Papers
Research papers from arXiv and related sources
Quantum Feedback Cooling without State Filtering
We introduce a state-based feedback law that stabilizes quantum states or subspaces associated with extremal values of a continuously monitored observable - a problem motivated by quantum cooling t...
Lorenzo Franceschetti, Francesco Ticozzi
OralGPT-Plus: Learning to Use Visual Tools via Reinforcement Learning for Panoramic X-ray Analysis
Panoramic dental radiographs require fine-grained spatial reasoning, bilateral symmetry understanding, and multi-step diagnostic verification, yet existing vision-language models operate under a st...
Yuxuan Fan, Jing Hao, Hong Chen, Jiahao Bao, Yihua Shao, Yuci Liang, Kuo Feng Hung, Hao Tang
ESAA-Security: An Event-Sourced, Verifiable Architecture for Agent-Assisted Security Audits of AI-Generated Code
AI-assisted software generation has increased development speed, but it has also amplified a persistent engineering problem: systems that are functionally correct may still be structurally insecure...
Elzo Brito dos Santos Filho
CLAIRE: Compressed Latent Autoencoder for Industrial Representation and Evaluation -- A Deep Learning Framework for Smart Manufacturing
Accurate fault detection in high-dimensional industrial environments remains a major challenge due to the inherent complexity, noise, and redundancy in sensor data. This paper introduces CLAIRE, i....
Mohammadhossein Ghahramani, Mengchu Zhou
A Scalable Benchmark for Repository-Oriented Long-Horizon Conversational Context Management
In recent years, large language models (LLMs) have advanced rapidly, substantially enhancing their code understanding and generation capabilities and giving rise to powerful code assistants. Howeve...
Yang Liu, Li Zhang, Fang Liu, Ping Lin, Xinyi Li
MoEless: Efficient MoE LLM Serving via Serverless Computing
Large Language Models (LLMs) have become a cornerstone of AI, driving progress across diverse domains such as content creation, search and recommendation systems, and AI-assisted workflows. To alle...
Hanfei Yu, Bei Ouyang, Shwai He, Ang Li, Hao Wang
Transparent AI for Mathematics: Transformer-Based Large Language Models for Mathematical Entity Relationship Extraction with XAI
Mathematical text understanding is a challenging task due to the presence of specialized entities and complex relationships between them. This study formulates mathematical problem interpretation a...
Tanjim Taharat Aurpa
Open-Source Based and ETSI Compliant Cooperative, Connected, and Automated Mini-Cars
The automotive sector is following a revolutionary path from vehicles controlled by humans to vehicles that will be fully automated, fully connected, and ultimately fully cooperative. Along this ro...
Lorenzo Farina, Federico Gavioli, Salvatore Iandolo, Francesco Moretti, Giuseppe Perrone, Matteo ...
How students use generative AI for computational modeling in physics
Generative artificial intelligence (genAI) is becoming increasingly prevalent and capable in physics, particularly for programming-related tasks. How, then, does genAI affect students' computationa...
Karl Henrik Fredly, Tor Ole Odden, Benjamin M. Zwickl
AI End-to-End Radiation Treatment Planning Under One Second
Artificial intelligence-based radiation therapy (RT) planning has the potential to reduce planning time and inter-planner variability, improving efficiency and consistency in clinical workflows. Mo...
Simon Arberet, Riqiang Gao, Martin Kraus, Florin C. Ghesu, Wilko Verbakel, Mamadou Diallo, Anthon...
SAHOO: Safeguarded Alignment for High-Order Optimization Objectives in Recursive Self-Improvement
Recursive self-improvement is moving from theory to practice: modern systems can critique, revise, and evaluate their own outputs, yet iterative self-modification risks subtle alignment drift. We i...
Subramanyam Sahoo, Aman Chadha, Vinija Jain, Divya Chaudhary
Structured Exploration vs. Generative Flexibility: A Field Study Comparing Bandit and LLM Architectures for Personalised Health Behaviour Interventions
Behaviour Change Techniques (BCTs) are central to digital health interventions, yet selecting and delivering effective techniques remains challenging. Contextual bandits enable statistically ground...
Dominik P. Hofer, Haochen Song, Rania Islambouli, Laura Hawkins, Ananya Bhattacharjee, Meredith F...
Variable selection in linear mixed model meta-regression with suspected interaction effects -- How can tree-based methods help?
Detecting interaction effects (IEs) in meta-regression is challenging, especially when few studies are available and many plausible interactions are considered. In many meta-analyses, interpretabil...
Jan-Bernd Igelmann, Paula Lorenz, Markus Pauly
Classification of Autistic and Non-Autistic Children's Speech: A Cross-Linguistic Study in Finnish, French, and Slovak
We present a cross-linguistic study of speech in autistic and non-autistic children speaking Finnish, French, and Slovak. We combine supervised classification with within-language and cross-corpus ...
Sofoklis Kakouros, Ida-Lotta Myllylä
The Art That Poses Back: Assessing AI Pastiches after Contemporary Artworks
This study explores artificial visual creativity, focusing on ChatGPT's ability to generate new images intentionally pastiching original artworks such as paintings, drawings, sculptures and install...
Anca Dinu, Andreiana Mihail, Andra-Maria Florescu, Claudiu Creanga
From Entropy to Calibrated Uncertainty: Training Language Models to Reason About Uncertainty
Large Language Models (LLMs) that can express interpretable and calibrated uncertainty are crucial in high-stakes domains. While methods to compute uncertainty post-hoc exist, they are often sampli...
Azza Jenane, Nassim Walha, Lukas Kuhn, Florian Buettner
A Generalized Feature Model for Digital Twins
The adoption of Digital Twin technologies is rapidly expanding in diverse industrial, economic, and societal domains. Over the past decade, a multitude of studies, surveys, and investigations have ...
Philipp Zech, Yanis Mair, Michael Vierhauser, Pablo Oliveira Antonino, Frank Schnicke, Tony Clark
The EpisTwin: A Knowledge Graph-Grounded Neuro-Symbolic Architecture for Personal AI
Personal Artificial Intelligence is currently hindered by the fragmentation of user data across isolated silos. While Retrieval-Augmented Generation offers a partial remedy, its reliance on unstruc...
Giovanni Servedio, Potito Aghilar, Alessio Mattiace, Gianni Carmosino, Francesco Musicco, Gabriel...
Learning Where the Physics Is: Probabilistic Adaptive Sampling for Stiff PDEs
Modeling stiff partial differential equations (PDEs) with sharp gradients remains a significant challenge for scientific machine learning. While Physics-Informed Neural Networks (PINNs) struggle wi...
Akshay Govind Srinivasan, Balaji Srinivasan
SuperSuit: An Isomorphic Bimodal Interface for Scalable Mobile Manipulation
High-quality, long-horizon demonstrations are essential for embodied AI, yet acquiring such data for tightly coupled wheeled mobile manipulators remains a fundamental bottleneck. Unlike fixed-base ...
Tongqing Chen, Hang Wu, Jiasen Wang, Xiaotao Li, Zhu Jin, Lu Fang