Papers
Research papers from arXiv and related sources
A Deep Surrogate Model for Robust and Generalizable Long-Term Blast Wave Prediction
Accurately modeling the spatio-temporal dynamics of blast wave propagation remains a longstanding challenge due to its highly nonlinear behavior, sharp gradients, and burdensome computational cost....
Danning Jing, Xinhai Chen, Xifeng Pu, Jie Hu, Chao Huang, Xuguang Chen, Qinglin Wang, Jie Liu
GrandTour: A Legged Robotics Dataset in the Wild for Multi-Modal Perception and State Estimation
Accurate state estimation and multi-modal perception are prerequisites for autonomous legged robots in complex, large-scale environments. To date, no large-scale public legged-robot dataset capture...
Jonas Frey, Turcan Tuna, Frank Fu, Katharine Patterson, Tianao Xu, Maurice Fallon, Cesar Cadena, ...
Equal Marginal Power for Co-Primary Endpoints
The choice of sample size in the context of co-primary endpoints for a randomised trial is discussed. Current guidance can leave endpoints with unequal marginal power. A method is provided to achie...
Simon Bond
FENCE: A Financial and Multimodal Jailbreak Detection Dataset
Jailbreaking poses a significant risk to the deployment of Large Language Models (LLMs) and Vision Language Models (VLMs). VLMs are particularly vulnerable because they process both text and images...
Mirae Kim, Seonghun Jeong, Youngjun Kwak
The Statistical Signature of LLMs
Large language models generate text through probabilistic sampling from high-dimensional distributions, yet how this process reshapes the structural statistical organization of language remains inc...
Ortal Hadad, Edoardo Loru, Jacopo Nudo, Niccolò Di Marco, Matteo Cinelli, Walter Quattrociocchi
Detecting Contextual Hallucinations in LLMs with Frequency-Aware Attention
Hallucination detection is critical for ensuring the reliability of large language models (LLMs) in context-based generation. Prior work has explored intrinsic signals available during generation, ...
Siya Qi, Yudong Chen, Runcong Zhao, Qinglin Zhu, Zhanghao Hu, Wei Liu, Yulan He, Zheng Yuan, Lin Gui
History-Constrained Systems
We study verification problems for history-constrained systems (HCS), a model of guarded computation that uses nested systems. An outer system describes the process architecture in which a sequence...
Louwe B. Kuijer, David Purser, Henry Sinclair-Banks, Patrick Totzke
Toward Automated Virtual Electronic Control Unit (ECU) Twins for Shift-Left Automotive Software Testing
Automotive software increasingly outpaces hardware availability, forcing late integration and expensive hardware-in-the-loop (HiL) bottlenecks. The InnoRegioChallenge project investigated whether a...
Sebastian Dingler, Frederik Boenke
Demonstrating Restraint
Some have claimed that the future development of powerful AI systems would enable the United States to shift the international balance of power dramatically in its favor. Such a feat may not be tec...
L. C. R. Patell, O. E. Guest
Agentic Adversarial QA for Improving Domain-Specific LLMs
Large Language Models (LLMs), despite extensive pretraining on broad internet corpora, often struggle to adapt effectively to specialized domains. There is growing interest in fine-tuning these mod...
Vincent Grari, Ciprian Tomoiaga, Sylvain Lamprier, Tatsunori Hashimoto, Marcin Detyniecki
Computing accurate singular values using a mixed-precision one-sided Jacobi algorithm
We present a relative forward error analysis of a mixed-precision preconditioned one-sided Jacobi algorithm, analogous to a two-sided version introduced in [N. J. Higham, F. Tisseur, M. Webb and Z....
Zhengbo Zhou, Françoise Tisseur, Marcus Webb
Learning Long-Range Dependencies with Temporal Predictive Coding
Predictive Coding (PC) is a biologically-inspired learning framework characterised by local, parallelisable operations, properties that enable energy-efficient implementation on neuromorphic hardwa...
Tom Potter, Oliver Rhodes
Comparative study of different quadrature methods for cut elements
The quadrature of cut elements is crucial for all Finite Element Methods that do not apply boundary-fitted meshes. It should be efficient, accurate, and robust. Various approaches balancing these r...
Michael Loibl, Guilherme H. Teixeira, Teoman Toprak, Irina Shishkina, Chen Miao, Josef Kiendl, Fl...
Testing the Icy Pebble Accretion Hypothesis with Primordial Main Belt Asteroids
Large main-belt asteroids (diameter $D \gtrsim 120\ \mathrm{km}$) exhibit a surface composition gradient as a function of heliocentric distance, ranging from anhydrous bodies to those rich in hydra...
Jinfei Yu, Hiroyuki Kurokawa, Tetsuo Taki
TROYE: Modeling Dynamic Phase Transitions in Gravitational Waves from Neutron Star-Black Hole Mergers
The Equation of State (EoS) of dense nuclear matter remains one of the most compelling open questions in high-energy astrophysics. While static EoS models are increasingly well-constrained by obser...
Ofek Dan, Ofek Birnholtz
3D radiative transfer modeling of scattering polarization with partial frequency redistribution I. Verification and disk-center results for the solar Ca I 4227 Å line
Several strong solar resonance lines show observable linear scattering polarization signals, holding a great potential for investigating the magnetism of the outer solar atmosphere. Accurately mode...
Pietro Benedusi, Simone Riva, Tanausú del Pino Alemán, Gioele Janett, Fabio Riva, Jirí Štepán, Ro...
Neurosymbolic Language Reasoning as Satisfiability Modulo Theory
Natural language understanding requires interleaving textual and logical reasoning, yet large language models often fail to perform such reasoning reliably. Existing neurosymbolic systems combine L...
Hyunseok Oh, Sam Stern, Youngki Lee, Matthai Philipose
OODBench: Out-of-Distribution Benchmark for Large Vision-Language Models
Existing Visual-Language Models (VLMs) have achieved significant progress by being trained on massive-scale datasets, typically under the assumption that data are independent and identically distri...
Ling Lin, Yang Bai, Heng Su, Congcong Zhu, Yaoxing Wang, Yang Zhou, Huazhu Fu, Jingrun Chen
Perceived Political Bias in LLMs Reduces Persuasive Abilities
Conversational AI has been proposed as a scalable way to correct public misconceptions and spread misinformation. Yet its effectiveness may depend on perceptions of its political neutrality. As LLM...
Matthew DiGiuseppe, Joshua Robison
AndroWasm: an Empirical Study on Android Malware Obfuscation through WebAssembly
In recent years, stealthy Android malware has increasingly adopted sophisticated techniques to bypass automatic detection mechanisms and harden manual analysis. Adversaries typically rely on obfusc...
Diego Soi, Silvia Lucia Sanna, Lorenzo Pisu, Leonardo Regano, Giorgio Giacinto