Papers
Research papers from arXiv and related sources
Grounded String Representations of Series-Parallel Graphs without Transitive Edges
In a {\em grounded string representation} of a graph there is a horizontal line $\ell$ and each vertex is represented as a simple curve below $\ell$ with one end point on $\ell$ such that two curve...
Sabine Cornelsen, Jan Kratochvíl, Miriam Münch, Giacomo Ortali, Alexandra Weinberger, Alexander W...
Charging power enhancement at the phase transition of a non-integrable quantum battery
Exploiting many-body interaction and critical phenomena to improve the performance of quantum batteries is an emerging and promising line of research. A central question in this direction is whethe...
D. Farina, M. Sassetti, V. Cataudella, D. Ferraro, N. Traverso Ziani
Merged amplitude encoding for Chebyshev quantum Kolmogorov--Arnold networks: trading qubits for circuit executions
Quantum Kolmogorov--Arnold networks based on Chebyshev polynomials (CCQKAN) evaluate each edge activation function as a quantum inner product, creating a trade-off between qubit count and the numbe...
Hikaru Wakaura
Single-star optical turbulence profiling techniques for the SHIMM and other Shack-Hartmann instruments
Atmospheric optical turbulence (OT) monitoring is crucial for site characterisation at astronomical observatories and optical communications ground stations. The Shack-Hartmann Image Motion Monitor...
Ryan Griffiths, Timothy Butterley, Richard Wilson, James Osborn
The Price of Robustness: Stable Classifiers Need Overparameterization
The relationship between overparameterization, stability, and generalization remains incompletely understood in the setting of discontinuous classifiers. We address this gap by establishing a gener...
Jonas von Berg, Adalbert Fono, Massimiliano Datres, Sohir Maskey, Gitta Kutyniok
Designing UNICORN: a Unified Benchmark for Imaging in Computational Pathology, Radiology, and Natural Language
Medical foundation models show promise to learn broadly generalizable features from large, diverse datasets. This could be the base for reliable cross-modality generalization and rapid adaptation t...
Michelle Stegeman, Lena Philipp, Fennie van der Graaf, Marina D'Amato, Clément Grisi, Luc Builtje...
Agentified Assessment of Logical Reasoning Agents
We present a framework for evaluating and benchmarking logical reasoning agents when assessment itself must be reproducible, auditable, and robust to execution failures. Building on agentified asse...
Zhiyu Ni, Yifeng Xiao, Zheng Liang
Two-stage Convolutional Neural Network for six-dimensional phase space reconstruction
In particle accelerators, full knowledge of the six-dimensional (6D) beam phase space is crucial but difficult to obtain with conventional beam diagnostics. We develop a two-stage convolutional neu...
Sayantan Mukherjee, Masao Kuriki, Zachary John Liptak, Hitoshi Hayano, Masakazu Kurata, Nobuhiro ...
Single Microphone Own Voice Detection based on Simulated Transfer Functions for Hearing Aids
This paper presents a simulation-based approach to own voice detection (OVD) in hearing aids using a single microphone. While OVD can significantly improve user comfort and speech intelligibility, ...
Mathuranathan Mayuravaani, W. Bastiaan Kleijn, Andrew Lensen, Charlotte Sørensen
Decoupling Intrinsic Molecular Efficacy from Platform Effects: An Interpretable Machine Learning Framework for Unbiased Perovskite Passivator Discovery
Rational design of interface passivators for perovskite solar cells is hindered by the entanglement of intrinsic molecular efficacy with extrinsic platform-dependent performance - a confounding fac...
Jing Zhang, Ziyuan Li, Shan Gao, Zhen Zhu, Jing Wang, Xiangmei Duan
Exact Moment Estimation of Stochastic Differential Dynamics
Moment estimation for stochastic differential equations (SDEs) is fundamental to the formal reasoning and verification of stochastic dynamical systems, yet remains challenging and is rarely availab...
Shenghua Feng, Jie An, Naijun Zhan, Fanjiang Xu
VisionCreator: A Native Visual-Generation Agentic Model with Understanding, Thinking, Planning and Creation
Visual content creation tasks demand a nuanced understanding of design conventions and creative workflows-capabilities challenging for general models, while workflow-based agents lack specialized k...
Jinxiang Lai, Zexin Lu, Jiajun He, Rongwei Quan, Wenzhe Zhao, Qinyu Yang, Qi Chen, Qin Lin, Chuyu...
Quantum Algorithms for Approximate Graph Isomorphism Testing
The graph isomorphism problem asks whether two graphs are identical up to vertex relabeling. While the exact problem admits quasi-polynomial-time classical algorithms, many applications in molecula...
Prateek P. Kulkarni
Improving Diffusion Planners by Self-Supervised Action Gating with Energies
Diffusion planners are a strong approach for offline reinforcement learning, but they can fail when value-guided selection favours trajectories that score well yet are locally inconsistent with the...
Yuan Lu, Dongqi Han, Yansen Wang, Dongsheng Li
Rethinking Training Targets, Architectures and Data Quality for Universal Speech Enhancement
Universal Speech Enhancement (USE) aims to restore speech quality under diverse degradation conditions while preserving signal fidelity. Despite recent progress, key challenges in training target s...
Szu-Wei Fu, Rong Chao, Xuesong Yang, Sung-Feng Huang, Ryandhimas E. Zezario, Rauf Nasretdinov, An...
The Vienna 4G/5G Drive-Test Dataset
Machine learning for mobile network analysis, planning, and optimization is often limited by the lack of large, comprehensive real-world datasets. This paper introduces the Vienna 4G/5G Drive-Test ...
Wilfried Wiedner, Lukas Eller, Mariam Mussbah, Dominik Rössler, Valerian Maresch, Philipp Svoboda...
Topological bounds on the dynamical growth rate of chemical reaction networks
Growth and decay are system-level properties of chemical reaction networks (CRNs) relevant from prebiotic chemistry to cellular metabolism. Their properties are typically analyzed through the kinet...
Praful Gagrani, Jiwei Wang, Yannick De Decker, David Lacoste
Same Error, Different Function: The Optimizer as an Implicit Prior in Financial Time Series
Neural networks applied to financial time series operate in a regime of underspecification, where model predictors achieve indistinguishable out-of-sample error. Using large-scale volatility foreca...
Federico Vittorio Cortesi, Giuseppe Iannone, Giulia Crippa, Tomaso Poggio, Pierfrancesco Beneventano
Mind the Way You Select Negative Texts: Pursuing the Distance Consistency in OOD Detection with VLMs
Out-of-distribution (OOD) detection seeks to identify samples from unknown classes, a critical capability for deploying machine learning models in open-world scenarios. Recent research has demonstr...
Zhikang Xu, Qianqian Xu, Zitai Wang, Cong Hua, Sicong Li, Zhiyong Yang, Qingming Huang
His2Trans: A Skeleton First Framework for Self Evolving C to Rust Translation with Historical Retrieval
Automated C-to-Rust migration encounters systemic obstacles when scaling from code snippets to industrial projects, mainly because build context is often unavailable ("dependency hell") and domain-...
Shengbo Wang, Mingwei Liu, Guangsheng Ou, Yuwen Chen, Zike Li, Yanlin Wang, Zibin Zheng