Papers
Research papers from arXiv and related sources
A Closed-Loop CPR Training Glove with Integrated Tactile Sensing and Haptic Feedback
Cardiopulmonary resuscitation (CPR) is a critical life-saving procedure, and effective training benefits from self-directed practice beyond instructor-led sessions. In this paper, we propose a clos...
Jaeyoung Moon, Mingzhuo Ma, Qifeng Yang, Youjin Choi, Seokhyun Hwang, Samuel Burden, Kyung-Joong ...
Task-Level Decisions to Gait Level Control: A Hierarchical Policy Approach for Quadruped Navigation
Real-world quadruped navigation is constrained by a scale mismatch between high-level navigation decisions and low-level gait execution, as well as by instabilities under out-of-distribution enviro...
Sijia Li, Haoyu Wang, Shenghai Yuan, Yizhuo Yang, Thien-Minh Nguyen
CodeScout: Contextual Problem Statement Enhancement for Software Agents
Current AI-powered code assistance tools often struggle with poorly-defined problem statements that lack sufficient task context and requirements specification. Recent analysis of software engineer...
Manan Suri, Xiangci Li, Mehdi Shojaie, Songyang Han, Chao-Chun Hsu, Shweta Garg, Aniket Anand Des...
Agentic AI -- Physicist Collaboration in Experimental Particle Physics: A Proof-of-Concept Measurement with LEP Open Data
We present an AI agentic measurement of the thrust distribution in $e^{+}e^{-}$ collisions at $\sqrt{s}=91.2$~GeV using archived ALEPH data. The analysis and all note writing is carried out entirel...
Anthony Badea, Yi Chen, Yen-Jie Lee
State-Selective Signatures of Quantum and Classical Gravitational Environments
A unified framework is developed for determining whether a gravitational-wave (GW) background behaves as a classical field or as a genuinely quantum environment. Unified here means that both descri...
Partha Nandi, Sankarshan Sahu, Bibhas Ranjan Majhi, Francesco Petruccione
Neural operator transformers capture bifurcating drift wave turbulence in fusion plasma simulations
Self-consistent modeling of turbulence-driven transport is critical for optimizing confinement in magnetically confined fusion plasmas, such as in tokamaks and stellarators. In particular, capturin...
Johannes J. van de Wetering, Ben Zhu
Challenges and Design Considerations for Finding CUDA Bugs Through GPU-Native Fuzzing
Modern computing is shifting from homogeneous CPU-centric systems to heterogeneous systems with closely integrated CPUs and GPUs. While the CPU software stack has benefited from decades of memory s...
Mingkai Li, Joseph Devietti, Suman Jana, Tanvir Ahmed Khan
Electrical Power Network Modeling Framework for Wildfire Risk and Resilience Analysis
The increasing intensity and frequency of wildfires are causing significant economic and societal impacts on communities through direct effects on the built environment, particularly critical infra...
Richard Campos, Erica Fischer, Eduardo Cotilla-Sanchez
Unsupervised domain adaptation for radioisotope identification in gamma spectroscopy
Training machine learning models for radioisotope identification using gamma spectroscopy remains an elusive challenge for many practical applications, largely stemming from the difficulty of acqui...
Peter Lalor, Ayush Panigrahy, Alex Hagen
Effects of 3D printed capsule material on activation thin foil irradiation and counting for fusion neutron yield measurements
Activation foils are used to independently measure the time integrated neutron yield and total fusion energy produced in both inertial and magnetic confinement fusion, making them crucial in the ne...
D. Lobelo, E. Panontin, X. Wang, P. Raj, I. Holmes, R. A. Tinguely
Determination of the Height-Temperature Profile Above a Solar Active Region from Multi-Frequency Radio Observations
An iterative method is presented for reconstructing the height-temperature profile of the solar atmosphere above a sunspot using multi-frequency spectro-polarimetric microwave observations. It is a...
T. I. Kaltman, A. G. Stupishin, G. A. Makoev
Non-intrusive Monitoring of Sealed Microreactor Cores Using Physics-Informed Muon Scattering Tomography With Momentum Measurements
Next-generation microreactors enable remote deployment and semi-autonomous operation, but compact, sealed, heterogeneous cores limit conventional safeguard approaches that rely on access and bulk a...
Reshma Ughade, Stylianos Chatzidakis
Reasoning Models Struggle to Control their Chains of Thought
Chain-of-thought (CoT) monitoring is a promising tool for detecting misbehaviors and understanding the motivations of modern reasoning models. However, if models can control what they verbalize in ...
Chen Yueh-Han, Robert McCarthy, Bruce W. Lee, He He, Ian Kivlichan, Bowen Baker, Micah Carroll, T...
Towards Robust Retrieval-Augmented Generation Based on Knowledge Graph: A Comparative Analysis
Retrieval-Augmented Generation (RAG) was introduced to enhance the capabilities of Large Language Models (LLMs) beyond their encoded prior knowledge. This is achieved by providing LLMs with an exte...
Hazem Amamou, Stéphane Gagnon, Alan Davoust, Anderson R. Avila
Warm Starting State-Space Models with Automata Learning
We prove that Moore machines can be exactly realized as state-space models (SSMs), establishing a formal correspondence between symbolic automata and these continuous machine learning architectures...
William Fishell, Sam Nicholas Kouteili, Mark Santolucito
Longitudinal Lesion Inpainting in Brain MRI via 3D Region Aware Diffusion
Accurate longitudinal analysis of brain MRI is often hindered by evolving lesions, which bias automated neuroimaging pipelines. While deep generative models have shown promise in inpainting these l...
Zahra Karimaghaloo, Dumitru Fetco, Haz-Edine Assemlal, Hassan Rivaz, Douglas L. Arnold
Improved Scaling Laws via Weak-to-Strong Generalization in Random Feature Ridge Regression
It is increasingly common in machine learning to use learned models to label data and then employ such data to train more capable models. The phenomenon of weak-to-strong generalization exemplifies...
Diyuan Wu, Lehan Chen, Theodor Misiakiewicz, Marco Mondelli
SecureRAG-RTL: A Retrieval-Augmented, Multi-Agent, Zero-Shot LLM-Driven Framework for Hardware Vulnerability Detection
Large language models (LLMs) have shown remarkable capabilities in natural language processing tasks, yet their application in hardware security verification remains limited due to scarcity of publ...
Touseef Hasan, Blessing Airehenbuwa, Nitin Pundir, Souvika Sarkar, Ujjwal Guin
Order Unit Spaces and Probabilistic Models
We exhibit a functor from the category OUS of order unit spaces and positive, unit-preserving mappings into the category $\Prob$ of probabilistic models (test spaces with designated state spaces) a...
John Harding, Alex Wilce
Scalable Digital Compute-in-Memory Ising Machines for Robustness Verification of Binary Neural Networks
Verification of binary neural network (BNN) robustness is NP-hard, as it can be formulated as a combinatorial search for an adversarial perturbation that induces misclassification. Exact verificati...
Madhav Vadlamani, Rahul Singh, Yuyao Kong, Zheng Zhang, Shimeng Yu