activity
20242026
collaborators

10 papers

cs.CV2026

Through the Magnifying Glass: Adaptive Perception Magnification for Hallucination-Free VLM Decoding

Shunqi Mao, Chaoyi Zhang, Weidong Cai

Existing vision-language models (VLMs) often suffer from visual hallucination, where the generated responses contain inaccuracies that are not grounded in the visual input. Efforts…

cs.CV2025

TractGraphFormer: Anatomically Informed Hybrid Graph CNN-Transformer Network for Interpretable Sex and Age Prediction from Diffusion MRI Tractography

Yuqian Chen, Fan Zhang, Meng Wang +10

The relationship between brain connections and non-imaging phenotypes is increasingly studied using deep neural networks. However, the local and global properties of brain white ma…

cs.CV2025

RealSyn: An Effective and Scalable Multimodal Interleaved Document Transformation Paradigm

Tiancheng Gu, Kaicheng Yang, Chaoyi Zhang +6

After pre-training on extensive image-text pairs, Contrastive Language-Image Pre-training (CLIP) demonstrates promising performance on a wide variety of benchmarks. However, a subs…

cs.CV2025

Multimodal Causal Reasoning Benchmark: Challenging Vision Large Language Models to Discern Causal Links Across Modalities

Zhiyuan Li, Heng Wang, Dongnan Liu +4

Multimodal Large Language Models (MLLMs) have showcased exceptional Chain-of-Thought (CoT) reasoning ability in complex textual inference tasks including causal reasoning. However,…

cs.CV2024

Enhancing Robustness to Noise Corruption for Point Cloud Recognition via Spatial Sorting and Set-Mixing Aggregation Module

Dingxin Zhang, Jianhui Yu, Tengfei Xue +3

Current models for point cloud recognition demonstrate promising performance on synthetic datasets. However, real-world point cloud data inevitably contains noise, impacting model…

cs.CV2024

Learning to Synthesize Graphics Programs for Geometric Artworks

Qi Bing, Chaoyi Zhang, Weidong Cai

Creating and understanding art has long been a hallmark of human ability. When presented with finished digital artwork, professional graphic artists can intuitively deconstruct and…