collaborators

5 papers

cs.CV2025

Scope: Selective Cross-modal Orchestration of Visual Perception Experts

Tianyu Zhang, Suyuchen Wang, Chao Wang +5

Vision-language models (VLMs) benefit from multiple vision encoders, but naively stacking them yields diminishing returns while multiplying inference costs. We propose SCOPE, a Mix…

cs.CV2025

Improving GUI Grounding with Explicit Position-to-Coordinate Mapping

Suyuchen Wang, Tianyu Zhang, Ahmed Masry +4

GUI grounding, the task of mapping natural-language instructions to pixel coordinates, is crucial for autonomous agents, yet remains difficult for current VLMs. The core bottleneck…

cs.LG2025

STRICT: Stress Test of Rendering Images Containing Text

Tianyu Zhang, Xinyu Wang, Lu Li +5

While diffusion models have revolutionized text-to-image generation with their ability to synthesize realistic and diverse scenes, they continue to struggle to generate consistent…

cs.CL2025

AlignVLM: Bridging Vision and Language Latent Spaces for Multimodal Document Understanding

Ahmed Masry, Juan A. Rodriguez, Tianyu Zhang +19

Aligning visual features with language embeddings is a key challenge in vision-language models (VLMs). The performance of such models hinges on having a good connector that maps vi…

cs.LG2024

BigDocs: An Open Dataset for Training Multimodal Models on Document and Code Tasks

Juan Rodriguez, Xiangru Jian, Siba Smarak Panigrahi +40

Multimodal AI has the potential to significantly enhance document-understanding tasks, such as processing receipts, understanding workflows, extracting data from documents, and sum…