3 papers
cs.LG2026
Memory Savings at What Cost? A Study of Alternatives to Backpropagation
Kunjal Panchal, Sunav Choudhary, Yuriy Brun +1
Forward-mode automatic differentiation (FmAD) and zero-order (ZO) optimization are increasingly proposed as memory-efficient, backpropagation-free alternatives for large language m…
cs.HC2025
Your Model Is Unfair, Are You Even Aware? Inverse Relationship Between Comprehension and Trust in Explainability Visualizations of Biased ML Models
Zhanna Kaufman, Madeline Endres, Cindy Xiong Bearfield +1
Systems relying on ML have become ubiquitous, but so has biased behavior within them. Research shows that bias significantly affects stakeholders' trust in systems and how they use…
cs.HC2025
Bias, Accuracy, and Trust: Gender-Diverse Perspectives on Large Language Models
Aimen Gaba, Emily Wall, Tejas Ramkumar Babu +3
Large language models (LLMs) are becoming increasingly ubiquitous in our daily lives, but numerous concerns about bias in LLMs exist. This study examines how gender-diverse populat…