12 citations · 13 across the 5 of their papers we have counts for
6 papers
Newer Is Not Fairer: Gender Stereotyping in Text-to-Image AI Across Model Generations
Shesh Narayan Gupta, Nik Bear Brown
Text-to-image generative models are widely used in professional and creative settings, yet how they represent gender across occupations -- and whether newer models are fairer -- re…
A Dialogue-Based Framework for Correcting Multimodal Errors in AI-Assisted STEM Education
Akshay Syal, Lawrence Swaminathan Xavier Prince, Evin Gultepe +2
Large Language Models (LLMs) are democratizing access to personalized tutoring; however, their effectiveness is hindered by challenges in processing multimodal content, which limit…
When Generative Augmentation Hurts: A Benchmark Study of GAN and Diffusion Models for Bias Correction in AI Classification Systems
Shesh Narayan Gupta, Nik Bear Brown
Generative models are widely used to compensate for class imbalance in AI training pipelines, yet their failure modes under low-data conditions are poorly understood. This paper re…
Advances in Transformers for Robotic Applications: A Review
Nikunj Sanghai, Nik Bear Brown
The introduction of Transformers architecture has brought about significant breakthroughs in Deep Learning (DL), particularly within Natural Language Processing (NLP). Since their…
Enhancing Trust in LLMs: Algorithms for Comparing and Interpreting LLMs
Nik Bear Brown
This paper surveys evaluation techniques to enhance the trustworthiness and understanding of Large Language Models (LLMs). As reliance on LLMs grows, ensuring their reliability, fa…
The Cognitive Type Project -- Mapping Typography to Cognition
Nik Bear Brown
The Cognitive Type Project is focused on developing computational tools to enable the design of typefaces with varying cognitive properties. This initiative aims to empower typogra…