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cs.CV2026
WorldBagel: Uncovering the Power of Unified Multimodal Models for Vision-Language-Action-World Modeling
Zelin Zhao, Min Shi, Bo Yuan +5
World models aim to capture environment dynamics in ways that support perception, reasoning, and action, and have recently become a central direction in Vision-Language-Action-Worl…
cs.CV2026
DuoGen: Towards General Purpose Interleaved Multimodal Generation
Min Shi, Xiaohui Zeng, Jiannan Huang +13
Interleaved multimodal generation enables capabilities beyond unimodal generation models, such as step-by-step instructional guides, visual planning, and generating visual drafts f…
cs.CV2026
SpikeVAEDiff: Neural Spike-based Natural Visual Scene Reconstruction via VD-VAE and Versatile Diffusion
Jialu Li, Taiyan Zhou
Reconstructing natural visual scenes from neural activity is a key challenge in neuroscience and computer vision. We present SpikeVAEDiff, a novel two-stage framework that combines…