Litigation

arXiv:2602.12368v1 Announce Type: new Abstract: This work introduces the Nirenberg Neural Network: a numerical approach to the Nirenberg problem of prescribing Gaussian curvature on $S^2$ for metrics that are pointwise conformal to the round metric. Our mesh-free physics-informed neural network...

arXiv:2602.12520v1 Announce Type: new Abstract: Learning to coordinate many agents in partially observable and highly dynamic environments requires both informative representations and data-efficient training. To address this challenge, we present a novel model-based multi-agent reinforcement learning framework that unifies joint...

arXiv:2602.12533v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) often exhibit significant modality preference, which is a tendency to favor one modality over another. Depending on the input, they may over-rely on linguistic priors relative to visual evidence, or...

arXiv:2602.12542v1 Announce Type: new Abstract: Deep learning models for clinical event prediction on electronic health records (EHR) often suffer performance degradation when deployed under different data distributions. While domain adaptation (DA) methods can mitigate such shifts, its "black-box" nature prevents...

arXiv:2602.12643v1 Announce Type: new Abstract: We present Unified Latent Dynamics (ULD), a novel reinforcement learning algorithm that unifies the efficiency of model-free methods with the representational strengths of model-based approaches, without incurring planning overhead. By embedding state-action pairs into a...

arXiv:2602.12651v1 Announce Type: new Abstract: Cellular identity and function are linked to both their intrinsic genomic makeup and extrinsic spatial context within the tissue microenvironment. Spatial transcriptomics (ST) offers an unprecedented opportunity to study this, providing in situ gene expression...

Abstract This article is a ‘metaphorical’ guide to today’s most pressing artificial intelligence (AI) copyright questions, focusing in particular on the EU and the USA. Is unauthorized training on copyright-protected works permitted? Can AI models copy? And is AI-generated output...

A Republican member of Congress, a group of voters, and New York election officials asked the Supreme Court to allow the state to proceed with the 2026 elections using its […]The postRepublicans urge Supreme Court to restore New York congressional...

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The Center for AI Safety is offering grants for philosophers to pursue research in conceptual AI safety.

The AI Safety, Ethics, and Society Course would be held virtually and be completely free. It would be part-time and we expect that it will require a time commitment of 3-5 hours per week for 10 weeks.