Zobrazeno 1 - 10
of 19 547
pro vyhledávání: '"Kirchhoff, A."'
Autor:
Kirchhoff, Jonas
We give insight in the structure of port-Hamiltonian systems as control systems in between two closed Hamiltonian systems. Using the language of category theory, we identify systems with their behavioural representation and view a port-control struct
Externí odkaz:
http://arxiv.org/abs/2406.01303
Autor:
Kirchhoff, Jonas, Maschke, Bernhard
We study the geometric structure of port-Hamiltonian systems. Starting with the intuitive understanding that port-Hamiltonian systems are "in between" certain closed Hamiltonian systems, the geometric structure of port-Hamiltonian systems must be "in
Externí odkaz:
http://arxiv.org/abs/2406.01036
Autor:
Peri, Raghuveer, Jayanthi, Sai Muralidhar, Ronanki, Srikanth, Bhatia, Anshu, Mundnich, Karel, Dingliwal, Saket, Das, Nilaksh, Hou, Zejiang, Huybrechts, Goeric, Vishnubhotla, Srikanth, Garcia-Romero, Daniel, Srinivasan, Sundararajan, Han, Kyu J, Kirchhoff, Katrin
Integrated Speech and Large Language Models (SLMs) that can follow speech instructions and generate relevant text responses have gained popularity lately. However, the safety and robustness of these models remains largely unclear. In this work, we in
Externí odkaz:
http://arxiv.org/abs/2405.08317
Autor:
Das, Nilaksh, Dingliwal, Saket, Ronanki, Srikanth, Paturi, Rohit, Huang, Zhaocheng, Mathur, Prashant, Yuan, Jie, Bekal, Dhanush, Niu, Xing, Jayanthi, Sai Muralidhar, Li, Xilai, Mundnich, Karel, Sunkara, Monica, Srinivasan, Sundararajan, Han, Kyu J, Kirchhoff, Katrin
Large language models (LLMs) have shown incredible proficiency in performing tasks that require semantic understanding of natural language instructions. Recently, many works have further expanded this capability to perceive multimodal audio and text
Externí odkaz:
http://arxiv.org/abs/2405.08295
The M{\o}lmer-S{\o}rensen gate is a widely used entangling gate for ion platforms with inherent robustness to trap heating. The gate performance is limited by coherent errors, arising from the Lamb-Dicke (LD) approximation and sideband errors. Here,
Externí odkaz:
http://arxiv.org/abs/2404.17478
Autor:
Tang, Zhiqiang, Fang, Haoyang, Zhou, Su, Yang, Taojiannan, Zhong, Zihan, Hu, Tony, Kirchhoff, Katrin, Karypis, George
AutoGluon-Multimodal (AutoMM) is introduced as an open-source AutoML library designed specifically for multimodal learning. Distinguished by its exceptional ease of use, AutoMM enables fine-tuning of foundation models with just three lines of code. S
Externí odkaz:
http://arxiv.org/abs/2404.16233
The definition of conservative-irreversible functions is extended to smooth manifolds. The local representation of these functions is studied and reveals that not each conservative-irreversible function is given by the weighted product of almost Pois
Externí odkaz:
http://arxiv.org/abs/2404.04092
Autor:
Kirchhoff, Yannick, Rokuss, Maximilian R., Roy, Saikat, Kovacs, Balint, Ulrich, Constantin, Wald, Tassilo, Zenk, Maximilian, Vollmuth, Philipp, Kleesiek, Jens, Isensee, Fabian, Maier-Hein, Klaus
Accurately segmenting thin tubular structures, such as vessels, nerves, roads or concrete cracks, is a crucial task in computer vision. Standard deep learning-based segmentation loss functions, such as Dice or Cross-Entropy, focus on volumetric overl
Externí odkaz:
http://arxiv.org/abs/2404.03010
Autor:
Im, Changbin, Kirchhoff, Björn, Mitoraj, Dariusz, Krivtsov, Igor, Farkas, Attila, Beranek, Radim, Jacob, Timo
Two-dimensional (2D) materials have attracted considerable attention due to their unique physicochemical properties and significant potential in energy-related applications. Polymeric carbon nitrides (PCNs) with 2D stacked architecture show promise a
Externí odkaz:
http://arxiv.org/abs/2403.13685
Autor:
Huang, James Y., Sengupta, Sailik, Bonadiman, Daniele, Lai, Yi-an, Gupta, Arshit, Pappas, Nikolaos, Mansour, Saab, Kirchhoff, Katrin, Roth, Dan
Large Language Models (LLMs) are nowadays expected to generate content aligned with human preferences. Current work focuses on alignment at model training time, through techniques such as Reinforcement Learning with Human Feedback (RLHF). However, it
Externí odkaz:
http://arxiv.org/abs/2402.06147