28 stories tagged Bias · page 2 of 2
Researchers say current methods for testing AI bias might be flawed because they don't account for all possible changes in the text. They propose a better way to measure how AI models really work. This could help make AI fairer and more reliable.
A new study analyzes intermediate reasoning steps of LLMs to reveal stigmatizing language and biases toward mental health conditions. The findings highlight limitations of traditional evaluation methods.
A new study identifies specific neurons and attention heads in LLMs that encode harmful stereotypes. The research provides tools to locate and potentially mitigate biases in AI models. Researchers used a combination of contrastive neuron activation analysis and attention head tracking to pinpoint bias sources in GPT-2 Small and Llama 3.2.
A new study analyzes how bias mitigation impacts the embedding spaces of BERT and Llama2, showing reduced gender-occupation disparities. The findings highlight measurable improvements in model fairness through representational analysis.