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20242026
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cs.CV2026

Mamoda2.5: Enhancing Unified Multimodal Model with DiT-MoE

Yangming Shi, Shixiang Zhu, Tao Shen +14

We present Mamoda2.5, a unified AR-Diffusion framework that seamlessly integrates multimodal understanding and generation within a single architecture. To efficiently enhance the m…

cs.CV2026

Implicit Geometry Representations for Vision-and-Language Navigation from Web Videos

Mingfei Han, Haihong Hao, Liang Ma +6

Vision-and-Language Navigation (VLN) has long been constrained by the limited diversity and scalability of simulator-curated datasets, which fail to capture the complexity of real-…

cs.CV2026

World2Act: Latent Action Post-Training from World Model Dynamics

An Dinh Vuong, Tuan Van Vo, Abdullah Sohail +6

World Models (WMs) offer a promising mechanism for post-training Vision-Language-Action (VLA) policies by providing dynamics priors that improve generalization under task and scene…

cs.CV2024

EACO: Enhancing Alignment in Multimodal LLMs via Critical Observation

Yongxin Wang, Meng Cao, Haokun Lin +5

Multimodal large language models (MLLMs) have achieved remarkable progress on various visual question answering and reasoning tasks leveraging instruction fine-tuning specific data…

cs.CV2024

RoomTour3D: Geometry-Aware Video-Instruction Tuning for Embodied Navigation

Mingfei Han, Liang Ma, Kamila Zhumakhanova +5

Vision-and-Language Navigation (VLN) suffers from the limited diversity and scale of training data, primarily constrained by the manual curation of existing simulators. To address…