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20242026
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cs.CV2026

Dual-Stream Cross-Anchor Correction Grounding Long-Form Captions and the Domain Limits of Object-Level Anchors

Lingkai Bu, Qian Gao, Jun Fan +4

Object hallucination in multimodal large language models arises when language priors and corpus co-occurrence bias outweigh the visual evidence, with nothing tying an object mentio…

cs.CV2026

Diagnosing Dense Same-Class Attribute Misbinding in Large Vision-Language Models

Yuanzhi Xu, Qian Gao, Jun Fan +4

Large vision-language models can recognize the objects and attributes in a crowded scene yet assign an attribute to the wrong same-class instance. Generic visual-question-answering…

cs.CV2025

Improved Visual-Spatial Reasoning via R1-Zero-Like Training

Zhenyi Liao, Qingsong Xie, Yanhao Zhang +4

Increasing attention has been placed on improving the reasoning capacities of multi-modal large language models (MLLMs). As the cornerstone for AI agents that function in the physi…

cs.CV2025

Layton: Latent Consistency Tokenizer for 1024-pixel Image Reconstruction and Generation by 256 Tokens

Qingsong Xie, Zhao Zhang, Zhe Huang +3

Image tokenization has significantly advanced visual generation and multimodal modeling, particularly when paired with autoregressive models. However, current methods face challeng…

cs.CV2025

H2VU-Benchmark: A Comprehensive Benchmark for Hierarchical Holistic Video Understanding

Qi Wu, Quanlong Zheng, Yanhao Zhang +8

With the rapid development of multimodal models, the demand for assessing video understanding capabilities has been steadily increasing. However, existing benchmarks for evaluating…

cs.CV2025

X2I: Seamless Integration of Multimodal Understanding into Diffusion Transformer via Attention Distillation

Jian Ma, Qirong Peng, Xu Guo +3

Text-to-image (T2I) models are well known for their ability to produce highly realistic images, while multimodal large language models (MLLMs) are renowned for their proficiency in…