Papers
Research papers from arXiv and related sources
When AI output tips to bad but nobody notices: Legal implications of AI's mistakes
The adoption of generative AI across commercial and legal professions offers dramatic efficiency gains -- yet for law in particular, it introduces a perilous failure mode in which the AI fabricates...
Dylan J. Restrepo, Nicholas J. Restrepo, Frank Y. Huo, Neil F. Johnson
General Intellectual Humility Is Malleable Through AI-Mediated Reflective Dialogue
General intellectual humility (GIH) -- the recognition that one's beliefs may be fallible and revisable -- is associated with improved reasoning, learning, and social discourse, yet is widely regar...
Mohammad Ratul Mahjabin, Raiyan Abdul Baten
DMR effect on drag reduction of a streamlined body measured by Magnetic Suspension and Balance System
This study experimentally investigates the aerodynamic drag reduction capabilities of distributed micro-roughness (DMR) coatings on a streamlined model, utilising the 1-m magnetic suspension and ba...
Aiko Yakeno, Hiroyuki Okuizumi, Kento Inokuma, Yoshiyuki Watanabe
PoliticsBench: Benchmarking Political Values in Large Language Models with Multi-Turn Roleplay
While Large Language Models (LLMs) are increasingly used as primary sources of information, their potential for political bias may impact their objectivity. Existing benchmarks of LLM social bias p...
Rohan Khetan, Ashna Khetan
Bridging the Interpretation Gap in Accessibility Testing: Empathetic and Legal-Aware Bug Report Generation via Large Language Models
Modern automated accessibility testing tools for mobile applications have significantly improved the detection of interface violations, yet their impact on remediation remains limited. A key reason...
Ryoya Koyama, Zhiyao Wang, Devi Karolita, Jialong Li, Kenji Tei
AgentRFC: Security Design Principles and Conformance Testing for Agent Protocols
AI agent protocols -- including MCP, A2A, ANP, and ACP -- enable autonomous agents to discover capabilities, delegate tasks, and compose services across trust boundaries. Despite massive deployment...
Shenghan Zheng, Qifan Zhang
Human, AI, and Hybrid Ensembles for Detection of Adaptive, RL-based Social Bots
The use of reinforcement learning to dynamically adapt and evade detection is now well-documented in several cybersecurity settings including Covert Social Influence Operations (CSIOs), in which bo...
Valerio La Gatta, Nathan Subrahmanian, Kaitlyn Wang, Larry Birnbaum, V. S. Subrahmanian
Re-Prompting SAM 3 via Object Retrieval: 3rd of the 5th PVUW MOSE Track
This technical report explores the MOSEv2 track of the PVUW 2026 Challenge, which targets complex semi-supervised video object segmentation. Built on SAM~3, we develop an automatic re-prompting fra...
Mingqi Gao, Sijie Li, Jungong Han
Retinal Disease Classification from Fundus Images using CNN Transfer Learning
Retinal diseases remain among the leading preventable causes of visual impairment worldwide. Automated screening based on fundus image analysis has the potential to expand access to early detection...
Ali Akram
Leveraging Large Language Models for Trustworthiness Assessment of Web Applications
The widespread adoption of web applications has made their security a critical concern and has increased the need for systematic ways to assess whether they can be considered trustworthy. However, ...
Oleksandr Yarotskyi, José D'Abruzzo Pereira, João R. Campos
Semantic Iterative Reconstruction: One-Shot Universal Anomaly Detection
Unsupervised medical anomaly detection is severely limited by the scarcity of normal training samples. Existing methods typically train dedicated models for each dataset or disease, requiring hundr...
Ning Zhu
Proton-Transfer Ferroelectrics with Exceptional Switching Endurance
Reliable organic ferroelectrics for memory applications require extreme endurance under repeated electrical switching. Here we demonstrate exceptional fatigue resistance in highly crystalline 2-met...
Bibek Tiwari, Yuanyuan Ni, Xiaoshan Xu
AgenticNet: Utilizing AI Coding Agents To Create Hybrid Network Experiments
Traditional network experiments focus on validation through either simulation or emulation. Each approach has its own advantages and limitations. In this work, we present a new tool for next-genera...
Majd Latah, Kubra Kalkan
Quantum-classical dynamics of Rashba spin-orbit coupling
Mixed quantum-classical models are widely used to reduce the computational cost of fully quantum simulations. However, their general applicability across different classes of problems remains an op...
Paul Bergold, Giovanni Manfredi, Cesare Tronci
Thermally inflated accretors in post-mass transfer binaries: Abell 35 and its class revisited
A small but growing class of binaries containing hot ($T_{\rm eff}\sim10^5\rm~K$) white dwarfs (WDs) and rapidly rotating, apparently subgiant companions -- including the prototype, Abell 35 -- sho...
Soumyadeep Bhattacharjee, Kareem El-Badry, Jim Fuller, Cheyanne Shariat, Natsuko Yamaguchi
Detection and Classification of (Pre)Cancerous Cells in Pap Smears: An Ensemble Strategy for the RIVA Cervical Cytology Challenge
Automated detection and classification of cervical cells in conventional Pap smear images can strengthen cervical cancer screening at scale by reducing manual workload, improving triage, and increa...
Lautaro Kogan, María Victoria Ríos
Spatial Sampling of Hemispherical Arrays for Three-Dimensional Photoacoustic Computed Tomography
Three-dimensional (3D) photoacoustic computed tomography (PACT) is a powerful noninvasive biomedical imaging modality that provides volumetric data for structural and functional assessment \textit{...
Wanqing Zhang, Hengyue Zhu, Yide Zhang
The Long Shadow of Pandemic: Understanding the lingering effects of cause-specific mortality shocks
In the aftermath of the COVID-19 pandemic, empirical data have revealed that large-scale health crises not only cause immediate disruptions in mortality dynamics but also have persistent effects th...
Yanxin Liu, Kenneth Q. Zhou
Distributionally Robust $k$-of-$n$ Sequential Testing
The $k$-of-$n$ testing problem involves performing $n$ independent tests sequentially, in order to determine whether/not at least $k$ tests pass. The objective is to minimize the expected cost of t...
Rayen Tan, Viswanath Nagarajan
Towards Leveraging LLMs to Generate Abstract Penetration Test Cases from Software Architecture
Software architecture models capture early design decisions that strongly influence system quality attributes, including security. However, architecture-level security assessment and feedback are o...
Mahdi Jafari, Rahul Sharma, Sami Naim, Christopher Gerking, Ralf Reussner