1 citations · 4 across the 13 of their papers we have counts for
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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…
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…
A Survey on the Real Power of ChatGPT
Ming Liu, Ran Liu, Ye Zhu +5
ChatGPT has changed the AI community and an active research line is the performance evaluation of ChatGPT. A key challenge for the evaluation is that ChatGPT is still closed-source…
D: Scaling Up Deepfake Detection by Learning from Discrepancy
Yongqi Yang, Zhihao Qian, Ye Zhu +2
The boom of Generative AI brings opportunities entangled with risks and concerns. Existing literature emphasizes the generalization capability of deepfake detection on unseen gener…
HAM-TTS: Hierarchical Acoustic Modeling for Token-Based Zero-Shot Text-to-Speech with Model and Data Scaling
Chunhui Wang, Chang Zeng, Bowen Zhang +6
Token-based text-to-speech (TTS) models have emerged as a promising avenue for generating natural and realistic speech, yet they grapple with low pronunciation accuracy, speaking s…