Agentic AI has significantly extended the capabilities of large language models (LLMs) by enabling complex reasoning and tool use. However, most existing frameworks are tailored to domains such as mathematics, coding, or web automation, and fall short on geospatial tasks that require spatial reasoning, multi-hop planning, and real-time map interaction. To address these challenges, we introduce MapAgent, a hierarchical multi-agent plug-and-play framework with customized toolsets and agentic scaffolds for map-integrated geospatial reasoning. Unlike existing flat agent-based approaches that treat tools uniformly-often overwhelming the LLM when handling similar but subtly different geospatial APIs-MapAgent decouples planning from execution. A high-level planner decomposes complex queries into subgoals, which are routed to specialized modules. For tool-heavy modules-such as map-based services-we then design a dedicated map-tool agent that efficiently orchestrates related APIs adaptively in parallel to effectively fetch geospatial data relevant for the query, while simpler modules (e.g., solution generation or answer extraction) operate without additional agent overhead. This hierarchical design reduces cognitive load, improves tool selection accuracy, and enables precise coordination across similar APIs. We evaluate MapAgent on four diverse geospatial benchmarks-MapEval-Textual, MapEval-API, MapEval-Visual, and MapQA-and demonstrate substantial gains over state-of-the-art tool-augmented and agentic baselines. We open-source our framwork at https://github.com/Hasebul/MapAgent.

The New Zealand government identified numerous challenges related to trust and truth in the context of digital technologies. These challenges result from an ever-increasing amount of online social networks, end-to-end digital supply chains, automated decision-making tools, generative artificial intelligence (AI), and cyber-physical systems. Such challenges impact people's lives across professional and private contexts and led to the Veracity Projecta 2021–2024. Outside the field of computing, veracity is not a common term in everyday language. One dictionary definition is "conformity with truth or fact."b

Connection science brings the computational sciences together with other disciplines such as psychology, neuroscience, philosophy, linguistics, sociology and cognitive science. This transdisciplinary approach seeks to leverage what's technically possible in a way that is inclusive and improves lifes.

Young scientists from the University of Auckland and Victoria University of Wellington have come up with a novel way to figure out which party or parties in New Zealand's Parliament are dominating any particular political debate or discourse. Young scientists from the University of Auckland and Victoria University of Wellington have come up with a novel way to figure out which party or parties in New Zealand's Parliament are dominating any particular political debate or discourse. Te Pūnaha Matatini Whanau members Ben Curran and Demival Vasques Filho (University of Auckland), and Kyle Higham and Elisenda Ortiz (Victoria University of Wellington) collaborated on the project, and their research findings have just been published in PLoS ONE, a leading international scientific journal. Their paper, 'Look who's talking: Two-mode networks as representations of a topic model of New Zealand Parliamentary speeches,' shows how the popularity of different topics debated in Parliament change over time, and proposes an approach that can reveal which party or parties are dominating the debate within certain topics. "It is difficult for any society to simply and easily track political debate and discussion over time," says co-author Demival Vasques Filho.