4 papers · 1 filter
Sparse but not Simpler: A Multi-Level Interpretability Analysis of Vision Transformers
Siyu Zhang
Sparse neural networks are often hypothesized to be more interpretable than dense models, motivated by findings that weight sparsity can produce compact circuits in language models…
Zero-Forgetting CISS via Dual-Phase Cognitive Cascades
Yuquan Lu, Yifu Guo, Zishan Xu +6
Continual semantic segmentation (CSS) is a cornerstone task in computer vision that enables a large number of downstream applications, but faces the catastrophic forgetting challen…
Shape of Thought: Progressive Object Assembly via Visual Chain-of-Thought
Yu Huo, Siyu Zhang, Kun Zeng +7
Multimodal models for text-to-image generation have achieved strong visual fidelity, yet they remain brittle under compositional structural constraints, notably generative numeracy…
Decoupling Continual Semantic Segmentation
Yifu Guo, Yuquan Lu, Wentao Zhang +5
Continual Semantic Segmentation (CSS) requires learning new classes without forgetting previously acquired knowledge, addressing the fundamental challenge of catastrophic forgettin…