arXiv:2505.17961v2 Announce Type: replace-cross Abstract: Causal inference typically assumes centralized access to individual-level data. Yet, in practice, data are often decentralized across multiple sites, making centralization infeasible due to privacy, logistical, or legal constraints. We address this problem by estimating…
arXiv:2510.00167v1 Announce Type: new Abstract: Autonomous drones must often respond to sudden events, such as alarms, faults, or unexpected changes in their environment, that require immediate and adaptive decision-making. Traditional approaches rely on safety engineers hand-coding large sets of recovery…
arXiv:2510.00185v1 Announce Type: new Abstract: We introduce Slot Attention Argumentation for Case-Based Reasoning (SAA-CBR), a novel neuro-symbolic pipeline for image classification that integrates object-centric learning via a neural Slot Attention (SA) component with symbolic reasoning conducted by Abstract Argumentation for…
arXiv:2510.00088v1 Announce Type: new Abstract: Large language models (LLMs) have been extensively used for legal judgment prediction tasks based on case reports and crime history. However, with a surge in the availability of large vision language models (VLMs), legal judgment…
arXiv:2510.00156v1 Announce Type: new Abstract: Financial fraud detection in real-world scenarios presents significant challenges due to the subtlety and dispersion of evidence across complex, multi-year financial disclosures. In this work, we introduce a novel multi-agent reasoning framework AuditAgent, enhanced with…
arXiv:2510.00084v1 Announce Type: new Abstract: Artificial Intelligence has rapidly become a cornerstone technology, significantly influencing Europe’s societal and economic landscapes. However, the proliferation of AI also raises critical ethical, legal, and regulatory challenges. The CERTAIN (Certification for Ethical and Regulatory…
arXiv:2510.00075v1 Announce Type: new Abstract: Designing wise AI policy is a grand challenge for society. To design such policy, policymakers should place a premium on rigorous evidence and scientific consensus. While several mechanisms exist for evidence generation, and nascent mechanisms…
arXiv:2510.00071v1 Announce Type: new Abstract: Large Reasoning Language Models (LRLMs or LRMs) demonstrate remarkable capabilities in complex reasoning tasks, but suffer from significant computational inefficiencies due to overthinking phenomena. Existing efficient reasoning methods face the challenge of balancing reasoning quality…
arXiv:2505.16928v2 Announce Type: replace Abstract: We introduce $infty$-THOR, a new framework for long-horizon embodied tasks that advances long-context understanding in embodied AI. $infty$-THOR provides: (1) a generation framework for synthesizing scalable, reproducible, and unlimited long-horizon trajectories; (2) a novel embodied…
arXiv:2510.00186v1 Announce Type: new Abstract: Transforming natural-language requests into reliable, production-ready data transformations remains challenging: correctness depends on precise schema linking and warehouse-specific SQL dialects, while the strongest supervision available during training–execution success and result matching–are provided only at the…
