The Skidmore Compromise: Interpreting Skidmore as a Tiebreaker to Preserve Judicial Wisdom in the Era of Loper Bright lawreview - Minnesota Law Review
By MITCHELL ZAIC. Full Text. 'Law must be stable, and yet it cannot stand still.' Here is the great antinomy confronting us at every turn. Rest and motion, unrelieved and unchecked, are equally destructive. The law, like human kind, if...
The Crisis in U.S. Cancer Care: Law, Markets, and Privatization lawreview - Minnesota Law Review
By DANIEL G. AARON. Full Text. Cancer is surging among youth and young adults in the United States, yet, instead of public regulation addressing its root causes, we have outsourced the management of cancer to the private sector. A suite...
Volume 110 – Issue 3 - Minnesota Law Review
Regulatory History and Judicial Review lawreview - Minnesota Law Review
By TODD PHILLIPS & ANTHONY MOFFA. Full Text. The Administrative Procedure Act (APA) requires federal agencies to simply "incorporate in the rules adopted a concise general statement of their basis and purpose" after they receive comments from the public, and...
Trump moves to ban Anthropic from the US government
The Defense Department pressured Anthropic to drop restrictions on how its AI can be used by the military.
The trap Anthropic built for itself
Anthropic, OpenAI, Google DeepMind and others have long promised to govern themselves responsibly. Now, in the absence of rules, there's not a lot to protect them.
Anthropic’s Claude rises to No. 2 in the App Store following Pentagon dispute
Anthropic’s chatbot Claude seems to have benefited from the attention around the company’s fraught negotiations with the Pentagon.
The billion-dollar infrastructure deals powering the AI boom
Here's everything we know about the biggest AI infrastructure projects, including major spending from Meta, Oracle, Microsoft, Google, and OpenAI.
OpenAI’s Sam Altman announces Pentagon deal with ‘technical safeguards’
OpenAI's CEO claims its new defense contract includes protections addressing the same issues that became a flashpoint for Anthropic.
ESG Investing Under Scrutiny: Legal and Regulatory Developments in 2026
ESG investing faces both increased regulatory support in some jurisdictions and political backlash in others, creating a complex compliance landscape.
The Rise of AI-Powered Legal Research: Transforming How Lawyers Work
AI-powered legal research tools are fundamentally changing the practice of law, offering unprecedented efficiency while raising questions about quality and oversight.
CRISPR Gene Therapy Patents: The Legal Battle Reshaping Biotechnology
The ongoing patent disputes surrounding CRISPR gene editing technology have profound implications for biotech innovation, patient access, and IP strategy.
Digital Sovereignty: How Nations Are Asserting Control Over Technology Infrastructure
Countries worldwide are implementing digital sovereignty measures to control data flows, technology standards, and digital infrastructure within their borders.
Zero-Day Vulnerabilities in Enterprise AI Systems: Legal and Technical Implications
The discovery of critical zero-day vulnerabilities in widely deployed AI systems raises urgent questions about cybersecurity liability and disclosure obligations.
Imagination Helps Visual Reasoning, But Not Yet in Latent Space
arXiv:2602.22766v1 Announce Type: new Abstract: Latent visual reasoning aims to mimic human's imagination process by meditating through hidden states of Multimodal Large Language Models. While recognized as a promising paradigm for visual reasoning, the underlying mechanisms driving its effectiveness remain...
Test-Time Scaling with Diffusion Language Models via Reward-Guided Stitching
arXiv:2602.22871v1 Announce Type: new Abstract: Reasoning with large language models often benefits from generating multiple chains-of-thought, but existing aggregation strategies are typically trajectory-level (e.g., selecting the best trace or voting on the final answer), discarding useful intermediate work from partial...
Where Vision Becomes Text: Locating the OCR Routing Bottleneck in Vision-Language Models
arXiv:2602.22918v1 Announce Type: new Abstract: Vision-language models (VLMs) can read text from images, but where does this optical character recognition (OCR) information enter the language processing stream? We investigate the OCR routing mechanism across three architecture families (Qwen3-VL, Phi-4, InternVL3.5)...
Quantity Convergence, Quality Divergence: Disentangling Fluency and Accuracy in L2 Mandarin Prosody
arXiv:2602.23071v1 Announce Type: new Abstract: While second language (L2) learners may acquire target syntactic word order, mapping this syntax onto appropriate prosodic structures remains a persistent challenge. This study investigates the fossilization and stability of the L2 syntax-prosody interface by...
MTRAG-UN: A Benchmark for Open Challenges in Multi-Turn RAG Conversations
arXiv:2602.23184v1 Announce Type: new Abstract: We present MTRAG-UN, a benchmark for exploring open challenges in multi-turn retrieval augmented generation, a popular use of large language models. We release a benchmark of 666 tasks containing over 2,800 conversation turns across 6...
Why Diffusion Language Models Struggle with Truly Parallel (Non-Autoregressive) Decoding?
arXiv:2602.23225v1 Announce Type: new Abstract: Diffusion Language Models (DLMs) are often advertised as enabling parallel token generation, yet practical fast DLMs frequently converge to left-to-right, autoregressive (AR)-like decoding dynamics. In contrast, genuinely non-AR generation is promising because it removes AR's...
SPARTA: Scalable and Principled Benchmark of Tree-Structured Multi-hop QA over Text and Tables
arXiv:2602.23286v1 Announce Type: new Abstract: Real-world Table-Text question answering (QA) tasks require models that can reason across long text and source tables, traversing multiple hops and executing complex operations such as aggregation. Yet existing benchmarks are small, manually curated -...
Improving Spatial Allocation for Energy System Coupling with Graph Neural Networks
arXiv:2602.22249v1 Announce Type: new Abstract: In energy system analysis, coupling models with mismatched spatial resolutions is a significant challenge. A common solution is assigning weights to high-resolution geographic units for aggregation, but traditional models are limited by using only a...
Deep Sequence Modeling with Quantum Dynamics: Language as a Wave Function
arXiv:2602.22255v1 Announce Type: new Abstract: We introduce a sequence modeling framework in which the latent state is a complex-valued wave function evolving on a finite-dimensional Hilbert space under a learned, time-dependent Hamiltonian. Unlike standard recurrent architectures that rely on gating...
Entropy-Controlled Flow Matching
arXiv:2602.22265v1 Announce Type: new Abstract: Modern vision generators transport a base distribution to data through time-indexed measures, implemented as deterministic flows (ODEs) or stochastic diffusions (SDEs). Despite strong empirical performance, standard flow-matching objectives do not directly control the information geometry...
WaveSSM: Multiscale State-Space Models for Non-stationary Signal Attention
arXiv:2602.22266v1 Announce Type: new Abstract: State-space models (SSMs) have emerged as a powerful foundation for long-range sequence modeling, with the HiPPO framework showing that continuous-time projection operators can be used to derive stable, memory-efficient dynamical systems that encode the past...
CQSA: Byzantine-robust Clustered Quantum Secure Aggregation in Federated Learning
arXiv:2602.22269v1 Announce Type: new Abstract: Federated Learning (FL) enables collaborative model training without sharing raw data. However, shared local model updates remain vulnerable to inference and poisoning attacks. Secure aggregation schemes have been proposed to mitigate these attacks. In this...
Positional-aware Spatio-Temporal Network for Large-Scale Traffic Prediction
arXiv:2602.22274v1 Announce Type: new Abstract: Traffic flow forecasting has emerged as an indispensable mission for daily life, which is required to utilize the spatiotemporal relationship between each location within a time period under a graph structure to predict future flow....
OmniZip: Learning a Unified and Lightweight Lossless Compressor for Multi-Modal Data
arXiv:2602.22286v1 Announce Type: new Abstract: Lossless compression is essential for efficient data storage and transmission. Although learning-based lossless compressors achieve strong results, most of them are designed for a single modality, leading to redundant compressor deployments in multi-modal settings. Designing...
Global River Forecasting with a Topology-Informed AI Foundation Model
arXiv:2602.22293v1 Announce Type: new Abstract: River systems operate as inherently interconnected continuous networks, meaning river hydrodynamic simulation ought to be a systemic process. However, widespread hydrology data scarcity often restricts data-driven forecasting to isolated predictions. To achieve systemic simulation and...
When Should a Model Change Its Mind? An Energy-Based Theory and Regularizer for Concept Drift in Electrocardiogram (ECG) Signals
arXiv:2602.22294v1 Announce Type: new Abstract: Models operating on dynamic physiologic signals must distinguish benign, label-preserving variability from true concept change. Existing concept-drift frameworks are largely distributional and provide no principled guidance on how much a model's internal representation may move...