5 papers
TF-TI2I: Training-Free Text-and-Image-to-Image Generation via Multi-Modal Implicit-Context Learning in Text-to-Image Models
Teng-Fang Hsiao, Bo-Kai Ruan, Yi-Lun Wu +2
Text-and-Image-To-Image (TI2I), an extension of Text-To-Image (T2I), integrates image inputs with textual instructions to enhance image generation. Existing methods often partially…
HyCE-RAG: Hypergraph Chain-of-Evidence Retrieval-Augmented Generation for Explainable Multi-hop Question Answering
Hong-Yu An, Yun-Jian Zhang, Chen-Wei Liang +7
Multi-hop question answering requires systems to retrieve evidence from multiple documents and connect scattered facts into a coherent reasoning process. Standard retrieval-augment…
PromptMoG: Enhancing Diversity in Long-Prompt Image Generation via Prompt Embedding Mixture-of-Gaussian Sampling
Bo-Kai Ruan, Teng-Fang Hsiao, Ling Lo +2
Recent advances in text-to-image (T2I) generation have achieved remarkable visual outcomes through large-scale rectified flow models. However, how these models behave under long pr…
Ranking-based Preference Optimization for Diffusion Models from Implicit User Feedback
Yi-Lun Wu, Bo-Kai Ruan, Chiang Tseng +1
Direct preference optimization (DPO) methods have shown strong potential in aligning text-to-image diffusion models with human preferences by training on paired comparisons. These…
FreeCond: Free Lunch in the Input Conditions of Text-Guided Inpainting
Teng-Fang Hsiao, Bo-Kai Ruan, Sung-Lin Tsai +2
In this study, we aim to determine and solve the deficiency of Stable Diffusion Inpainting (SDI) in following the instruction of both prompt and mask. Due to the training bias from…