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cs.CV2026
Lens: Rethinking Training Efficiency for Foundational Text-to-Image Models
Dong Chen, Fangyun Wei, Ziyu Wan +18
We introduce Lens, a 3.8B-parameter T2I model that achieves performance competitive with, and in several cases surpassing, state-of-the-art models with more than 6B parameters acro…
cs.CV2026
MMViR: A Multi-Modal and Multi-Granularity Representation for Long-range Video Understanding
Zizhong Li, Haopeng Zhang, Jiawei Zhang
Long videos, ranging from minutes to hours, present significant challenges for current Multi-modal Large Language Models (MLLMs) due to their complex events, diverse scenes, and lo…
cs.CV2023
Generic Attention-model Explainability by Weighted Relevance Accumulation
Yiming Huang, Aozhe Jia, Xiaodan Zhang +1
Attention-based transformer models have achieved remarkable progress in multi-modal tasks, such as visual question answering. The explainability of attention-based methods has rece…