Papers
Research papers from arXiv and related sources
Transform-Invariant Generative Ray Path Sampling for Efficient Radio Propagation Modeling
Ray tracing has become a standard for accurate radio propagation modeling, but suffers from exponential computational complexity, as the number of candidate paths scales with the number of objects ...
Jérome Eertmans, Enrico M. Vitucci, Vittorio Degli-Esposti, Nicola Di Cicco, Laurent Jacques, Cla...
An Investigation of the Relation Between Immersion and Learning Across Three Domains
We investigate the relationship between immersion and learning across three domains (cultural heritage, environmental awareness, and high school physics) through the lens of the Cognitive Affective...
Paolo Boffi, Alberto Gallace, Pier Luca Lanzi
Learning Structured Reasoning via Tractable Trajectory Control
Large language models can exhibit emergent reasoning behaviors, often manifested as recurring lexical patterns (e.g., "wait," indicating verification). However, complex reasoning trajectories remai...
Po-Nien Kung, Zhen Yang, Jeffrey Luo, Cheng-Fu Yang, Haikang Deng, Zi-Yi Dou, Yinfei Yang, Nanyun...
Episode-wise spectro-polarimetry of GRB 220107A: Testing the hypothesis of evolving radiation mechanisms
We investigate the spectro-polarimetric properties of the long-duration GRB~220107A, which exhibited two distinct emission episodes separated by a 40 s quiescent gap, to test whether such multi-epi...
Rahul Gupta, Rushikesh Sonawane, Shabnam Iyyani, D. Frederiks, Judith Racusin, Tanmoy Chattopadha...
SEED-SET: Scalable Evolving Experimental Design for System-level Ethical Testing
As autonomous systems such as drones, become increasingly deployed in high-stakes, human-centric domains, it is critical to evaluate the ethical alignment since failure to do so imposes imminent da...
Anjali Parashar, Yingke Li, Eric Yang Yu, Fei Chen, James Neidhoefer, Devesh Upadhyay, Chuchu Fan
Mapping properties of the $S$-operator
In this paper, we study the $\ell^p\to \ell^r$ estimates for the $S$-operator arising in restriction problems for spheres over finite fields. We establish a necessary and sufficient condition for t...
Hunseok Kang, Doowon Koh, Changhun Yang
A Block Least Mean Square Method for Fiber Longitudinal Power Profile Monitoring
We propose a block least mean square (LMS) algorithm to monitor the longitudinal power profile of a fiber-optic link through receiver-based digital data from a coherent detector. Compared to the be...
Paolo Serena, Chiara Lasagni, Alberto Bononi, Fabien Boitier, Joana Girard-Jollet
IDProxy: Cold-Start CTR Prediction for Ads and Recommendation at Xiaohongshu with Multimodal LLMs
Click-through rate (CTR) models in advertising and recommendation systems rely heavily on item ID embeddings, which struggle in item cold-start settings. We present IDProxy, a solution that leverag...
Yubin Zhang, Haiming Xu, Guillaume Salha-Galvan, Ruiyan Han, Feiyang Xiao, Yanhua Huang, Li Lin, ...
DualSentinel: A Lightweight Framework for Detecting Targeted Attacks in Black-box LLM via Dual Entropy Lull Pattern
Recent intelligent systems integrate powerful Large Language Models (LLMs) through APIs, but their trustworthiness may be critically undermined by targeted attacks like backdoor and prompt injectio...
Xiaoyi Pang, Xuanyi Hao, Pengyu Liu, Qi Luo, Song Guo, Zhibo Wang
Testing Hooke-like isotropic hyper-/hypo-elastic material models under finite simple shear deformations
We test some Hooke-like isotropic hyper-/hypo-elastic material models under finite simple shear deformations (cf., Thiel et al. Int. J. Non-linear Mech. 112: 57--72, 2019) and show that (1) the com...
Sergey N. Korobeynikov, Alexey Yu. Larichkin, Patrizio Neff
Pharmacology Knowledge Graphs: Do We Need Chemical Structure for Drug Repurposing?
The contributions of model complexity, data volume, and feature modalities to knowledge graph-based drug repurposing remain poorly quantified under rigorous temporal validation. We constructed a ph...
Youssef Abo-Dahab, Ruby Hernandez, Ismael Caleb Arechiga Duran
Benchmarking Semantic Segmentation Models via Appearance and Geometry Attribute Editing
Semantic segmentation takes pivotal roles in various applications such as autonomous driving and medical image analysis. When deploying segmentation models in practice, it is critical to test their...
Zijin Yin, Bing Li, Kongming Liang, Hao Sun, Zhongjiang He, Zhanyu Ma, Jun Guo
RoboGPU: Accelerating GPU Collision Detection for Robotics
Autonomous robots are increasingly prevalent in our society, emerging in medical care, transportation vehicles, and home assistance. These robots rely on motion planning and collision detection to ...
Lufei Liu, Liwei Xue, Youssef Mohammed, Jocelyn Zhao, Yuan Hsi Chou, Tor M. Aamodt
Retrieval, Refinement, and Ranking for Text-to-Video Generation via Prompt Optimization and Test-Time Scaling
While large-scale datasets have driven significant progress in Text-to-Video (T2V) generative models, these models remain highly sensitive to input prompts, demonstrating that prompt design is crit...
Zillur Rahman, Alex Sheng, Cristian Meo
FATE: Closed-Loop Feasibility-Aware Task Generation with Active Repair for Physically Grounded Robotic Curricula
Recent breakthroughs in generative simulation have harnessed Large Language Models (LLMs) to generate diverse robotic task curricula, yet these open-loop paradigms frequently produce linguistically...
Bingchuan Wei, Bingqi Huang, Jingheng Ma, Zeyu zhang, Sen Cui
Wild Bootstrap Inference for Non-Negative Matrix Factorization with Random Effects
Non-negative matrix factorization (NMF) is widely used for parts-based representations, yet formal inference for covariate effects is rarely available when the basis is learned under non-negativity...
Kenichi Satoh
Modified Teukolsky formalism: Null testing and numerical benchmarking
Next-generation gravitational-wave detectors will make black-hole ringdown an increasingly sensitive probe of small departures from General Relativity in the strong-field regime. This motivates obt...
Fawzi Aly, Mahmoud A. Mansour, Luis Lehner, Dejan Stojkovic, Dongjun Li, Pratik Wagle
VidDoS: Universal Denial-of-Service Attack on Video-based Large Language Models
Video-LLMs are increasingly deployed in safety-critical applications but are vulnerable to Energy-Latency Attacks (ELAs) that exhaust computational resources. Current image-centric methods fail bec...
Duoxun Tang, Dasen Dai, Jiyao Wang, Xiao Yang, Jianyu Wang, Siqi Cai
Autoregressive Synthesis of Sparse and Semi-Structured Mixed-Type Data
Synthetic data generation is a critical capability for data sharing, privacy compliance, system benchmarking and test data provisioning. Existing methods assume dense, fixed-schema tabular data, ye...
Thomas Rückstieß, Robin Vujanic
Quantifying Conversational Reliability of Large Language Models under Multi-Turn Interaction
Large Language Models (LLMs) are increasingly deployed in real-world applications where users engage in extended, mixed-topic conversations that depend on prior context. Yet, their reliability unde...
Jiyoon Myung