18 citations · 31 across the 8 of their papers we have counts for
8 papers
The Multimodal Paradox: How Added and Missing Modalities Shape Bias and Performance in Multimodal AI
Kishore Sampath, Pratheesh, Ayaazuddin Mohammad +1
Multimodal learning, which integrates diverse data sources such as images, text, and structured data, has proven superior to unimodal counterparts in high-stakes decision-making. H…
Unequal Opportunities: Examining the Bias in Geographical Recommendations by Large Language Models
Shiran Dudy, Thulasi Tholeti, Resmi Ramachandranpillai +3
Recent advancements in Large Language Models (LLMs) have made them a popular information-seeking tool among end users. However, the statistical training methods for LLMs have raise…
Fairness at Every Intersection: Uncovering and Mitigating Intersectional Biases in Multimodal Clinical Predictions
Resmi Ramachandranpillai, Kishore Sampath, Ayaazuddin Mohammad +1
Biases in automated clinical decision-making using Electronic Healthcare Records (EHR) impose significant disparities in patient care and treatment outcomes. Conventional approache…
Generating Synthetic Fair Syntax-agnostic Data by Learning and Distilling Fair Representation
Md Fahim Sikder, Resmi Ramachandranpillai, Daniel de Leng +1
Data Fairness is a crucial topic due to the recent wide usage of AI powered applications. Most of the real-world data is filled with human or machine biases and when those data are…
Are Generative Language Models Multicultural? A Study on Hausa Culture and Emotions using ChatGPT
Ibrahim Said Ahmad, Shiran Dudy, Resmi Ramachandranpillai +1
Large Language Models (LLMs), such as ChatGPT, are widely used to generate content for various purposes and audiences. However, these models may not reflect the cultural and emotio…
FairX: A comprehensive benchmarking tool for model analysis using fairness, utility, and explainability
Md Fahim Sikder, Resmi Ramachandranpillai, Daniel de Leng +1
We present FairX, an open-source Python-based benchmarking tool designed for the comprehensive analysis of models under the umbrella of fairness, utility, and eXplainability (XAI).…
Bt-GAN: Generating Fair Synthetic Healthdata via Bias-transforming Generative Adversarial Networks
Resmi Ramachandranpillai, Md Fahim Sikder, David Bergström +1
Synthetic data generation offers a promising solution to enhance the usefulness of Electronic Healthcare Records (EHR) by generating realistic de-identified data. However, the exis…
TransFusion: Generating Long, High Fidelity Time Series using Diffusion Models with Transformers
Md Fahim Sikder, Resmi Ramachandranpillai, Fredrik Heintz
The generation of high-quality, long-sequenced time-series data is essential due to its wide range of applications. In the past, standalone Recurrent and Convolutional Neural Netwo…