a comprehensive survey that explores …

The llama 3 herd of models

A Dubey, A Jauhri, A Pandey, A Kadian… - arxiv preprint arxiv …, 2024 - arxiv.org
Modern artificial intelligence (AI) systems are powered by foundation models. This paper
presents a new set of foundation models, called Llama 3. It is a herd of language models …

Fairness in large language models: A taxonomic survey

Z Chu, Z Wang, W Zhang - ACM SIGKDD explorations newsletter, 2024 - dl.acm.org
Large Language Models (LLMs) have demonstrated remarkable success across various
domains. However, despite their promising performance in numerous real-world …

A survey on gender bias in natural language processing

K Stanczak, I Augenstein - arxiv preprint arxiv:2112.14168, 2021 - arxiv.org
Language can be used as a means of reproducing and enforcing harmful stereotypes and
biases and has been analysed as such in numerous research. In this paper, we present a …

Seamless: Multilingual Expressive and Streaming Speech Translation

L Barrault, YA Chung, MC Meglioli, D Dale… - arxiv preprint arxiv …, 2023 - arxiv.org
Large-scale automatic speech translation systems today lack key features that help machine-
mediated communication feel seamless when compared to human-to-human dialogue. In …

Quantifying social biases in NLP: A generalization and empirical comparison of extrinsic fairness metrics

P Czarnowska, Y Vyas, K Shah - Transactions of the Association for …, 2021 - direct.mit.edu
Measuring bias is key for better understanding and addressing unfairness in NLP/ML
models. This is often done via fairness metrics, which quantify the differences in a model's …

Accelerating transformer inference for translation via parallel decoding

A Santilli, S Severino, E Postolache, V Maiorca… - arxiv preprint arxiv …, 2023 - arxiv.org
Autoregressive decoding limits the efficiency of transformers for Machine Translation (MT).
The community proposed specific network architectures and learning-based methods to …

Theories of “gender” in nlp bias research

H Devinney, J Björklund, H Björklund - … of the 2022 ACM conference on …, 2022 - dl.acm.org
The rise of concern around Natural Language Processing (NLP) technologies containing
and perpetuating social biases has led to a rich and rapidly growing area of research …

Language variation and algorithmic bias: understanding algorithmic bias in British English automatic speech recognition

N Markl - Proceedings of the 2022 ACM Conference on Fairness …, 2022 - dl.acm.org
All language is characterised by variation which language users employ to construct
complex social identities and express social meaning. Like other machine learning …