We present the first approach to build hierarchical task-driven 3D scene graphs of arbitrary indoor or outdoor environments using an uncalibrated monocular camera in real-time. We leverage geometric foundation models to estimate geometric attributes of the scene graph (e.g., object bounding boxes), but we also observe that traversability information (the "places" layer of a scene graph) can be directly reconstructed by adding an extra head to existing geometric foundation models, like VGGT. Our approach is task-driven in the sense that we adjust the granularity of the objects and regions in the map depending on the task; for instance, during a manipulation task, our approach is able to resolve small knobs on a stove, while during a navigation task it can focus on large objects (e.g., the entire stove). However, in a major departure from related work, we consider the realistic case where the list of tasks is not predefined and fixed, but evolves as the robot operates. This naturally allows dealing with complex loco-manipulation tasks, where the robot can dynamically adjust its representation as the task unfolds. We dub the resulting approach FOUND-IT. FOUND-IT also includes an agent
Seasonality has traditionally shaped the U.S. housing market, with activity peaking in spring-summer and declining in autumn-winter. However, recent disruptions, particularly post-COVID-19, raise questions about shift in these patterns. This study analyzes housing market date (1991-2024) to examine evolving seasonality and regional heterogeneity. Using Housing Price Index (HPI), inventory and sales data from the Federal Housing Finance Agency and U.S. Census Bureau, seasonal components are extracted via the X-13-ARIMA procedure, and statistical tests assess variations across regions. The results confirm seasonal fluctuations in prices and volumes, with recent shifts toward earlier annual peak (March-April) and amplified seasonal effects. Regional variations align with differences in climate and market structure, while prices and sales volumes exhibit in-phase movement, suggesting thick-market momentum behaviour. These findings highlight key implications for policymakers, realtors and investors navigating post-pandemic market dynamics, offering insights into the timing and interpretation of housing market activities.
This paper develops an agentic framework that employs large language models (LLMs) for grounded persuasive language generation in automated copywriting, with real estate marketing as a focal application. Our method is designed to align the generated content with user preferences while highlighting useful factual attributes. This agent consists of three key modules: (1) Grounding Module, mimicking expert human behavior to predict marketable features; (2) Personalization Module, aligning content with user preferences; (3) Marketing Module, ensuring factual accuracy and the inclusion of localized features. We conduct systematic human-subject experiments in the domain of real estate marketing, with a focus group of potential house buyers. The results demonstrate that marketing descriptions generated by our approach are preferred over those written by human experts by a clear margin while maintaining the same level of factual accuracy. Our findings suggest a promising agentic approach to automate large-scale targeted copywriting while ensuring factuality of content generation.
K2-18b is one of the most promising worlds for the search for extraterrestrial life, so astronomers conducted an unusually powerful radio survey using both the VLA and MeerKAT telescopes。 Advanced software analyzed millions of signals, filtering out Earth-based interference and other false positives。 No convincing artificial radio transmissions wer
Gold may have a secret self-defense system that helps it resist tarnishing。 Researchers discovered that atoms on gold surfaces reorganize themselves into patterns that block oxygen from reacting with the metal, suppressing oxidation by up to a trillion-fold。 Beyond explaining why gold jewelry stays bright for generations, the finding could help sci
NASA has chosen 41 commercial technology projects that could solve critical challenges for future missions to the Moon and Mars。 From powering lunar outposts to protecting spacecraft from Moon dust, the innovations are designed to push both space exploration and the commercial space economy forward
Scientists have developed a new framework that could finally apply the laws of thermodynamics to real, ever-changing black holes instead of only perfectly stable ones。 The advance may improve our understanding of black hole mergers, evaporation, and the powerful gravitational wave events detected by observatories like LIGO
A new AI-powered blood test could give people a remarkably early warning of serious heart and circulation problems。 Developed by researchers at the University of Hong Kong, CardiOmicScore analyzes thousands of proteins and metabolites to estimate the risk of six major cardiovascular diseases, including heart attack, stroke, heart failure, and atria
Scientists have rewritten the story of gallium after discovering that its unusual atomic bonds re-form at high temperatures, contradicting decades of accepted theory。 The finding changes how researchers explain why the metal melts so easily and behaves unlike almost any other metal。 Beyond solving a long-standing scientific mystery, the work could
Scientists say new technologies have reopened the debate over whether Mars could someday be terraformed, turning a once impossible idea into a serious research topic。 Before anyone tries to reshape the Red Planet, though, researchers say we must understand the risks, including what might be lost if Mars already harbors its own forms of life
Researchers have created cosmic dust from scratch by recreating space-like conditions inside glass tubes。 The dust contains complex carbon-rich molecules built from elements essential to life and produces infrared signals similar to real material found in space。 By studying these laboratory samples, scientists can explore how organic chemistry unfo
The FireSat program can spot wildfires that other satellites miss
A new particle detector called PLATON could replace millions of tiny detector components with a single block of light-producing material。 Using a light-field camera, highly sensitive photon sensors, and AI, it reconstructs particle paths in fast, detailed 3D。 Simulations suggest it could match or surpass today’s best detectors while being far easie
Dark matter may be far more complicated than scientists once believed。 A new study suggests it could consist of at least two different kinds of particles that slowly separate over time, with heavier particles sinking toward the centers of galaxies and lighter ones drifting outward。 This simple idea could explain several puzzling cosmic observations
A new study suggests the brain begins making decisions much earlier than scientists previously thought。 Researchers found that even primary sensory regions are influenced by higher brain areas through rapid feedback loops, rather than simply passing information forward。 This more dynamic view of brain function could help engineers design future AI
Scientists have created a silicon chip that can write dozens of DNA sequences simultaneously using electricity and water-based enzymes, offering a cleaner alternative to conventional DNA manufacturing。 The breakthrough could eventually support portable DNA-writing devices and even massive DNA data storage, although new chemistry will be needed to s
Researchers have achieved a major milestone by creating a long-sought two-dimensional quantum material and confirming its unusual conducting edge states。 The ability to control these states through strain could make the material a promising platform for future room-temperature quantum electronics