Tootfinder

Collaborative Human-Robot Surgery for Mandibular Angle Split Osteotomy: Optical Tracking based Approach
Zhe Han, Huanyu Tian, Tom Vercauteren, Da Liu, Changsheng Li, Xingguang Duan
https://arxiv.org/abs/2507.07794

Collaborative Human-Robot Surgery for Mandibular Angle Split Osteotomy: Optical Tracking based Approach
Mandibular Angle Split Osteotomy (MASO) is a significant procedure in oral and maxillofacial surgery. Despite advances in technique and instrumentation, its success still relies heavily on the surgeon's experience. In this work, a human-robot collaborative system is proposed to perform MASO according to a preoperative plan and under guidance of a surgeon. A task decomposition methodology is used to divide the collaborative surgical procedure into three subtasks: (1) positional control and (2) o…

Phase-Space Framework for Noisy Intermediate-Scale Quantum Optical Neural Networks
Stanis{\l}aw \'Swierczewski, Wouter Verstraelen, Piotr Deuar, Barbara Pi\k{e}tka, Timothy C. H. Liew, Micha{\l} Matuszewski, Andrzej Opala
https://arxiv.org/abs/2507.07684

Phase-Space Framework for Noisy Intermediate-Scale Quantum Optical Neural Networks
Quantum optical neural networks (QONNs) enable information processing beyond classical limits by exploiting the advantages of classical and quantum optics. However, simulation of large-scale bosonic lattices remains a significant challenge due to the exponential growth of the Hilbert space required to describe a quantum network accurately. Consequently, previous theoretical studies have been limited to small-scale systems, leaving the behaviour of multimode QONNs largely unexplored. This work p…

Re-Bottleneck: Latent Re-Structuring for Neural Audio Autoencoders
Dimitrios Bralios, Jonah Casebeer, Paris Smaragdis
https://arxiv.org/abs/2507.07867 http…

Re-Bottleneck: Latent Re-Structuring for Neural Audio Autoencoders
Neural audio codecs and autoencoders have emerged as versatile models for audio compression, transmission, feature-extraction, and latent-space generation. However, a key limitation is that most are trained to maximize reconstruction fidelity, often neglecting the specific latent structure necessary for optimal performance in diverse downstream applications. We propose a simple, post-hoc framework to address this by modifying the bottleneck of a pre-trained autoencoder. Our method introduces a …

This https://arxiv.org/abs/2502.15786 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qbi…

MindLLM: A Subject-Agnostic and Versatile Model for fMRI-to-Text Decoding
Decoding functional magnetic resonance imaging (fMRI) signals into text has been a key challenge in the neuroscience community, with the potential to advance brain-computer interfaces and uncover deeper insights into brain mechanisms. However, existing approaches often struggle with suboptimal predictive performance, limited task variety, and poor generalization across subjects. In response to this, we propose MindLLM, a model designed for subject-agnostic and versatile fMRI-to-text decoding. M…

Die Hamburger Palästina-Querfront will wieder durch die Schanze ziehen
https://www.mopo.de/hamburg/polizei/reichsbuerger-nahe-putin-versteher-demonstrieren-wieder-fuer-palaestina/

Reichsbürger-nahe Putin-Versteher wollen für Palästina demonstrieren
Sie argumentieren wie Reichsbürger, verbreiten pro-russische Propaganda, protestierten während der Pandemie gegen die angebliche Unterdrückung durch das

This https://arxiv.org/abs/2409.07885 has been replaced.
initial toot: https://mastoxiv.page/@ar…

Towards Timetronics with Photonic Systems
Periodic driving of particles can create crystalline structures in their dynamics. Such systems can be used to study solid-state physics phenomena in the time domain. In addition, it is possible to realize photonic time crystals and to engineer the wave-number band structure of optical devices by periodic temporal modulation of the properties of light-propagating media. Here we introduce a versatile approach which uses traveling wave resonators to emulate various condensed matter phases in the …

From Fragments to Facts: A Curriculum-Driven DPO Approach for Generating Hindi News Veracity Explanations
Pulkit Bansal, Raghvendra Kumar, Shakti Singh, Sriparna Saha, Adam Jatowt
https://arxiv.org/abs/2507.05179

From Fragments to Facts: A Curriculum-Driven DPO Approach for Generating Hindi News Veracity Explanations
In an era of rampant misinformation, generating reliable news explanations is vital, especially for under-represented languages like Hindi. Lacking robust automated tools, Hindi faces challenges in scaling misinformation detection. To bridge this gap, we propose a novel framework integrating Direct Preference Optimization (DPO) with curriculum learning to align machine-generated explanations with human reasoning. Fact-checked explanations from credible sources serve as preferred responses, whil…

Viele Menschen verstehen #Warnungen wie „#Hitzeindex“ oder „#Hitzewarnung“ falsch. Das zeigt eine US-Studie.
Fast die Hälfte hält den Hitzeindex für die reine

Bridging the Gap between National Weather Service Heat Terminology and Public Understanding
Abstract Clearly communicating heat warning information to the public is an important way to reduce heat mortality and morbidity. However, heat communication interventions from the National Weather Service commonly include technical and scientific terms, otherwise known as jargon. These terms, such as heat advisory or heat index, may not be understood by the public. Given the importance of message understanding in protective action decision-making, the purpose of this study is to assess how the…

A Physics-Based Continuum Model for Versatile, Scalable, and Fast Terramechanics Simulation
Huzaifa Unjhawala, Luning Bakke, Harry Zhang, Michael Taylor, Ganesh Arivoli, Radu Serban, Dan Negrut
https://arxiv.org/abs/2507.05643

A Physics-Based Continuum Model for Versatile, Scalable, and Fast Terramechanics Simulation
This paper discusses Chrono's Continuous Representation Model (called herein Chrono