Tootfinder

Beyond touch-based HMI: Control your machines in natural language by utilizing large language models and OPC UA
Bernd Hofmann, Sven Kreitlein, Joerg Franke, Patrick Bruendl
https://arxiv.org/abs/2510.11300

Beyond touch-based HMI: Control your machines in natural language by utilizing large language models and OPC UA
This paper proposes an agent-based approach toward a more natural interface between humans and machines. Large language models equipped with tools and the communication standard OPC UA are utilized to control machines in natural language. Instead of touch interaction, which is currently the state-of-the-art medium for interaction in operations, the proposed approach enables operators to talk or text with machines. This allows commands such as 'Please decrease the temperature by 20 % in machine …

Probabilistic Constellation Shaping for OFDM ISAC Signals Under Temporal-Frequency Filtering
Zhen Du, Jingjing Xu, Yifeng Xiong, Jie Wang, Musa Furkan Keskin, Henk Wymeersch, Fan Liu, Shi Jin
https://arxiv.org/abs/2510.12204

Probabilistic Constellation Shaping for OFDM ISAC Signals Under Temporal-Frequency Filtering
Integrated sensing and communications (ISAC) is considered an innovative technology in sixth-generation (6G) wireless networks, where utilizing orthogonal frequency division multiplexing (OFDM) communication signals for sensing provides a cost-effective solution for implementing ISAC. However, the sensing performance of matched and mismatched filtering schemes can be significantly deteriorated due to the signaling randomness induced by finite-alphabet modulations with nonconstant modulus, such …

Contextuality-based quantum key distribution with deterministic single-photon sources
Yu Meng, Debashis Saha, Mikkel Thorbj{\o}rn Mikkelsen, Clara Henke, Ying Wang, Nikolai Bart, Arne Ludwig, Ad\'an Cabello, Leonardo Midolo
https://arxiv.org/abs/2510.12761

Contextuality-based quantum key distribution with deterministic single-photon sources
Photons are central to quantum technologies, with photonic qubits offering a promising platform for quantum communication. Semiconductor quantum dots stand out for their ability to generate single photons on demand, a key capability for enabling long-distance quantum networks. In this work, we utilize high-purity single-photon sources based on self-assembled InAs(Ga)As quantum dots as quantum information carriers. We demonstrate that such on-demand single photons can generate quantum contextual…

OTFS for Joint Radar and Communication: Algorithms, Prototypes, and Experiments
Xiaojuan Zhang, Yonghong Zeng, Francois Chin Po Shin
https://arxiv.org/abs/2510.00668 https://

OTFS for Joint Radar and Communication: Algorithms, Prototypes, and Experiments
We propose an Joint Radar and Communication (JRC) system that utilizes the Orthogonal Time Frequency Space (OTFS) signals. The system features a fast radar sensing algorithm for detecting target range and speed by using the OTFS communication signals, and a self-interference cancellation for enhanced multi-target separation. In addition to target detection, we propose methods for monitoring human vital signs, such as breathing rate and heartbeat. Furthermore, we explore two approaches for disti…

GPU-Accelerated Algorithms for Process Mapping
Petr Samoldekin, Christian Schulz, Henning Woydt
https://arxiv.org/abs/2510.12196 https://arxiv.org/pdf/2510…

GPU-Accelerated Algorithms for Process Mapping
Process mapping asks to assign vertices of a task graph to processing elements of a supercomputer such that the computational workload is balanced while the communication cost is minimized. Motivated by the recent success of GPU-based graph partitioners, we propose two GPU-accelerated algorithms for this optimization problem. The first algorithm employs hierarchical multisection, which partitions the task graph alongside the hierarchy of the supercomputer. The method utilizes GPU-based graph pa…

xRouter: Training Cost-Aware LLMs Orchestration System via Reinforcement Learning
Cheng Qian, Zuxin Liu, Shirley Kokane, Akshara Prabhakar, Jielin Qiu, Haolin Chen, Zhiwei Liu, Heng Ji, Weiran Yao, Shelby Heinecke, Silvio Savarese, Caiming Xiong, Huan Wang
https://arxiv.org/abs/2510.08439

xRouter: Training Cost-Aware LLMs Orchestration System via Reinforcement Learning
Modern LLM deployments confront a widening cost-performance spectrum: premium models deliver strong reasoning but are expensive, while lightweight models are economical yet brittle on complex tasks. Static escalation rules and keyword heuristics under-utilize this spectrum and fail to adapt across task types. We present xRouter, a tool-calling-based routing system in which a learned router can either answer directly or invoke one or more external models. The router is trained end-to-end with re…

Effect of nearby Metals on Electro-Quasistatic Human Body Communication
Samyadip Sarkar, Arunashish Datta, David Yang, Mayukh Nath, Shovan Maity, Shreyas Sen
https://arxiv.org/abs/2510.04409

Effect of nearby Metals on Electro-Quasistatic Human Body Communication
In recent decades Human Body Communication has emerged as a promising alternative to traditional radio wave communication, utilizing the body's conductive properties for low-power connectivity among wearables. This method harnesses the human body as an energy-efficient channel for data transmission within the electro-quasistatic frequency range, enabling advancements in human-machine interaction. While prior work has noted the role of parasitic return paths in such capacitively coupled systems,…

NeuroBridge: Using Generative AI to Bridge Cross-neurotype Communication Differences through Neurotypical Perspective-taking
Rukhshan Haroon, Kyle Wigdor, Katie Yang, Nicole Toumanios, Eileen T. Crehan, Fahad Dogar
https://arxiv.org/abs/2509.23434

NeuroBridge: Using Generative AI to Bridge Cross-neurotype Communication Differences through Neurotypical Perspective-taking
Communication challenges between autistic and neurotypical individuals stem from a mutual lack of understanding of each other's distinct, and often contrasting, communication styles. Yet, autistic individuals are expected to adapt to neurotypical norms, making interactions inauthentic and mentally exhausting for them. To help redress this imbalance, we build NeuroBridge, an online platform that utilizes large language models (LLMs) to simulate: (a) an AI character that is direct and literal, a …

Maritime Communication in Evaporation Duct Environment with Ship Trajectory Optimization
Ruifeng Gao, Hao Zhang, Jue Wang, Ye Li, Yingdong Hu, Qiuming Zhu, Shu Sun, Meixia Tao
https://arxiv.org/abs/2510.06946

Maritime Communication in Evaporation Duct Environment with Ship Trajectory Optimization
In maritime wireless networks, the evaporation duct effect has been known as a preferable condition for long-range transmissions. However, how to effectively utilize the duct effect for efficient communication design is still open for investigation. In this paper, we consider a typical scenario of ship-to-shore data transmission, where a ship collects data from multiple oceanographic buoys, sails from one to another, and transmits the collected data back to a terrestrial base station during its…

Utilizing Model-Free Reinforcement Learning for Optimizing Secure Multi-Party Computation Protocols
Javad Sayyadi, Mahdi Nangir, Mahmood Mohassel Feghhi, Hamid Sayyadi
https://arxiv.org/abs/2510.07814 …

Utilizing Model-Free Reinforcement Learning for Optimizing Secure Multi-Party Computation Protocols
In this manuscript, we explore the application of model-free reinforcement learning in optimizing secure multiparty computation (SMPC) protocols. SMPC is a crucial tool for performing computations on private data without the need to disclose it, holding significant importance in various domains, including information security and privacy. However, the efficiency of current protocols is often suboptimal due to computational and communicational complexities. Our proposed approach leverages model-…