Government
Checklist 1. For all authors (a)
We explored whether SSL performance systematically varied as a function of reverberance using acoustic simulations.
Asynchronous Perception Machine for Efficient Test Time Training
We demonstrate APM's ability to recognize
Ask, Attend, Attack: An Effective Decision-Based Black-Box Targeted Attack for Image-to-Text Models
Despite the remarkable progress, they are vulnerable to deliberate attacks, giving rise to concerns about the reliability and trustworthiness of these models in real-world scenarios.
Large Language Model Unlearning
We study how to perform unlearning, i.e. forgetting undesirable (mis)behaviors, on large language models (LLMs).
The PRISM Alignment Dataset: What Participatory, Representative and Individualised Human Feedback Reveals About the Subjective and Multicultural Alignment of Large Language Models Hannah Rose Kirk 1
Human feedback is central to the alignment of Large Language Models (LLMs).
The World's First AI-Powered Minister Tests the Future of Government
Pillay is an editorial fellow at TIME. Albania's new AI-generated minister Diella speaks during the parliamentary session for the voting of the new government of Albania, in Tirana, on September 18, 2025. Albania's new AI-generated minister Diella speaks during the parliamentary session for the voting of the new government of Albania, in Tirana, on September 18, 2025. Pillay is an editorial fellow at TIME. In September, Albania appointed an AI system to a cabinet-level position--a world-first. Called Diella (Albanian for "sun"), the system was declared "Minister of State for Artificial Intelligence," and tasked by Albania's Prime Minister with addressing corruption in government contracting.
M3LEO: A Multi-Modal, Multi-Label Earth Observation Dataset Integrating Interferometric SAR and Multispectral Data
Satellite-based remote sensing has revolutionised the way we address global challenges in a rapidly evolving world. Huge quantities of Earth Observation (EO) data are generated by satellite sensors daily, but processing these large datasets for use in ML pipelines is technically and computationally challenging. Specifically, different types of EO data are often hosted on a variety of platforms, with differing degrees of availability for Python preprocessing tools. In addition, spatial alignment across data sources and data tiling for easier handling can present significant technical hurdles for novice users.
Towards Estimating Bounds on the Effect of Policies under Unobserved Confounding
As many practical fields transition to provide personalized decisions, data is increasingly relevant to support the evaluation of candidate plans and policies ( e.g.,
Stepwise Alignment for Constrained Language Model Policy Optimization Akifumi Wachi Thien Q. Tran Rei Sato Takumi Tanabe Y ouhei Akimoto L Y Corporation University of Tsukuba
Safety and trustworthiness are indispensable requirements for real-world applications of AI systems using large language models (LLMs).
