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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.CV2026

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.CV2026

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.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…