22 citations · 73 across the 29 of their papers we have counts for
5 papers · 1 filter
The Silent Assistant: NoiseQuery as Implicit Guidance for Goal-Driven Image Generation
Ruoyu Wang, Huayang Huang, Ye Zhu +2
In this work, we introduce NoiseQuery as a novel method for enhanced noise initialization in versatile goal-driven text-to-image (T2I) generation. Specifically, we propose to lever…
SOWing Information: Cultivating Contextual Coherence with MLLMs in Image Generation
Yuhan Pei, Ruoyu Wang, Yongqi Yang +3
Originating from the diffusion phenomenon in physics, which describes the random movement and collisions of particles, diffusion generative models simulate a random walk in the dat…
ConceptMix: A Compositional Image Generation Benchmark with Controllable Difficulty
Xindi Wu, Dingli Yu, Yangsibo Huang +2
Compositionality is a critical capability in Text-to-Image (T2I) models, as it reflects their ability to understand and combine multiple concepts from text descriptions. Existing e…
What is Dataset Distillation Learning?
William Yang, Ye Zhu, Zhiwei Deng +1
Dataset distillation has emerged as a strategy to overcome the hurdles associated with large datasets by learning a compact set of synthetic data that retains essential information…
Analyzing the Roles of Language and Vision in Learning from Limited Data
Allison Chen, Ilia Sucholutsky, Olga Russakovsky +1
Does language help make sense of the visual world? How important is it to actually see the world rather than having it described with words? These basic questions about the nature…