12 citations · 27 across the 14 of their papers we have counts for
9 papers · 1 filter
GEO-Detective: Unveiling Location Privacy Risks in Images with LLM Agents
Xinyu Zhang, Yixin Wu, Boyang Zhang +4
Images shared on social media often expose geographic cues. While early geolocation methods required expert effort and lacked generalization, the rise of Large Vision Language Mode…
OralGPT-Omni: A Versatile Dental Multimodal Large Language Model
Jing Hao, Yuci Liang, Lizhuo Lin +12
Multimodal Large Language Models (MLLMs) have exhibited immense potential across numerous medical specialties; yet, dentistry remains underexplored, in part due to limited domain-s…
Rectifying Soft-Label Entangled Bias in Long-Tailed Dataset Distillation
Chenyang Jiang, Hang Zhao, Xinyu Zhang +4
Dataset distillation compresses large-scale datasets into compact, highly informative synthetic data, significantly reducing storage and training costs. However, existing research…
Stroke Modeling Enables Vectorized Character Generation with Large Vectorized Glyph Model
Xinyue Zhang, Haolong Li, Jiawei Ma +1
Vectorized glyphs are widely used in poster design, network animation, art display, and various other fields due to their scalability and flexibility. In typography, they are often…
Glyph: Scaling Context Windows via Visual-Text Compression
Jiale Cheng, Yusen Liu, Xinyu Zhang +11
Large language models (LLMs) increasingly rely on long-context modeling for tasks such as document understanding, code analysis, and multi-step reasoning. However, scaling context…
GACO-CAD: Geometry-Augmented and Conciseness-Optimized CAD Model Generation from Single Image
Yinghui Wang, Xinyu Zhang, Peng Du
Generating editable, parametric CAD models from a single image holds great potential to lower the barriers of industrial concept design. However, current multi-modal large language…
Cutting the Skip: Training Residual-Free Transformers
Yiping Ji, James Martens, Jianqiao Zheng +5
Transformers have achieved remarkable success across a wide range of applications, a feat often attributed to their scalability. Yet training them without skip (residual) connectio…
SkipVAR: Accelerating Visual Autoregressive Modeling via Adaptive Frequency-Aware Skipping
Jiajun Li, Yue Ma, Xinyu Zhang +3
Recent studies on Visual Autoregressive (VAR) models have highlighted that high-frequency components, or later steps, in the generation process contribute disproportionately to inf…
Why Settle for One? Text-to-ImageSet Generation and Evaluation
Chengyou Jia, Xin Shen, Zhuohang Dang +6
Despite remarkable progress in Text-to-Image models, many real-world applications require generating coherent image sets with diverse consistency requirements. Existing consistent…