Tootfinder

An Explainable Emotion Alignment Framework for LLM-Empowered Agent in Metaverse Service Ecosystem
Qun Ma, Xiao Xue, Ming Zhang, Yifan Shen, Zihan Zhao
https://arxiv.org/abs/2507.22326

An Explainable Emotion Alignment Framework for LLM-Empowered Agent in Metaverse Service Ecosystem
Metaverse service is a product of the convergence between Metaverse and service systems, designed to address service-related challenges concerning digital avatars, digital twins, and digital natives within Metaverse. With the rise of large language models (LLMs), agents now play a pivotal role in Metaverse service ecosystem, serving dual functions: as digital avatars representing users in the virtual realm and as service assistants (or NPCs) providing personalized support. However, during the m…

Generative Recommendation with Semantic IDs: A Practitioner's Handbook
Clark Mingxuan Ju, Liam Collins, Leonardo Neves, Bhuvesh Kumar, Louis Yufeng Wang, Tong Zhao, Neil Shah
https://arxiv.org/abs/2507.22224

Generative Recommendation with Semantic IDs: A Practitioner's Handbook
Generative recommendation (GR) has gained increasing attention for its promising performance compared to traditional models. A key factor contributing to the success of GR is the semantic ID (SID), which converts continuous semantic representations (e.g., from large language models) into discrete ID sequences. This enables GR models with SIDs to both incorporate semantic information and learn collaborative filtering signals, while retaining the benefits of discrete decoding. However, varied mod…

Tunable Valley Polarization and Anomalous Hall Effect in Ferrovalley NbX2 and TaX2 (X = S, Se, Te): A First-Principles Study
Samiul Islam, Sharif Mohammad Mominuzzaman, Ahmed Zubair
https://arxiv.org/abs/2508.17240

Tunable Valley Polarization and Anomalous Hall Effect in Ferrovalley NbX2 and TaX2 (X = S, Se, Te): A First-Principles Study
Two-dimensional transition metal dichalcogenides lack inversion symmetry and have broken time-reversal symmetry due to the honeycomb structure and intrinsic ferromagnetism, which leads to their valley polarization. Here, we explored the electronic and magnetic properties of the novel ferrovalley materials 1H-NbS2, 1H-NbSe2, 1H-NbTe2, 1H-TaS2, 1H-TaSe2, and 1H-TaTe2 using first-principles calculations based on density functional theory. The materials are dynamically stable bipolar magnetic semic…

A Step-by-step Guide on Nonlinear Model Predictive Control for Safe Mobile Robot Navigation
Dennis Benders, Laura Ferranti, Johannes K\"ohler
https://arxiv.org/abs/2507.17856

A Step-by-step Guide on Nonlinear Model Predictive Control for Safe Mobile Robot Navigation
Designing a Model Predictive Control (MPC) scheme that enables a mobile robot to safely navigate through an obstacle-filled environment is a complicated yet essential task in robotics. In this technical report, safety refers to ensuring that the robot respects state and input constraints while avoiding collisions with obstacles despite the presence of disturbances and measurement noise. This report offers a step-by-step approach to implementing Nonlinear Model Predictive Control (NMPC) schemes …

Learning to See Through Flare
Xiaopeng Peng, Heath Gemar, Erin Fleet, Kyle Novak, Abbie Watnik, Grover Swartzlander
https://arxiv.org/abs/2508.13907 https://

Learning to See Through Flare
Machine vision systems are susceptible to laser flare, where unwanted intense laser illumination blinds and distorts its perception of the environment through oversaturation or permanent damage to sensor pixels. We introduce NeuSee, the first computational imaging framework for high-fidelity sensor protection across the full visible spectrum. It jointly learns a neural representation of a diffractive optical element (DOE) and a frequency-space Mamba-GAN network for image restoration. NeuSee sys…

Neutrino Telescope Event Classification on Quantum Computers
Pablo Rodriguez-Grasa, Pavel Zhelnin, Carlos A. Arg\"uelles, Mikel Sanz
https://arxiv.org/abs/2506.16530

Neutrino Telescope Event Classification on Quantum Computers
Quantum computers represent a new computational paradigm with steadily improving hardware capabilities. In this article, we present the first study exploring how current quantum computers can be used to classify different neutrino event types observed in neutrino telescopes. We investigate two quantum machine learning approaches, Neural Projected Quantum Kernels (NPQKs) and Quantum Convolutional Neural Networks (QCNNs), and find that both achieve classification performance comparable to classic…

Capturing and Sharing Know-How through Visual Process Representations: A Human-Centred Approach to Teacher Workflows
Gloria Fern\'andez-Nieto, Vanessa Echeverria, Yuheng Li, Yi-Shan Tsai, Lele Sha, Guanliang Chen, Dragan Gasevic, Zachari Swiecki
https://arxiv.org/abs/2508.04357

Capturing and Sharing Know-How through Visual Process Representations: A Human-Centred Approach to Teacher Workflows
Knowledge Management is crucial for capturing and transferring expertise within universities, especially in high staff turnover contexts where expertise loss disrupts teaching. Documenting teachers' workflows is time-intensive and diverts experts from core responsibilities. Sequential Pattern Mining (SPM) leverages log data to identify expert workflows, offering an automated alternative to represent workflows but requiring transformation into intuitive formats for novice educators. This paper i…

Las nubes y la probabilidad de tormentas nos han fastidiado la salida para ver las perseidas; pero hay que buscar siempre el lado positivo de las cosas, refresca, es muy probable que llueva y puedo seguir leyendo Última salida para Brooklyn.

VLM-Empowered Multi-Mode System for Efficient and Safe Planetary Navigation
Sinuo Cheng, Ruyi Zhou, Wenhao Feng, Huaiguang Yang, Haibo Gao, Zongquan Deng, Liang Ding
https://arxiv.org/abs/2506.16703

VLM-Empowered Multi-Mode System for Efficient and Safe Planetary Navigation
The increasingly complex and diverse planetary exploration environment requires more adaptable and flexible rover navigation strategy. In this study, we propose a VLM-empowered multi-mode system to achieve efficient while safe autonomous navigation for planetary rovers. Vision-Language Model (VLM) is used to parse scene information by image inputs to achieve a human-level understanding of terrain complexity. Based on the complexity classification, the system switches to the most suitable naviga…

Navigating High-Dimensional Backstage: A Guide for Exploring Literature for the Reliable Use of Dimensionality Reduction
Hyeon Jeon, Hyunwook Lee, Yun-Hsin Kuo, Taehyun Yang, Daniel Archambault, Sungahn Ko, Takanori Fujiwara, Kwan-Liu Ma, Jinwook Seo
https://arxiv.org/abs/2506.14820

Navigating High-Dimensional Backstage: A Guide for Exploring Literature for the Reliable Use of Dimensionality Reduction
Visual analytics using dimensionality reduction (DR) can easily be unreliable for various reasons, e.g., inherent distortions in representing the original data. The literature has thus proposed a wide range of methodologies to make DR-based visual analytics reliable. However, the diversity and extensiveness of the literature can leave novice analysts and researchers uncertain about where to begin and proceed. To address this problem, we propose a guide for reading papers for reliable visual ana…