Threat actors are operationalizing AI to scale and sustain malicious activity, accelerating tradecraft and increasing risk for defenders, as illustrated by recent activity from North Korean groups ...
With USC, IBM and RWTH as co-authors, paper introduces dynamic decoupling method to deliver highest ever fidelity on ...
Microsoft researchers have developed On-Policy Context Distillation (OPCD), a training method that permanently embeds ...
Quantum computers are alternative computing devices that process information, leveraging quantum mechanical effects, such as entanglement between different particles. Entanglement establishes a link ...
Breakthrough technology advancement solves the biggest problem in traceability -- an unacceptably high error rate -- ensuring the quality and accuracy of data ...
We conducted a two-phase evaluation. First, we assessed LLMs (GPT o4-mini and Gemini 2.5 Pro) on 1,000 synthetic clinical hematology/oncology vignettes with ...
HEADQUARTERS IN TOWSON. WE’VE LEARNED HUMAN ERROR, SPECIFICALLY A LACK OF COMMUNICATION IS RESPONSIBLE FOR THE POLICE RESPONSE AND NOT THE AI GUN DETECTION SYSTEM. COUNCILMAN JULIAN JONES AND IZZY ...
AEGIS is a large-scale dataset and benchmark for detecting errors in Multi-Agent Systems (MAS). It provides systematically generated failure scenarios with verifiable ground-truth labels across ...
In seismic structural interpretation, fault detection plays a crucial role as it serves as the foundation and key step for identifying favorable oil and gas zones. Currently, many re-searchers are ...
Traffic monitoring plays a vital role in smart city infrastructure, road safety, and urban planning. Traditional detection systems, including earlier deep learning models, often struggle with ...
Abstract: The error stability of current transformers (CTs) during online operation is highly sensitive to power grid fluctuations, often resulting in error overruns ...
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