Papers
Research papers from arXiv and related sources
Hybrid topic modelling for computational close reading: Mapping narrative themes in Pushkin's Evgenij Onegin
This study presents a hybrid topic modelling framework for computational literary analysis that integrates Latent Dirichlet Allocation (LDA) with sparse Partial Least Squares Discriminant Analysis ...
Angelo Maria Sabatini
Modeling the merger-ringdown of an eccentric test-mass inspiral into a Kerr black hole using the effective-one-body framework
We characterize and phenomenologically model the merger-ringdown of gravitational waves emitted by a small compact object that plunges and merges into a Kerr black hole from equatorial-eccentric in...
Guglielmo Faggioli, Alessandra Buonanno, Maarten van de Meent, Gaurav Khanna
DSC curve fingerprints directly encode mechanical properties of aluminum alloys
Differential scanning calorimetry (DSC) is a standard tool for studying precipitation and phase transformations in aluminum alloys, yet its relation to mechanical performance has so far remained mo...
Lukas Pichlmann, Samuel Studer, Aurel R. Arnoldt, Paul Oberhauser, Johannes A. Österreicher
Constraints on the $^{12}$C$(α, γ)^{16}$O and $^{16}$O+$^{16}$O Reaction Rates from Binary Black Holes Detected via Gravitational Wave Signals
Gravitational-wave observations of binary black hole (BH) mergers provide a novel avenue for testing massive-star evolution and the resulting BH mass spectrum. Recent population analyses under the ...
Wenyu Xin, Xiaokun Hou, Xianfei Zhang, Shaolan Bi, Gang Zhao
Modeling Quasar Photo-$z$ Distribution and Uncertainty. A Study Based on the Kilo-Degree Survey
We aim to determine the most effective approach for estimating uncertainties in quasar photo-$z$ and to evaluate the ability of different models to reconstruct the true redshift distribution under ...
Kacper Drabicki, Szymon J. Nakoneczny, Maciej Bilicki
NASimJax: GPU-Accelerated Policy Learning Framework for Penetration Testing
Penetration testing, the practice of simulating cyberattacks to identify vulnerabilities, is a complex sequential decision-making task that is inherently partially observable and features large act...
Raphael Simon, José Carrasquel, Wim Mees, Pieter Libin
Dynamically Reprogrammable Runtime Monitors for Bounded-time MTL
A Runtime Verification (RV) framework that supports online, at-speed verification of properties that can change dynamically (during in-field operations) will benefit a large variety of applications...
Chirantan Hebballi, Akash Poptani, Amrutha Benny, Rajshekar Kalayappan, Sandeep Chandran, Ramchan...
Modeling subgrid scale production rates on complex meshes using graph neural networks
Large-eddy simulations (LES) require closures for filtered production rates because the resolved fields do not contain all correlations that govern chemical source terms. We develop a graph neural ...
Priyabrat Dash, Mathis Bode, Konduri Aditya
HUGE-Bench: A Benchmark for High-Level UAV Vision-Language-Action Tasks
Existing UAV vision-language navigation (VLN) benchmarks have enabled language-guided flight, but they largely focus on long, step-wise route descriptions with goal-centric evaluation, making them ...
Jingyu Guo, Ziye Chen, Ziwen Li, Zhengqing Gao, Jiaxin Huang, Hanlue Zhang, Fengming Huang, Yu Ya...
Quantifying Gate Contribution in Quantum Feature Maps for Scalable Circuit Optimization
Quantum machine learning offers promising advantages for classification tasks, but noise, decoherence, and connectivity constraints in current devices continue to limit the efficient execution of f...
F. Rodríguez-Díaz, D. Gutiérrez-Avilés, A. Troncoso, F. Martínez-Álvarez
Chaotic motion and power spectral density in Schwarzschild Bertotti-Robinson black hole spacetime
In this paper, we show that in weak field limit Schwarzschild Bertotti-Robinson black hole (Schwarzschild-BR BH) turns into Schwarzschild black hole immersed in external uniform magnetic field whic...
Yunqiao Xu, Uktamjon Uktamov, Pierros Ntelis, Ahmadjon Abdujabbarov, Bobomurat Ahmedov, Chengxun ...
Template-based Object Detection Using a Foundation Model
Most currently used object detection methods are learning-based, and can detect objects under varying appearances. Those models require training and a training dataset. We focus on use cases with l...
Valentin Braeutigam, Matthias Stock, Bernhard Egger
Extraction of tabulated statistical results with tableParser
Tabulated content is omnipresent in scientific literature. This work presents the R package *tableParser*, designed to extract and postprocess tables from NISO-JATS-encoded XML, HTML, DOCX, and, wi...
Ingmar Böschen
LiteAtt: Secure and Seamless IoT Services Using TinyML-based Self-Attestation as a Primitive
As the Internet of Things (IoT) becomes an integral part of critical infrastructure, smart cities, and consumer networks, there has been an increase in the number of software attacks on the microco...
Varun Kohli, Biplab Sikdar
Sensing Your Vocals: Exploring the Activity of Vocal Cord Muscles for Pitch Assessment Using Electromyography and Ultrasonography
Vocal training is difficult because the muscles that control pitch, resonance, and phonation are internal and invisible to learners. This paper investigates how Electromyography (EMG) and ultrasoni...
Kanyu Chen, Rebecca Panskus, Erwin Wu, Yichen Peng, Daichi Saito, Emiko Kamiyama, Ruiteng Li, Che...
ATHENA: Adaptive Test-Time Steering for Improving Count Fidelity in Diffusion Models
Text-to-image diffusion models achieve high visual fidelity but surprisingly exhibit systematic failures in numerical control when prompts specify explicit object counts. To address this limitation...
Mohammad Shahab Sepehri, Asal Mehradfar, Berk Tinaz, Salman Avestimehr, Mahdi Soltanolkotabi
GenFacet: End-to-End Generative Faceted Search via Multi-Task Preference Alignment in E-Commerce
Faceted search acts as a critical bridge for navigating massive ecommerce catalogs, yet traditional systems rely on static rule-based extraction or statistical ranking, struggling with emerging voc...
Zhouwei Zhai, Min Yang, Jin Li
The Residual Stream Is All You Need: On the Redundancy of the KV Cache in Transformer Inference
The key-value (KV) cache is widely treated as essential state in transformer inference, and a large body of work engineers policies to compress, evict, or approximate its entries. We prove that thi...
Kaleem Ullah Qasim, Jiashu Zhang, Muhammad Kafeel Shaheen, Razan Alharith, Heying Zhang
Accurate Open-Loop Control of a Soft Continuum Robot Through Visually Learned Latent Representations
This work addresses open-loop control of a soft continuum robot (SCR) from video-learned latent dynamics. Visual Oscillator Networks (VONs) from previous work are used, that provide mechanistically...
Henrik Krauss, Johann Licher, Naoya Takeishi, Annika Raatz, Takehisa Yairi
Ensembles-based Feature Guided Analysis
Recent Deep Neural Networks (DNN) applications ask for techniques that can explain their behavior. Existing solutions, such as Feature Guided Analysis (FGA), extract rules on their internal behavio...
Federico Formica, Stefano Gregis, Andrea Rota, Aurora Francesca Zanenga, Mark Lawford, Claudio Me...