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cs.LG2026
Understanding Submodular Information Measure Based Objectives for Representation Learning: A Variance and Separation Perspective
Rishabh Iyer, Truong Pham, Anay Majee
Submodular Information Measures (SIMs) have recently emerged as a powerful framework for representation learning and multimodal learning. In particular, the SCORE framework~\cite{m…
cs.LG2026
SMA: Submodular Modality Aligner For Data Efficient Multimodal Learning
Truong Pham, Anay Majee, Rishabh Iyer
Despite the recent success of Multimodal Foundation Models (FMs), their reliance on massive paired datasets limits their applicability in low-data and rare-scenario settings where…
cs.CV2026
SHaSaM: Submodular Hard Sample Mining for Fair Facial Attribute Recognition
Anay Majee, Rishabh Iyer
Deep neural networks often inherit social and demographic biases from annotated data during model training, leading to unfair predictions, especially in the presence of sensitive a…