4 citations · 9 across the 6 of their papers we have counts for
6 papers
From Tokens to Semantics: Leveraging Complementary Signals for Hallucination Detection in Black-Box LLMs
Urja Pawar, Rajitha Ramanayake, Owen O'Neill +5
When LLMs support public-facing or high-stakes workflows, missed fabrications can harm users and institutions, while false alarms consume limited human-review capacity. When no tru…
Beyond Accuracy: Measuring Bias Acknowledgment in Chain-of-Thought Reasoning for Responsible AI Evaluation
Xian Sun, Wei Gao, Yingshuo Wang +9
Reasoning models are increasingly used in settings where the final answer is not the only object of review: educational tools may show students intermediate steps, decision-support…
Generated Bias: Auditing Internal Bias Dynamics of Text-To-Image Generative Models
Abhishek Mandal, Susan Leavy, Suzanne Little
Text-To-Image (TTI) Diffusion Models such as DALL-E and Stable Diffusion are capable of generating images from text prompts. However, they have been shown to perpetuate gender ster…
Biased Attention: Do Vision Transformers Amplify Gender Bias More than Convolutional Neural Networks?
Abhishek Mandal, Susan Leavy, Suzanne Little
Deep neural networks used in computer vision have been shown to exhibit many social biases such as gender bias. Vision Transformers (ViTs) have become increasingly popular in compu…
Gender Bias in Multimodal Models: A Transnational Feminist Approach Considering Geographical Region and Culture
Abhishek Mandal, Suzanne Little, Susan Leavy
Deep learning based visual-linguistic multimodal models such as Contrastive Language Image Pre-training (CLIP) have become increasingly popular recently and are used within text-to…
Multimodal Composite Association Score: Measuring Gender Bias in Generative Multimodal Models
Abhishek Mandal, Susan Leavy, Suzanne Little
Generative multimodal models based on diffusion models have seen tremendous growth and advances in recent years. Models such as DALL-E and Stable Diffusion have become increasingly…