Papers
Research papers from arXiv and related sources
Constraints on Axion-Photon Mixing from Fast Radio Burst Dispersion Measures
Fast radio bursts (FRBs) offer a powerful probe of the ionized Universe through their dispersion measures (DM). While a significant fraction of the DM arises from the intergalactic medium (IGM), th...
Gunalan Muthusami, Gopal Kashyap
Exploring the Viability of Fisher Discriminants in Galaxy Morphology Classification
One of the major challenges in astronomy involves accurately classifying galaxies, particularly distinguishing between different galaxy types. While many complex algorithms have shown strong perfor...
Sazatul Nadhilah Zakaria, Santtosh Muniyandy, John Y. H. Soo
A Hybrid Neural-Assisted Unscented Kalman Filter for Unmanned Ground Vehicle Navigation
Modern autonomous navigation for unmanned ground vehicles relies on different estimators to fuse inertial sensors and GNSS measurements. However, the constant noise covariance matrices often strugg...
Gal Versano, Itzik Klein
Beyond BFS: A Comparative Study of Rooted Spanning Tree Algorithms on GPUs
Rooted spanning trees (RSTs) are a core primitive in parallel graph analytics, underpinning algorithms such as biconnected components and planarity testing. On GPUs, RST construction has traditiona...
Abhijeet Sahu, Srikar Vilas Donur
Chunk-Boundary Artifact in Action-Chunked Generative Policies: A Noise-Sensitive Failure Mechanism
Action chunking has become a central design choice for generative visuomotor policies, yet the execution discontinuities that arise at chunk boundaries remain poorly understood. In a frozen pretrai...
Rui Wang
Taming OpenClaw: Security Analysis and Mitigation of Autonomous LLM Agent Threats
Autonomous Large Language Model (LLM) agents, exemplified by OpenClaw, demonstrate remarkable capabilities in executing complex, long-horizon tasks. However, their tightly coupled instant-messaging...
Xinhao Deng, Yixiang Zhang, Jiaqing Wu, Jiaqi Bai, Sibo Yi, Zhuoheng Zou, Yue Xiao, Rennai Qiu, J...
Quantitative 3D imaging of highly distorted micro-crystals using Bragg ptychography
Bragg coherent diffraction imaging (BCDI) fails to reliably retrieve phases in micro-crystals exhibiting strong strain inhomogeneities, which restricts its applicability. Here we show that three-di...
Peng Li, David Yang, Christoph Rau, Marc Allain, Felix Hofmann, Virginie Chamard
Quantum Error Correction by Purification
We present a general-purpose quantum error correction primitive based on state purification via the SWAP test, which we refer to as purification quantum error correction (PQEC). This method operate...
Jonathan Raghoonanan, Tim Byrnes
AI Knows What's Wrong But Cannot Fix It: Helicoid Dynamics in Frontier LLMs Under High-Stakes Decisions
Large language models perform reliably when their outputs can be checked: solving equations, writing code, retrieving facts. They perform differently when checking is impossible, as when a clinicia...
Alejandro R Jadad
ReHARK: Refined Hybrid Adaptive RBF Kernels for Robust One-Shot Vision-Language Adaptation
The adaptation of large-scale Vision-Language Models (VLMs) like CLIP to downstream tasks with extremely limited data -- specifically in the one-shot regime -- is often hindered by a significant "S...
Md Jahidul Islam
Standard Condition Number-Based Detection for MIMO ISAC Systems under Noise Uncertainty
This paper presents a unified analytical and optimization framework for Standard Condition Number (SCN)-based detection in MIMO Integrated Sensing and Communication (ISAC) systems operating under n...
Alex Obando, Tharindu Udupitiya, Saman Atapattu, Kandeepan Sithamparanathan
Multi-Agent Collaboration for Automated Design Exploration on High Performance Computing Systems
Today's scientific challenges, from climate modeling to Inertial Confinement Fusion design to novel material design, require exploring huge design spaces. In order to enable high-impact scientific ...
Harshitha Menon, Charles F. Jekel, Kevin Korner, Brian Gunnarson, Nathan K. Brown, Michael Stees,...
Gen-Fab: A Variation-Aware Generative Model for Predicting Fabrication Variations in Nanophotonic Devices
Silicon photonic devices often exhibit fabrication-induced variations such as over-etching, underetching, and corner rounding, which can significantly alter device performance. These variations are...
Rambod Azimi, Yuri Grinberg, Dan-Xia Xu, Odile Liboiron-Ladouceur
Spherically-symmetrical vacuum solution in Freund-Nambu scalar-tensor gravity
Scalar--tensor theories of gravity provide a natural extension of general relativity and may predict naked singularities as alternative compact objects. In this work, we investigate a novel exact s...
Akbar Davlataliev, Bobur Turimov, Bobomurat Ahmedov, Yuri Vyblyi, Chengxun Yuan, Chen Zhou
Variance Estimation with Dependence and Heterogeneous Means
This paper considers the problem of estimating the variance of a sum of a triangular array of random vectors with heterogeneous means. When random vectors exhibit two-way cluster dependence or weak...
Luther Yap
SPEGC: Continual Test-Time Adaptation via Semantic-Prompt-Enhanced Graph Clustering for Medical Image Segmentation
In medical image segmentation tasks, the domain gap caused by the difference in data collection between training and testing data seriously hinders the deployment of pre-trained models in clinical ...
Xiaogang Du, Jiawei Zhang, Tongfei Liu, Tao Lei, Yingbo Wang
AutoVeriFix+: High-Correctness RTL Generation via Trace-Aware Causal Fix and Semantic Redundancy Pruning
Large language models (LLMs) have demonstrated impressive capabilities in generating software code for high-level programming languages such as Python and C++. However, their application to hardwar...
Yan Tan, Xiangchen Meng, Zijun Jiang, Yangdi Lyu
Quantized Inference for OneRec-V2
Quantized inference has demonstrated substantial system-level benefits in large language models while preserving model quality. In contrast, reliably applying low-precision quantization to recommen...
Yi Su, Xinchen Luo, Hongtao Cheng, Ziteng Shu, Yunfeng Zhao, Fangyu Zhang, Jiaqiang Liu, Xiao Lia...
Graph Generation Methods under Partial Information
We study the problem of generating graphs with prescribed degree sequences for bipartite, directed, and undirected networks. We first propose a sequential method for bipartite graph generation and ...
Tong Sun, Jianshu Hao, Michael C. Fu, Guangxin Jiang
Leveraging Phytolith Research using Artificial Intelligence
Phytolith analysis is a crucial tool for reconstructing past vegetation and human activities, but traditional methods are severely limited by labour-intensive, time-consuming manual microscopy. To ...
Andrés G. Mejía Ramón, Kate Dudgeon, Nina Witteveen, Dolores Piperno, Michael Kloster, Luigi Palo...