Tootfinder

ISCA: A Framework for Interview-Style Conversational Agents
Charles Welch, Allison Lahnala, Vasudha Varadarajan, Lucie Flek, Rada Mihalcea, J. Lomax Boyd, Jo\~ao Sedoc
https://arxiv.org/abs/2508.14344 …

ISCA: A Framework for Interview-Style Conversational Agents
We present a low-compute non-generative system for implementing interview-style conversational agents which can be used to facilitate qualitative data collection through controlled interactions and quantitative analysis. Use cases include applications to tracking attitude formation or behavior change, where control or standardization over the conversational flow is desired. We show how our system can be easily adjusted through an online administrative panel to create new interviews, making the …

Extracting Insights from Large-Scale Telematics Data for ITS Applications: Lessons and Recommendations
Gibran Ali, Neal Feierabend, Prarthana Doshi, Calvin Winkowski, Michael Fontaine
https://arxiv.org/abs/2507.13936

Extracting Insights from Large-Scale Telematics Data for ITS Applications: Lessons and Recommendations
Over 90% of new vehicles in the United States now collect and transmit telematics data. Similar trends are seen in other developed countries. Transportation planners have previously utilized telematics data in various forms, but its current scale offers significant new opportunities in traffic measurement, classification, planning, and control. Despite these opportunities, the enormous volume of data and lack of standardization across manufacturers necessitates a clearer understanding of the da…

Failure Tolerant Phase-Only Indoor Positioning via Deep Learning
Fatih Ayten, Mehmet C. Ilter, Akshay Jain, Ossi Kaltiokallio, Jukka Talvitie, Elena Simona Lohan, Henk Wymeersch, Mikko Valkama
https://arxiv.org/abs/2508.14739

Failure Tolerant Phase-Only Indoor Positioning via Deep Learning
High-precision localization turns into a crucial added value and asset for next-generation wireless systems. Carrier phase positioning (CPP) enables sub-meter to centimeter-level accuracy and is gaining interest in 5G-Advanced standardization. While CPP typically complements time-of-arrival (ToA) measurements, recent literature has introduced a phase-only positioning approach in a distributed antenna/MIMO system context with minimal bandwidth requirements, using deep learning (DL) when operatin…

Towards Nomadic 6G Communication Networks: Implications on Architecture, Standardization, and Regulatory Aspects
Daniel Lindenschmitt, Marcos Rates Crippa, Hans D. Schotten
https://arxiv.org/abs/2508.12710

Towards Nomadic 6G Communication Networks: Implications on Architecture, Standardization, and Regulatory Aspects
The emergence of nomadic mobile communication networks for sixth-generation (6G) introduces a paradigm shift in how network infrastructure is conceptualized, deployed, and operated. Unlike traditional fixed systems, Nomadic Networks (NNs) consist of mobile and self-organizing nodes that provide radio infrastructure capabilities in motion. This paper explores the architectural implications of such systems, with a particular focus on the design and evolution of network interfaces. We analyze the …

Overcoming Standardization: Revealing Hidden Age Patterns of Suicide with Spatiotemporal Models
J. Mart\'in-Pozuelo (Department of Statistics and Operations Research. University of Valencia), A. L\'opez-Qu\'ilez (Department of Statistics and Operations Research. University of Valencia), X. Barber (Joint Research Unit UMH-FISABIO), M. Marco (Department of Social Psychology, University of Valencia)

Overcoming Standardization: Revealing Hidden Age Patterns of Suicide with Spatiotemporal Models
Indirect standardization is widely used in disease mapping to control for confounding, but relies on restrictive assumptions that may bias estimates if violated. Using data on suicide-related emergency calls, this study highlights such limitations and proposes age-structured hierarchical Bayesian models as an alternative. These models incorporate space-time, space-age, and time-age interactions, allowing for more accurate estimation without strong assumptions. The results show improved model fi…

Towards Native AI in 6G Standardization: The Roadmap of Semantic Communication
Ping Zhang, Xiaodong Xu, Mengying Sun, Haixiao Gao, Nan Ma, Xiaoyun Wang, Ruichen Zhang, Jiacheng Wang, Dusit Niyato
https://arxiv.org/abs/2509.12758

Towards Native AI in 6G Standardization: The Roadmap of Semantic Communication
Semantic communication (SemCom) has emerged as a transformative paradigm for future 6G networks, offering task-oriented and meaning-aware transmission that fundamentally redefines traditional bit-centric design. Recognized by leading standardization bodies including the institute of electrical and electronics engineers (IEEE) and the international telecommunication union (ITU), and actively discussed within the 3rd generation partnership project (3GPP) working groups, SemCom is rapidly gaining …

Automatically describe data and models as text using the {report} package. #rstats

A Fault Analysis on SNOVA
Gustavo Banegas (GRACE), Ricardo Villanueva-Polanco (TII)
https://arxiv.org/abs/2509.12879 https://arxiv.org/pdf/2509.12879

A Fault Analysis on SNOVA
SNOVA is a post-quantum cryptographic signature scheme known for its efficiency and compact key sizes, making it a second-round candidate in the NIST post-quantum cryptography standardization process. This paper presents a comprehensive fault analysis of SNOVA, focusing on both permanent and transient faults during signature generation. We introduce several fault injection strategies that exploit SNOVA's structure to recover partial or complete secret keys with limited faulty signatures. Our an…

LLM-Based Approach for Enhancing Maintainability of Automotive Architectures
Nenad Petrovic, Lukasz Mazur, Alois Knoll
https://arxiv.org/abs/2509.12798 https://

LLM-Based Approach for Enhancing Maintainability of Automotive Architectures
There are many bottlenecks that decrease the flexibility of automotive systems, making their long-term maintenance, as well as updates and extensions in later lifecycle phases increasingly difficult, mainly due to long re-engineering, standardization, and compliance procedures, as well as heterogeneity and numerosity of devices and underlying software components involved. In this paper, we explore the potential of Large Language Models (LLMs) when it comes to the automation of tasks and process…

Generating Actionable Robot Knowledge Bases by Combining 3D Scene Graphs with Robot Ontologies
Giang Nguyen, Mihai Pomarlan, Sascha Jongebloed, Nils Leusmann, Minh Nhat Vu, Michael Beetz
https://arxiv.org/abs/2507.11770

Generating Actionable Robot Knowledge Bases by Combining 3D Scene Graphs with Robot Ontologies
In robotics, the effective integration of environmental data into actionable knowledge remains a significant challenge due to the variety and incompatibility of data formats commonly used in scene descriptions, such as MJCF, URDF, and SDF. This paper presents a novel approach that addresses these challenges by developing a unified scene graph model that standardizes these varied formats into the Universal Scene Description (USD) format. This standardization facilitates the integration of these …

An Agentic Model Context Protocol Framework for Medical Concept Standardization
Jaerong Ahn, Andrew Wen, Nan Wang, Heling Jia, Zhiyi Yue, Sunyang Fu, Hongfang Liu
https://arxiv.org/abs/2509.03828

An Agentic Model Context Protocol Framework for Medical Concept Standardization
The Observational Medical Outcomes Partnership (OMOP) common data model (CDM) provides a standardized representation of heterogeneous health data to support large-scale, multi-institutional research. One critical step in data standardization using OMOP CDM is the mapping of source medical terms to OMOP standard concepts, a procedure that is resource-intensive and error-prone. While large language models (LLMs) have the potential to facilitate this process, their tendency toward hallucination ma…

Dredging up recollections of my experience as R6RS editor for my PLSS talk tomorrow.
https://2025.ecoop.org/details/plss-2025-papers/8/Do-Programming-Languages-Fulfill-Requirements-Should-They-

Towards AI-Native RAN: An Operator's Perspective of 6G Day 1 Standardization
Nan Li, Qi Sun, Lehan Wang, Xiaofei Xu, Jinri Huang, Chunhui Liu, Jing Gao, Yuhong Huang, Chih-Lin I
https://arxiv.org/abs/2507.08403

Towards AI-Native RAN: An Operator's Perspective of 6G Day 1 Standardization
Artificial Intelligence/Machine Learning (AI/ML) has become the most certain and prominent feature of 6G mobile networks. Unlike 5G, where AI/ML was not natively integrated but rather an add-on feature over existing architecture, 6G shall incorporate AI from the onset to address its complexity and support ubiquitous AI applications. Based on our extensive mobile network operation and standardization experience from 2G to 5G, this paper explores the design and standardization principles of AI-Na…

Replaced article(s) found for cs.HC. https://arxiv.org/list/cs.HC/new
[1/1]:
- Human-AI Collaboration for Wearable Technology Component Standardization
Andrew M. Lydner

Unveiling Usability Challenges in Web Privacy Controls
Rahat Masood, Sunday Oyinlola Ogundoyin, Muhammad Ikram, Alex Ye
https://arxiv.org/abs/2507.11908 ht…

Unveiling Usability Challenges in Web Privacy Controls
With the increasing concerns around privacy and the enforcement of data privacy laws, many websites now provide users with privacy controls. However, locating these controls can be challenging, as they are frequently hidden within multiple settings and layers. Moreover, the lack of standardization means these controls can vary widely across services. The technical or confusing terminology used to describe these controls further complicates users' ability to understand and use them effectively. …

Taming Domain Shift in Multi-source CT-Scan Classification via Input-Space Standardization
Chia-Ming Lee, Bo-Cheng Qiu, Ting-Yao Chen, Ming-Han Sun, Fang-Ying Lin, Jung-Tse Tsai, I-An Tsai, Yu-Fan Lin, Chih-Chung Hsu
https://arxiv.org/abs/2507.19858

Taming Domain Shift in Multi-source CT-Scan Classification via Input-Space Standardization
Multi-source CT-scan classification suffers from domain shifts that impair cross-source generalization. While preprocessing pipelines combining Spatial-Slice Feature Learning (SSFL++) and Kernel-Density-based Slice Sampling (KDS) have shown empirical success, the mechanisms underlying their domain robustness remain underexplored. This study analyzes how this input-space standardization manages the trade-off between local discriminability and cross-source generalization. The SSFL++ and KDS pipel…

Evaluating Artificial Intelligence Algorithms for the Standardization of Transtibial Prosthetic Socket Shape Design
C. H. E. Jordaan, M. van der Stelt, T. J. J. Maal, V. M. A. Stirler, R. Leijendekkers, T. Kachman, G. A. de Jong
https://arxiv.org/abs/2507.16818

Evaluating Artificial Intelligence Algorithms for the Standardization of Transtibial Prosthetic Socket Shape Design
The quality of a transtibial prosthetic socket depends on the prosthetist's skills and expertise, as the fitting is performed manually. This study investigates multiple artificial intelligence (AI) approaches to help standardize transtibial prosthetic socket design. Data from 118 patients were collected by prosthetists working in the Dutch healthcare system. This data consists of a three-dimensional (3D) scan of the residual limb and a corresponding 3D model of the prosthetist-designed socket. …

LiDARCrafter: Dynamic 4D World Modeling from LiDAR Sequences
Ao Liang, Youquan Liu, Yu Yang, Dongyue Lu, Linfeng Li, Lingdong Kong, Huaici Zhao, Wei Tsang Ooi
https://arxiv.org/abs/2508.03692

LiDARCrafter: Dynamic 4D World Modeling from LiDAR Sequences
Generative world models have become essential data engines for autonomous driving, yet most existing efforts focus on videos or occupancy grids, overlooking the unique LiDAR properties. Extending LiDAR generation to dynamic 4D world modeling presents challenges in controllability, temporal coherence, and evaluation standardization. To this end, we present LiDARCrafter, a unified framework for 4D LiDAR generation and editing. Given free-form natural language inputs, we parse instructions into eg…

A Unified Framework for Cultural Heritage Data Historicity and Migration: The ARGUS Approach
Lingxiao Kong, Apostolos Sarris, Miltiadis Polidorou, Victor Klingenberg, Vasilis Sevetlidis, Vasilis Arampatzakis, George Pavlidis, Cong Yang, Zeyd Boukhers
https://arxiv.org/abs/2509.06044

A Unified Framework for Cultural Heritage Data Historicity and Migration: The ARGUS Approach
Cultural heritage preservation faces significant challenges in managing diverse, multi-source, and multi-scale data for effective monitoring and conservation. This paper documents a comprehensive data historicity and migration framework implemented within the ARGUS project, which addresses the complexities of processing heterogeneous cultural heritage data. We describe a systematic data processing pipeline encompassing standardization, enrichment, integration, visualization, ingestion, and publ…

A Tractable Approach to Massive Communication and Ubiquitous Connectivity in 6G Standardization
Junyi Jiang (Angela), Wei Chen (Angela), Xin Guo (Angela), Shenghui Song (Angela), Ying Jun (Angela), Zhang, Zhu Han, Merouane Debbah, Khaled B. Letaief
https://arxiv.org/abs/2506.16304

A Tractable Approach to Massive Communication and Ubiquitous Connectivity in 6G Standardization
The full-scale 6G standardization has attracted considerable recent attention, especially since the first 3GPP-wide 6G workshop held in March 2025. To understand the practical and fundamental values of 6G and facilitate its standardization, it is crucial to explore the theoretical limits of spectrum, energy, and coverage efficiency considering practical hardware and signaling constraints. In this paper, we present a mean-field-approximation-based investigation on two out of six use case scenari…

Industrial Viewpoints on RAN Technologies for 6G
Mansoor Shafi, Erik G. Larsson, Xingqin Lin, Dorin Panaitopol, Stefan Parkvall, Flavien Ronteix-Jacquet, Antti Toskala
https://arxiv.org/abs/2508.08225 …

Industrial Viewpoints on RAN Technologies for 6G
6G standardization is to start imminently, with commercial deployments expected before 2030. Its technical components and performance requirements are the focus of this article. Our emphasis is on the 6G radio access, especially MIMO, AI, waveforms, coding, signal constellations and integration with non-terrestrial networks. Whilst standardization has not yet formally started, the scope of the 6G study items has been defined. Our predictions in this paper are speculative as there are no results…

CF-RAG: A Dataset and Method for Carbon Footprint QA Using Retrieval-Augmented Generation
Kaiwen Zhao, Bharathan Balaji, Stephen Lee
https://arxiv.org/abs/2508.03489 https://

CF-RAG: A Dataset and Method for Carbon Footprint QA Using Retrieval-Augmented Generation
Product sustainability reports provide valuable insights into the environmental impacts of a product and are often distributed in PDF format. These reports often include a combination of tables and text, which complicates their analysis. The lack of standardization and the variability in reporting formats further exacerbate the difficulty of extracting and interpreting relevant information from large volumes of documents. In this paper, we tackle the challenge of answering questions related to …

Energy-Aware 6G Network Design: A Survey
Rashmi Kamran, Mahesh Ganesh Bhat, Pranav Jha, Shana Moothedath, Manjesh Hanawal, Prasanna Chaporkar
https://arxiv.org/abs/2509.11289 ht…

Energy-Aware 6G Network Design: A Survey
6th Generation (6G) mobile networks are envisioned to support several new capabilities and data-centric applications for unprecedented number of users, potentially raising significant energy efficiency and sustainability concerns. This brings focus on sustainability as one of the key objectives in the their design. To move towards sustainable solution, research and standardization community is focusing on several key issues like energy information monitoring and exposure, use of renewable energ…

Model-robust standardization in stepped wedge designs
Xi Fang, Xueqi Wang, Patrick J. Heagerty, Bingkai Wang, Fan Li
https://arxiv.org/abs/2507.17190 https://

Model-robust standardization in stepped wedge designs
Stepped-wedge cluster-randomized trials (SW-CRTs) are widely used in healthcare and implementation science, providing an ethical advantage by ensuring all clusters eventually receive the intervention. The staggered rollout of treatment introduces complexities in defining and estimating treatment effect estimands, particularly under informative sizes. Traditional model-based methods, including generalized estimating equations (GEE) and linear mixed models (LMM), produce estimates that depend on …

Do We Need Pre-Processing for Deep Learning Based Ultrasound Shear Wave Elastography?
Sarah Grube, S\"oren Gr\"unhagen, Sarah Latus, Michael Meyling, Alexander Schlaefer
https://arxiv.org/abs/2508.03744

Do We Need Pre-Processing for Deep Learning Based Ultrasound Shear Wave Elastography?
Estimating the elasticity of soft tissue can provide useful information for various diagnostic applications. Ultrasound shear wave elastography offers a non-invasive approach. However, its generalizability and standardization across different systems and processing pipelines remain limited. Considering the influence of image processing on ultrasound based diagnostics, recent literature has discussed the impact of different image processing steps on reliable and reproducible elasticity analysis.…

Physics-Informed Neural Networks for Industrial Gas Turbines: Recent Trends, Advancements and Challenges
Afila Ajithkumar Sophiya, Sepehr Maleki, Giuseppe Bruni, Senthil K. Krishnababu
https://arxiv.org/abs/2506.19503

Physics-Informed Neural Networks for Industrial Gas Turbines: Recent Trends, Advancements and Challenges
Physics-Informed Neural Networks (PINNs) have emerged as a promising computational framework for solving differential equations by integrating deep learning with physical constraints. However, their application in gas turbines is still in its early stages, requiring further refinement and standardization for wider adoption. This survey provides a comprehensive review of PINNs in Industrial Gas Turbines (IGTs) research, highlighting their contributions to the analysis of aerodynamic and aeromech…

Future Illiteracies -- Architectural Epistemology and Artificial Intelligence
Mustapha El Moussaoui
https://arxiv.org/abs/2507.23434 https://arxiv.org/pdf/…

Future Illiteracies -- Architectural Epistemology and Artificial Intelligence
In the age of artificial intelligence, architectural practice faces a paradox of immense potential and creeping standardization. As humans are increasingly relying on AI-generated outputs, architecture risks becoming a spectacle of repetition- a shuffling of data that neither truly innovates nor progresses vertically in creative depth. This paper explores the critical role of data in AI systems, scrutinizing the training datasets that form the basis of AI's generative capabilities and the impli…

Enhanced Drift-Aware Computer Vision Architecture for Autonomous Driving
Md Shahi Amran Hossain, Abu Shad Ahammed, Sayeri Mukherjee, Roman Obermaisser
https://arxiv.org/abs/2508.17975

Enhanced Drift-Aware Computer Vision Architecture for Autonomous Driving
The use of computer vision in automotive is a trending research in which safety and security are a primary concern. In particular, for autonomous driving, preventing road accidents requires highly accurate object detection under diverse conditions. To address this issue, recently the International Organization for Standardization (ISO) released the 8800 norm, providing structured frameworks for managing associated AI relevant risks. However, challenging scenarios such as adverse weather or low …

An (m,k)-firm Elevation Policy to Increase the Robustness of Time-Driven Schedules in 5G Time-Sensitive Networks
Simon Egger, Robin Laidig, Heiko Geppert, Lucas Haug, Jona Herrmann, Frank D\"urr, Christian Becker
https://arxiv.org/abs/2508.09769

An (m,k)-firm Elevation Policy to Increase the Robustness of Time-Driven Schedules in 5G Time-Sensitive Networks
Current standardization efforts are advancing the integration of 5G and Time-Sensitive Networking (TSN) to facilitate the deployment of safety-critical industrial applications that require real-time communication. However, there remains a fundamental disconnect between the probabilistic 5G delay characteristics and the often idealistic delay models used to synthesize 5G-TSN network configurations. For time-driven schedules in particular, any delay outlier unforeseen during schedule synthesis ca…

WHAR Datasets: An Open Source Library for Wearable Human Activity Recognition
Maximilian Burzer, Tobias King, Till Riedel, Michael Beigl, Tobias R\"oddiger
https://arxiv.org/abs/2508.16604

WHAR Datasets: An Open Source Library for Wearable Human Activity Recognition
The lack of standardization across Wearable Human Activity Recognition (WHAR) datasets limits reproducibility, comparability, and research efficiency. We introduce WHAR datasets, an open-source library designed to simplify WHAR data handling through a standardized data format and a configuration-driven design, enabling reproducible and computationally efficient workflows with minimal manual intervention. The library currently supports 9 widely-used datasets, integrates with PyTorch and TensorFl…

DCPO: Dynamic Clipping Policy Optimization
Shihui Yang, Chengfeng Dou, Peidong Guo, Kai Lu, Qiang Ju, Fei Deng, Rihui Xin
https://arxiv.org/abs/2509.02333 https://

DCPO: Dynamic Clipping Policy Optimization
Reinforcement Learning from Verifiable Rewards (RLVR) has emerged as a promising framework for enhancing the reasoning capabilities of large language models. However, existing approaches such as GRPO often suffer from zero gradients. This problem arises primarily due to fixed clipping bounds for token-level probability ratios and the standardization of identical rewards, which can lead to ineffective gradient updates and underutilization of generated responses. In this work, we propose Dynamic …

Use as Directed? A Comparison of Software Tools Intended to Check Rigor and Transparency of Published Work
Peter Eckmann, Adrian Barnett, Alexandra Bannach-Brown, Elisa Pilar Bascunan Atria, Guillaume Cabanac, Louise Delwen Owen Franzen, Ma{\l}gorzata Anna Gazda, Kaitlyn Hair, James Howison, Halil Kilicoglu, Cyril Labbe, Sarah McCann, Vladislav Nachev, Martijn Roelandse, Maia Salholz-Hillel, Robert Schulz, Gerben ter Riet, Colby Vorland, Anita Bandrowski, Tracey Weissgerber

Use as Directed? A Comparison of Software Tools Intended to Check Rigor and Transparency of Published Work
The causes of the reproducibility crisis include lack of standardization and transparency in scientific reporting. Checklists such as ARRIVE and CONSORT seek to improve transparency, but they are not always followed by authors and peer review often fails to identify missing items. To address these issues, there are several automated tools that have been designed to check different rigor criteria. We have conducted a broad comparison of 11 automated tools across 9 different rigor criteria from t…

What's Really Different with AI? -- A Behavior-based Perspective on System Safety for Automated Driving Systems
Marcus Nolte, Nayel Fabian Salem, Olaf Franke, Jan Heckmann, Christoph H\"ohmann, Georg Stettinger, Markus Maurer
https://arxiv.org/abs/2507.20685

What's Really Different with AI? -- A Behavior-based Perspective on System Safety for Automated Driving Systems
Assuring safety for ``AI-based'' systems is one of the current challenges in safety engineering. For automated driving systems, in particular, further assurance challenges result from the open context that the systems need to operate in after deployment. The current standardization and regulation landscape for ``AI-based'' systems is becoming ever more complex, as standards and regulations are being released at high frequencies. This position paper seeks to provide guidance for making qualifi…

Unfolding Data Quality Dimensions in Practice: A Survey
Vasileios Papastergios, Lisa Ehrlinger, Anastasios Gounaris
https://arxiv.org/abs/2507.17507 https:…

Unfolding Data Quality Dimensions in Practice: A Survey
Data quality describes the degree to which data meet specific requirements and are fit for use by humans and/or downstream tasks (e.g., artificial intelligence). Data quality can be assessed across multiple high-level concepts called dimensions, such as accuracy, completeness, consistency, or timeliness. While extensive research and several attempts for standardization (e.g., ISO/IEC 25012) exist for data quality dimensions, their practical application often remains unclear. In parallel to rese…

TCM-Tongue: A Standardized Tongue Image Dataset with Pathological Annotations for AI-Assisted TCM Diagnosis
Xuebo Jin, Longfei Gao, Anshuo Tong, Zhengyang Chen, Jianlei Kong, Ning Sun, Huijun Ma, Qiang Wang, Yuting Bai, Tingli Su
https://arxiv.org/abs/2507.18288

TCM-Tongue: A Standardized Tongue Image Dataset with Pathological Annotations for AI-Assisted TCM Diagnosis
Traditional Chinese medicine (TCM) tongue diagnosis, while clinically valuable, faces standardization challenges due to subjective interpretation and inconsistent imaging protocols, compounded by the lack of large-scale, annotated datasets for AI development. To address this gap, we present the first specialized dataset for AI-driven TCM tongue diagnosis, comprising 6,719 high-quality images captured under standardized conditions and annotated with 20 pathological symptom categories (averaging …

Survey of GenAI for Automotive Software Development: From Requirements to Executable Code
Nenad Petrovic, Vahid Zolfaghari, Andre Schamschurko, Sven Kirchner, Fengjunjie Pan, Chengdng Wu, Nils Purschke, Aleksei Velsh, Krzysztof Lebioda, Yinglei Song, Yi Zhang, Lukasz Mazur, Alois Knoll
https://arxiv.org/abs/2507.15025

Survey of GenAI for Automotive Software Development: From Requirements to Executable Code
Adoption of state-of-art Generative Artificial Intelligence (GenAI) aims to revolutionize many industrial areas by reducing the amount of human intervention needed and effort for handling complex underlying processes. Automotive software development is considered to be a significant area for GenAI adoption, taking into account lengthy and expensive procedures, resulting from the amount of requirements and strict standardization. In this paper, we explore the adoption of GenAI for various steps …

Leveraging Large Language Models for Accurate Sign Language Translation in Low-Resource Scenarios
Luana Bulla, Gabriele Tuccio, Misael Mongiov\`i, Aldo Gangemi
https://arxiv.org/abs/2508.18183

Leveraging Large Language Models for Accurate Sign Language Translation in Low-Resource Scenarios
Translating natural languages into sign languages is a highly complex and underexplored task. Despite growing interest in accessibility and inclusivity, the development of robust translation systems remains hindered by the limited availability of parallel corpora which align natural language with sign language data. Existing methods often struggle to generalize in these data-scarce environments, as the few datasets available are typically domain-specific, lack standardization, or fail to captur…

Lightweight Gradient Descent Optimization for Mitigating Hardware Imperfections in RIS Systems
Pedro H. C. de Souza (National Institute of Telecommunications), Luiz A. M. Pereira (National Institute of Telecommunications), Faustino R. G\'omez (National Institute of Telecommunications), Elsa M. Mater\'on (National Institute of Telecommunications), Jorge Ricardo Mej\'ia-Salazar (National Institute of Telecommunications)

Lightweight Gradient Descent Optimization for Mitigating Hardware Imperfections in RIS Systems
Ongoing discussions about the future of wireless communications are reaching a turning point as standardization activities for the sixth generation of mobile networks (6G) become more mature. New technologies must now face renewed scrutiny by the industry and academia in order to be ready for deployment in the near future. Recently, reconfigurable intelligent surfaces (RISs) gained attention as a promising solution for improving the propagation conditions of signal transmission in general. The …

White paper: Towards Human-centric and Sustainable 6G Services -- the fortiss Research Perspective
Rute C. Sofia, Hao Shen, Yuanting Liu, Severin Kacianka, Holger Pfeifer
https://arxiv.org/abs/2507.14209

White paper: Towards Human-centric and Sustainable 6G Services -- the fortiss Research Perspective
As a leading research institute in software-intensive systems, fortiss is actively shaping the vision of Sixth Generation Mobile Communication (6G). Our mission is to ensure that 6G technologies go beyond technical advancements and are aligned with societal needs. fortiss plays a key role in 6G initiatives worldwide, including contributions to standardization bodies and collaborative Research and Development programs. We focus on software-defined, AI-enabled, and sustainable communication servi…