4 citations · 6 across the 13 of their papers we have counts for
6 papers · 1 filter
HeadRouter: A Training-free Image Editing Framework for MM-DiTs by Adaptively Routing Attention Heads
Yu Xu, Fan Tang, Juan Cao +5
Diffusion Transformers (DiTs) have exhibited robust capabilities in image generation tasks. However, accurate text-guided image editing for multimodal DiTs (MM-DiTs) still poses a…
Newton Losses: Using Curvature Information for Learning with Differentiable Algorithms
Felix Petersen, Christian Borgelt, Tobias Sutter +3
When training neural networks with custom objectives, such as ranking losses and shortest-path losses, a common problem is that they are, per se, non-differentiable. A popular appr…
Break-for-Make: Modular Low-Rank Adaptations for Composable Content-Style Customization
Yu Xu, Fan Tang, Juan Cao +5
Personalized generation paradigms empower designers to customize visual intellectual properties with the help of textual descriptions by tuning or adapting pre-trained text-to-imag…
generAItor: Tree-in-the-Loop Text Generation for Language Model Explainability and Adaptation
Thilo Spinner, Rebecca Kehlbeck, Rita Sevastjanova +4
Large language models (LLMs) are widely deployed in various downstream tasks, e.g., auto-completion, aided writing, or chat-based text generation. However, the considered output ca…
Uncertainty Quantification via Stable Distribution Propagation
Felix Petersen, Aashwin Mishra, Hilde Kuehne +3
We propose a new approach for propagating stable probability distributions through neural networks. Our method is based on local linearization, which we show to be an optimal appro…
Dance-to-Music Generation with Encoder-based Textual Inversion
Sifei Li, Weiming Dong, Yuxin Zhang +5
The seamless integration of music with dance movements is essential for communicating the artistic intent of a dance piece. This alignment also significantly improves the immersive…