arXiv:2602.20175v1 Announce Type: new Abstract: We present an application of the tensor network generator-enhanced optimization (TN-GEO) framework to address the traveling salesman problem (TSP), a fundamental combinatorial optimization challenge. Our approach employs a tensor network Born machine based on automatically differentiable matrix product states (MPS) as the generative model, using the Born rule to define probability distributions over candidate solutions. Unlike approaches based on binary encoding, which require $N^2$ variables and penalty terms to enforce valid tour constraints, […]

Ver mais

arXiv:2604.06200v1 Announce Type: new Abstract: Designing project-based learning (PBL) demands managing highly interdependent components, a task that both traditional linear tools and purely conversational AI struggle with. Traditional tools fail to capture the non-linear nature of creative design, while conversational systems lack the persistent, shared context necessary for reflective collaboration. Grounded in theories of distributed cognition, we introduce CoMAP, a system that embodies a graph-based collaboration paradigm. By providing a shared visual workspace with dual-modality AI support, CoMAP […]

Ver mais

arXiv:2602.20202v1 Announce Type: new Abstract: The growing reliance on AI-identified digital evidence raises significant concerns about its reliability, particularly as large language models (LLMs) are increasingly integrated into forensic investigations. This paper proposes a structured framework that automates forensic artifact extraction, refines data through LLM-driven analysis, and validates results using a Digital Forensic Knowledge Graph (DFKG). Evaluated on a 13 GB forensic image dataset containing 61 applications, 2,864 databases, and 5,870 tables, the framework ensures artifact traceability and […]

Ver mais

arXiv:2603.28774v1 Announce Type: new Abstract: This demo introduces Focus360, a system designed to enhance user engagement in 360{deg} VR videos by guiding attention to key elements within the scene. Using natural language descriptions, the system identifies important elements and applies a combination of visual effects to guide attention seamlessly. At the demonstration venue, participants can experience a 360{deg} Safari Tour, showcasing the system’s ability to improve user focus while maintaining an immersive experience.

Ver mais

This study aims to develop and improve machine learning-based post-processing models for precipitation, temperature, and wind speed predictions using the Mesoscale Model (MSM) dataset provided by the Japan Meteorological Agency (JMA) for 18 locations across Japan, including plains, mountainous regions, and islands. By incorporating meteorological variables from grid points surrounding the target locations as input features and applying feature selection based on correlation analysis, we found that, in our experimental setting, the LightGBM-based models achieved lower RMSE than […]

Ver mais

arXiv:2601.12213v1 Announce Type: cross Abstract: Matrix completion is a classical problem that has received recurring interest across a wide range of fields. In this paper, we revisit this problem in an ultra-sparse sampling regime, where each entry of an unknown, $ntimes d$ matrix $M$ (with $n ge d$) is observed independently with probability $p = C / d$, for a fixed integer $C ge 2$. This setting is motivated by applications involving large, sparse panel datasets, where the […]

Ver mais

Large language models (LLMs) represent a cutting-edge breakthrough in the deep learning models designed for processing human languages. This study created a local LLM that used Book Four of the Civil Code of Catalonia relating to Successions and the regulations of the Notary Profession of Spain for summarization and answering questions in a context of increased security. The model summarized and replied to specific questions in a reasonable manner but was not absent of information loss and contextual […]

Ver mais