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cs.CV2026

Same Semantics, Different Paths: Self-Improving Alignment for Vision-Text Compression

Tianyu Liang, Xiangxi Zheng, Yilin Wang +1

Vision-Text Compression (VTC) renders long texts into images and encodes them through the vision encoder (ViT), compressing thousands of text tokens into far fewer visual tokens. H…

cs.CV2026

Efficient Frame Selection for Long Videos at Test Time with Attention-Based MLLM Selectors

Yilin Wang, Xiangxi Zheng, Dongxing Mao +6

Understanding long videos with multimodal large language models (MLLMs) requires selecting a compact set of frames from thousands of candidates, yet identifying the right frames se…

cs.CV2026

DataEvolver: Self-Evolving Multi-Agent Data Construction for Text-Rich Image Generation

Siyu Yan, Yizhen Gao, Yilin Wang +2

Text-rich image generation is one of the most challenging settings in image generation, since models must simultaneously produce visually realistic images and render legible, seman…

cs.CV2026

TextGround4M: A Prompt-Aligned Dataset for Layout-Aware Text Rendering

Dongxing Mao, Yilin Wang, Linjie Li +2

Despite recent advances in text-to-image generation, models still struggle to accurately render prompt-specified text with correct spatial layout -- especially in multi-span, struc…

cs.CV2024

TokenCompose: Text-to-Image Diffusion with Token-level Supervision

Zirui Wang, Zhizhou Sha, Zheng Ding +2

We present TokenCompose, a Latent Diffusion Model for text-to-image generation that achieves enhanced consistency between user-specified text prompts and model-generated images. De…

cs.CV2024

OmniControlNet: Dual-stage Integration for Conditional Image Generation

Yilin Wang, Haiyang Xu, Xiang Zhang +4

We provide a two-way integration for the widely adopted ControlNet by integrating external condition generation algorithms into a single dense prediction method and incorporating i…