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cs.CV2025

VLNVerse: A Benchmark for Vision-Language Navigation with Versatile, Embodied, Realistic Simulation and Evaluation

Sihao Lin, Zerui Li, Xunyi Zhao +10

Despite remarkable progress in Vision-Language Navigation (VLN), existing benchmarks remain confined to fixed, small-scale datasets with naive physical simulation. These shortcomin…

cs.CV2025

WEAVE: Unleashing and Benchmarking the In-context Interleaved Comprehension and Generation

Wei Chow, Jiachun Pan, Yongyuan Liang +10

Recent advances in unified multimodal models (UMMs) have enabled impressive progress in visual comprehension and generation. However, existing datasets and benchmarks focus primari…

cs.CV2025

TAlignDiff: Automatic Tooth Alignment assisted by Diffusion-based Transformation Learning

Yunbi Liu, Enqi Tang, Shiyu Li +5

Orthodontic treatment hinges on tooth alignment, which significantly affects occlusal function, facial aesthetics, and patients' quality of life. Current deep learning approaches p…

cs.CV2025

On Path to Multimodal Generalist: General-Level and General-Bench

Hao Fei, Yuan Zhou, Juncheng Li +29

The Multimodal Large Language Model (MLLM) is currently experiencing rapid growth, driven by the advanced capabilities of LLMs. Unlike earlier specialists, existing MLLMs are evolv…

cs.CV2025

RepText: Rendering Visual Text via Replicating

Haofan Wang, Yujia Xu, Yimeng Li +5

Although contemporary text-to-image generation models have achieved remarkable breakthroughs in producing visually appealing images, their capacity to generate precise and flexible…

cs.CV2025

Generative Multimodal Pretraining with Discrete Diffusion Timestep Tokens

Kaihang Pan, Wang Lin, Zhongqi Yue +6

Recent endeavors in Multimodal Large Language Models (MLLMs) aim to unify visual comprehension and generation by combining LLM and diffusion models, the state-of-the-art in each ta…