4 papers
How Many Images Does It Take? Estimating Imitation Thresholds in Text-to-Image Models
Sahil Verma, Royi Rassin, Arnav Das +6
Text-to-image models are trained using large datasets of image-text pairs collected from the internet. These datasets often include copyrighted and private images. Training models…
Small Changes, Large Consequences: Analyzing the Allocational Fairness of LLMs in Hiring Contexts
Preethi Seshadri, Hongyu Chen, Sameer Singh +1
Large language models (LLMs) are increasingly being deployed in high-stakes applications like hiring, yet their potential for unfair decision-making remains understudied in generat…
Agree to Disagree? A Meta-Evaluation of LLM Misgendering
Arjun Subramonian, Vagrant Gautam, Preethi Seshadri +3
Numerous methods have been proposed to measure LLM misgendering, including probability-based evaluations (e.g., automatically with templatic sentences) and generation-based evaluat…
Learning Robust Representations for Communications over Interference-limited Channels
Shubham Paul, Sudharsan Senthil, Preethi Seshadri +2
In the context of cellular networks, users located at the periphery of cells are particularly vulnerable to substantial interference from neighbouring cells, which can be represent…