Building on this foundation, we introduce \ours, a novel approach that identifies and aligns the most relevant visual and textual representations in a modular manner.

In this work, we propose Mod-Squad, a modular multi-task learner based on mixture-of-experts and a novel loss to address the gradient conflicts among tasks. We demonstrate its potential to scale up in …

We propose a simple but effective modular approach MOPA (Modular ObjectNav with PointGoal agents) to sys-tematically investigate the inherent modularity of the object navigation task in Embodied AI.

End-to-End Yet Modular Architecture distinguishes it-self from traditional and end-to-end planning approaches by integrating modular design with end-to-end training. As a result, it maintains safety …

This necessitates the creation of modular and scalable ways to teach VLMs about physical reasoning. To that end, we introduce Physics Context Builders (PCBs), a modular framework where specialized …

The modular architecture of MoReVQA allows it to be dynamically tailored to a wide range of datasets, question types, and tasks by selectively engaging different APIs and reasoning strategies based on …

Building on this foundation, we introduce SmartCLIP, a novel approach that identifies and aligns the most relevant visual and textual representations in a modular manner.

Modular Blind Video Quality Assessment Wen Wen, Mu Li, Yabin Zhang, Yiting Liao, Junlin Li, Li Zhang, Kede Ma; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition …

We design modular adapter consisting of a functional adapter and a representation descriptor. The representation descriptors are trained as a distribution shift indicator and used to trigger self …

In this paper, we ad-dress a new problem called Modular Customization, with the goal of efficiently merging customized models that were fine-tuned independently for individual concepts.