arXiv:2509.17544v2 Announce Type: replace Abstract: The increasing availability of open Earth Observation (EO) and agricultural datasets holds great potential for supporting sustainable land management. However, their high technical entry barrier limits accessibility for non-expert users. This study presents an open-source…
arXiv:2509.19088v1 Announce Type: cross Abstract: Do “digital twins” capture individual responses in surveys and experiments? We run 19 pre-registered studies on a national U.S. panel and their LLM-powered digital twins (constructed based on previously-collected extensive individual-level data) and compare twin…
arXiv:2509.19212v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) are increasingly deployed in real-world applications, yet their ability to make context-aware safety decisions remains limited. Existing methods often fail to balance oversensitivity (unjustified refusals of benign queries) and undersensitivity…
arXiv:2509.02783v2 Announce Type: replace-cross Abstract: We present the Transparent Earth, a transformer-based architecture for reconstructing subsurface properties from heterogeneous datasets that vary in sparsity, resolution, and modality, where each modality represents a distinct type of observation (e.g., stress angle, mantle…
arXiv:2509.18874v1 Announce Type: cross Abstract: Automated ad targeting on social media is opaque, creating risks of exploitation and invisibility to external scrutiny. Users may be steered toward harmful content while independent auditing of these processes remains blocked. Large Language Models…
arXiv:2509.18186v1 Announce Type: new Abstract: Most educational recommender systems are tuned and judged on click- or rating-based relevance, leaving their true pedagogical impact unclear. We introduce OBER-an Outcome-Based Educational Recommender that embeds learning outcomes and assessment items directly into the…
arXiv:2509.18198v1 Announce Type: new Abstract: Autonomous systems have advanced significantly, but challenges persist in accident-prone environments where robust decision-making is crucial. A single vehicle’s limited sensor range and obstructed views increase the likelihood of accidents. Multi-vehicle connected systems and multi-modal…
arXiv:2509.18180v1 Announce Type: new Abstract: Operations research (OR) provides fundamental methodologies for complex system decision-making, with established applications in transportation, supply chain management, and production scheduling. Traditional approaches, which depend on expert-based modeling and manual parameter adjustment, often face challenges…
arXiv:2509.18181v1 Announce Type: new Abstract: Accurate modeling of ridesourcing mode choices is essential for designing and implementing effective traffic management policies for reducing congestion, improving mobility, and allocating resources more efficiently. Existing models for predicting ridesourcing mode choices often suffer…
arXiv:2509.18178v1 Announce Type: new Abstract: Computational Fluid Dynamics (CFD) is an essential simulation tool in engineering, yet its steep learning curve and complex manual setup create significant barriers. To address these challenges, we introduce Foam-Agent, a multi-agent framework that automates…
