activity
20192025
most citedForce-Directed Graph Layouts Revisited: A New Force Based on the T-Distribution

12 citations · 22 across the 11 of their papers we have counts for

collaborators

11 papers

cs.RO2025

Mesh2SLAM in VR: A Fast Geometry-Based SLAM Framework for Rapid Prototyping in Virtual Reality Applications

Carlos Augusto Pinheiro de Sousa, Heiko Hamann, Oliver Deussen

SLAM is a foundational technique with broad applications in robotics and AR/VR. SLAM simulations evaluate new concepts, but testing on resource-constrained devices, such as VR HMDs…

cs.CV2024

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…

cs.CV2024

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…

cs.HC20244 cited

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…

cs.LG2024

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…

cs.CL2023

Revealing the Unwritten: Visual Investigation of Beam Search Trees to Address Language Model Prompting Challenges

Thilo Spinner, Rebecca Kehlbeck, Rita Sevastjanova +5

The growing popularity of generative language models has amplified interest in interactive methods to guide model outputs. Prompt refinement is considered one of the most effective…