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14 papers published across 1 lab.
Initial evidence is provided that greCAPTCHA can assess manuscript-specific understanding under proctored conditions and the appropriate construct validity for author understanding is remarked on, while also suggesting important changes to be made before deployment.
The results suggest that, for large digital libraries and archives, retrieval accountability and corpus-aware agent design can provide a practical alternative to heavier training-based or graph-construction approaches.
It is demonstrated that gradient-based attribution methods track format similarity more than task semantics, meaning that such methods, as well as the semantic interpretation of the gradient, should be tested on data where answer format and task vary independently for greater robustness and reliability.
Initial evidence is provided that greCAPTCHA can assess manuscript-specific understanding under proctored conditions and the appropriate construct validity for author understanding is remarked on, while also suggesting important changes to be made before deployment.
The results suggest that, for large digital libraries and archives, retrieval accountability and corpus-aware agent design can provide a practical alternative to heavier training-based or graph-construction approaches.
It is demonstrated that gradient-based attribution methods track format similarity more than task semantics, meaning that such methods, as well as the semantic interpretation of the gradient, should be tested on data where answer format and task vary independently for greater robustness and reliability.
This work audits five LLM overseers on 19 compliance tasks, varying only trace detail and evidence labeling, finding that elaborate traces shift the decision criterion toward rejection, increasing false alarms in susceptible overseers.
An automated framework is developed that constructs user runtime instruction-agnostic UI desynchronization attacks and realizes them in deployable APKs, demonstrating that this threat is feasible and feasible.
Atria Dawn Preview is introduced, a foundation agentic language model designed for scientific research and engineering workflows, with the goal of expanding the frontier of agent productivity in the real world.
This paper investigates how AI-driven feedback mechanisms, including sentiment analysis systems, pulse surveys, chatbots, engagement dashboards, and predictive analytics, are changing African workplaces through offering continuous listening, instant performance information and proactive engagement with employees.
The research establishes task-based access control as a measured, potentially deployable mechanism for reducing attack surface in agentic deployments.