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cs.CV2026

Information Router for Mitigating Modality Dominance in Vision-Language Models

Seulgi Kim, Mohit Prabhushankar, Ghassan AlRegib

Vision Language models (VLMs) have demonstrated strong performance across a wide range of benchmarks, yet they often suffer from modality dominance, where predictions rely dispropo…

cs.CV2025

Countering Multi-modal Representation Collapse through Rank-targeted Fusion

Seulgi Kim, Kiran Kokilepersaud, Mohit Prabhushankar +1

Multi-modal fusion methods often suffer from two types of representation collapse: feature collapse where individual dimensions lose their discriminative power (as measured by eige…

cs.CV2025

Multi-level and Multi-modal Action Anticipation

Seulgi Kim, Ghazal Kaviani, Mohit Prabhushankar +1

Action anticipation, the task of predicting future actions from partially observed videos, is crucial for advancing intelligent systems. Unlike action recognition, which operates o…

cs.CV2025

Hierarchical and Multimodal Data for Daily Activity Understanding

Ghazal Kaviani, Yavuz Yarici, Seulgi Kim +4

Daily Activity Recordings for Artificial Intelligence (DARai, pronounced "Dahr-ree") is a multimodal, hierarchically annotated dataset constructed to understand human activities in…

cs.CV2024

HEX: Hierarchical Emergence Exploitation in Self-Supervised Algorithms

Kiran Kokilepersaud, Seulgi Kim, Mohit Prabhushankar +1

In this paper, we propose an algorithm that can be used on top of a wide variety of self-supervised (SSL) approaches to take advantage of hierarchical structures that emerge during…