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20222026
most citedControllable Generation with Text-to-Image Diffusion Models: A Survey

18 citations · 26 across the 11 of their papers we have counts for

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5 papers · 1 filter

cs.CV2026

Flow-CLIP: Image-Conditioned Residual Scoring for CompositionalImage-Text Matching

Minghong Wei, Enguang Zhu, Pu Cao +2

Vision--language pre-training has enabled substantial progress in image--text retrieval and zero-shot recognition by learning transferable cross-modal representations. However, sen…

cs.CV2026

Query, Align, and Distill: Navigation-Aware Cross-Modal Interaction for Efficient Vision-and-Language Navigation

Zhihao Chen, Yiyuan Ge, Ziyang Wang +2

Recent large-scale Vision-and-Language Navigation (VLN) models deliver strong accuracy but remain costly to deploy due to their large parameter counts and computational requirement…

cs.CV2026

PointRL: Learning Point-Level Vision-Language Grounding from Verifiable Annotation Evidence

Jingyang Su, Pu Cao, Xiuze Jin +3

Vision-language models (VLMs) increasingly rely on point coordinates as a compact and executable interface for visual grounding in GUI interaction, robotic manipulation, and intera…

cs.CV2026

DrawAI: Agentic Benchmark and Workflow for Making Raster Images Editable

Pu Cao, Qingye Kong, Xuedan Yin +5

Recent image-generation models and multimodal agents can produce high-quality visuals for increasingly complex visual communication tasks. Yet their raster outputs remain difficult…

cs.CV2026

A Tilted Seesaw: Revisiting Autoencoder Trade-off for Controllable Diffusion

Pu Cao, Yiyang Ma, Feng Zhou +3

In latent diffusion models, the autoencoder (AE) is typically expected to balance two capabilities: faithful reconstruction and a generation-friendly latent space (e.g., low gFID).…