Aug 2026· Zenodo (CERN European Organization for Nuclear Research)
Abstract
Abstract Getting timely financial compensation for road accident victims and their families is a matter of utmost humanitarian and legal importance. Traditionally, the compensation process through Motor Vehicle Accident Claims Tribunals (MACT) and insurance companies in many countries, including India, has been very complex, paper-based and time-consuming. However, in the modern era, the advent of technologies like Artificial Intelligence (AI), telematics, GPS, online portals and digital interoperable databases has brought a major revolution in this field. This research article examines in detail the role of technology in the process of motor accident claims, from filing to final settlement and payment. The study shows how digital platforms like e-DAR (e-Detailed Accident Report), through direct digital connectivity between police, hospitals, insurance companies and the judiciary, can reduce the time to compensation from years to months or weeks.
Investigating how experienced developers use agents in building software, including their motivations, strategies, task suitability, and sentiments finds that while experienced developers value agents as a productivity boost, they retain their agency in software design and implementation out of insistence on fundamental software quality attributes.
An adaptive surrogate modeling method for problems with very high-dimensional spatio-temporal outputs is developed that combines exploration and exploitation to improve the surrogate model accuracy with the fewest possible runs of the expensive physics-based model.
B. Kapusuzoglu, S. Mahadevan, Shunsaku Matsumoto et al.· Structural And Multidiscipli...· 17 citations
An adaptive jailbreak attack framework for systematic evaluation of both cascaded pipelines and end-to-end large audio-language models under a unified experimental setting that achieves consistently higher attack success rates across diverse audio-based LLM systems.
Linghan Huang, Bo Li, Huaming Chen et al.· 12 citations· ⚡2
This review provides a systematic literature review of LLM-based Verilog code generation, analyzing 102 papers (70 published and 32 high-quality preprints) from SE, AI, and EDA venues and outlines a roadmap highlighting potential opportunities in LLM-assisted hardware design.
This work introduces Behavior-Outcome Freedom (F), a pre-synthesis diagnostic of signed behavior-outcome rank mismatch, and formalizes its candidate-conditional role through Signed Anchor-Rank Transfer, which preserves validated capability resources, removes runtime orchestration, and conditionally inherits pipeline guidance using a calibrated rule over F.
Binyan Xu, Dong Fang, Haitao Li et al.· arXiv.org· 10 citations
Simulation results confirm the effectiveness and benefits of DMs in generating neighbor velocity estimates in a four-UAV swarm coordination task using Deep Reinforcement Learning (DRL), and explore the integration of DMs with RL and DT.
