Papers
Research papers from arXiv and related sources
p-Hacking Inflates Type I Error Rates in the Error Statistical Approach but not in the Formal Inference Approach
p-hacking occurs when researchers conduct multiple significance tests (e.g., p1;H0,1 and p2;H0,2) and then selectively report tests that yield desirable (usually significant) results (e.g., p2 < 0....
Mark Rubin
CALIMA: On-the-fly dust and PAH evolution for radiation-hydrodynamics galaxy formation simulations
Dust grains and polycyclic aromatic hydrocarbons (PAHs) actively contribute to the thermodynamics, chemistry, and radiative state of the interstellar medium (ISM), yet most ISM models and galaxy si...
Francisco Rodríguez Montero, Yohan Dubois, Harley Katz, Adrianne Slyz, Julien Devriendt
Therapist-Robot-Patient Physical Interaction is Worth a Thousand Words: Enabling Intuitive Therapist Guidance via Remote Haptic Control
Robotic systems can enhance the amount and repeatability of physically guided motor training. Yet their real-world adoption is limited, partly due to non-intuitive trainer/therapist-trainee/patient...
Beatrice Luciani, Alex van den Berg, Matti Lang, Alexandre L. Ratschat, Laura Marchal-Crespo
Beyond Static Artifacts: A Forensic Benchmark for Video Deepfake Reasoning in Vision Language Models
Current Vision-Language Models (VLMs) for deepfake detection excel at identifying spatial artifacts but overlook a critical dimension: temporal inconsistencies in video forgeries. Adapting VLMs to ...
Zheyuan Gu, Qingsong Zhao, Yusong Wang, Zhaohong Huang, Xinqi Li, Cheng Yuan, Jiaowei Shao, Chi Z...
Linear Perturbations and Multi-Probe Diagnostics in Dark-Sector Selective $f(R,T_χ)$ Gravity
We develop a dark-sector selective trace-coupled extension of gravity in which the matter--curvature coupling depends exclusively on the trace of the dark-matter energy--momentum tensor, $T_χ$, def...
L. Yildiz, D. Kayki, E. Gudekli
RAMSeS: Robust and Adaptive Model Selection for Time-Series Anomaly Detection Algorithms
Time-series data vary widely across domains, making a universal anomaly detector impractical. Methods that perform well on one dataset often fail to transfer because what counts as an anomaly is co...
Mohamed Abdelmaksoud, Sheng Ding, Andrey Morozov, Ziawasch Abedjan
Learning spatially adaptive sparsity level maps for arbitrary convolutional dictionaries
State-of-the-art learned reconstruction methods often rely on black-box modules that, despite their strong performance, raise questions about their interpretability and robustness. Here, we build o...
Joshua Schulz, David Schote, Christoph Kolbitsch, Kostas Papafitsoros, Andreas Kofler
Learning Complex Physical Regimes via Coverage-oriented Uncertainty Quantification: An application to the Critical Heat Flux
A central challenge in scientific machine learning (ML) is the correct representation of physical systems governed by multi-regime behaviours. In these scenarios, standard data analysis techniques ...
Michele Cazzola, Alberto Ghione, Lucia Sargentini, Julien Nespoulous, Riccardo Finotello
Combining matrix product states and mean-field theory to capture magnetic order in quasi-1D cuprates
We study quasi-one-dimensional strongly correlated materials using a multi-step approach based on density functional theory, downfolding techniques, and tensor-network simulations. The downfolding ...
Quentin Staelens, Daan Verraes, Daan Vrancken, Tom Braeckevelt, Jutho Haegeman, Veronique Van Spe...
Multimodal Survival Modeling and Fairness-Aware Clinical Machine Learning for 5-Year Breast Cancer Risk Prediction
Clinical risk prediction models often underperform in real-world settings due to poor calibration, limited transportability, and subgroup disparities. These challenges are amplified in high-dimensi...
Toktam Khatibi
Mitigating Structural Noise in Low-Resource S2TT: An Optimized Cascaded Nepali-English Pipeline with Punctuation Restoration
This paper presents and evaluates an optimized cascaded Nepali speech-to-English text translation (S2TT) system, focusing on mitigating structural noise introduced by Automatic Speech Recognition (...
Tangsang Chongbang, Pranesh Pyara Shrestha, Amrit Sarki, Anku Jaiswal
Permutation Polynomials Under Multiplicative-Additive Perturbations: Characterization via Difference Distribution Tables
We investigate permutation polynomials F over finite fields F_{p^n} whose generalized derivative maps x -> F(x + a) - cF(x) are themselves permutations for all nonzero shifts a. This property, term...
Ranit Dutta, Pantelimon Stanica, Bimal Mandal
Holographic QCD equation of state constrained by lattice QCD: neural-ODE for probe-limit and a back-reaction test
We study the equation of state (EoS) of QCD matter in a bottom-up holographic setup that combines an Einstein-Maxwell-dilaton (EMD) sector with an improved Karch-Katz-Son-Stephanov (KKSS) flavor ac...
Yutian Deng, Mei Huang, Lin Zhang
GW070605: An Undisclosed Binary Neutron Star Hardware Injection in LIGO's Fifth Science Run
The authors wished to document the sensitivity improvement that has been contributed to the GW detection rate by detection algorithm research and development efforts, and set about re-analyzing S5 ...
Heather Fong, Kipp Cannon, Chi-Wai Chan, Richard N. George, Alvin K. Y. Li, Soichiro Kuwahara, Hi...
WatchHand: Enabling Continuous Hand Pose Tracking On Off-the-Shelf Smartwatches
Tracking hand poses on wrist-wearables enables rich, expressive interactions, yet remains unavailable on commercial smartwatches, as prior implementations rely on external sensors or custom hardwar...
Jiwan Kim, Chi-Jung Lee, Hohurn Jung, Tianhong Catherine Yu, Ruidong Zhang, Ian Oakley, Cheng Zhang
Deep Clustering based Boundary-Decoder Net for Inter and Intra Layer Stress Prediction of Heterogeneous Integrated IC Chip
High stress occurs when 3D heterogeneous IC packages are subjected to thermal cycling at extreme temperatures. Stress mainly occurs at the interface between different materials. We investigate stre...
Kart Leong Lim, Ji Lin
Iterative Closed-Loop Motion Synthesis for Scaling the Capabilities of Humanoid Control
Physics-based humanoid control relies on training with motion datasets that have diverse data distributions. However, the fixed difficulty distribution of datasets limits the performance ceiling of...
Weisheng Xu, Qiwei Wu, Jiaxi Zhang, Tan Jing, Yangfan Li, Yuetong Fang, Jiaqi Xiong, Kai Wu, Rong...
Physics Informed Neural Network using Finite Difference Method
In recent engineering applications using deep learning, physics-informed neural network (PINN) is a new development as it can exploit the underlying physics of engineering systems. The novelty of P...
Kart Leong Lim, Rahul Dutta, Mihai Rotaru
Goodness-of-Fit Tests for Latent Class Models with Ordinal Categorical Data
Ordinal categorical data are widely collected in psychology, education, and other social sciences, appearing commonly in questionnaires, assessments, and surveys. Latent class models provide a flex...
Huan Qing
How many asymmetric communities are there in multi-layer directed networks?
Estimating the asymmetric numbers of communities in multi-layer directed networks is a challenging problem due to the multi-layer structures and inherent directional asymmetry, leading to possibly ...
Huan Qing