Justices to consider rules pardoning omissions by bankrupt debtors
Next week’s argument in Keathley v. Buddy Ayers Construction involves a technical question about bankruptcy procedure – the standards for overlooking the failure of a debtor in bankruptcy to mention […]The postJustices to consider rules pardoning omissions by bankrupt debtorsappeared...
Uninjured class members, hindsight harmlessness, presidential cronies, and the mistaken use of deadly force
The Relist Watch column examines cert petitions that the Supreme Court has “relisted” for its upcoming conference. A short explanation of relists is available here. There are 261 petitions and applications […]The postUninjured class members, hindsight harmlessness, presidential cronies, and...
Volume 2026, No. 1 – Wisconsin Law Review – UW–Madison
Contract Law and Civil Justice in Local Courts by Cathy Hwang & Justin Weinstein-Tull; Preempting Drug Price Reform by Shweta Kumar; Lessons Learned? COVID’s Continued Impact on Remote Work Disability Accommodations by D’Andra Millsap Shu; Unbundling AI Openness by Parth...
The State of Charity Care in the United States: Holding Nonprofit Hospitals Accountable for Their Tax Exemptions
Introduction A health system in the Midwest withholds medical care from patients who have $4,500 or more of unpaid debt.[1] A busy university hospital in Manhattan has emergency room nurses redirecting homeless patients to a public hospital that primarily serves...
Catching Pokémon, Not Tax Bills
Introduction What if we told you that you could play a unique and magical game for free? What if we told you this game would let you chase fantastical creatures across your neighborhood, turning your daily stroll into an epic...
On the Cone Effect and Modality Gap in Medical Vision-Language Embeddings
arXiv:2603.17246v1 Announce Type: new Abstract: Vision-Language Models (VLMs) exhibit a characteristic "cone effect" in which nonlinear encoders map embeddings into highly concentrated regions of the representation space, contributing to cross-modal separation known as the modality gap. While this phenomenon has...
SCALE:Scalable Conditional Atlas-Level Endpoint transport for virtual cell perturbation prediction
arXiv:2603.17380v1 Announce Type: new Abstract: Virtual cell models aim to enable in silico experimentation by predicting how cells respond to genetic, chemical, or cytokine perturbations from single-cell measurements. In practice, however, large-scale perturbation prediction remains constrained by three coupled bottlenecks:...
Large-Scale 3D Ground-Motion Synthesis with Physics-Inspired Latent Operator Flow Matching
arXiv:2603.17403v1 Announce Type: new Abstract: Earthquake hazard analysis and design of spatially distributed infrastructure, such as power grids and energy pipeline networks, require scenario-specific ground-motion time histories with realistic frequency content and spatiotemporal coherence. However, producing the large ensembles needed...
TimeAPN: Adaptive Amplitude-Phase Non-Stationarity Normalization for Time Series Forecasting
arXiv:2603.17436v1 Announce Type: new Abstract: Non-stationarity is a fundamental challenge in multivariate long-term time series forecasting, often manifested as rapid changes in amplitude and phase. These variations lead to severe distribution shifts and consequently degrade predictive performance. Existing normalization-based methods...
SCOTUStoday for Wednesday, March 18
Should the White House look more like the Supreme Court Building? The chairman of the Commission of Fine Arts, Rodney Mims Cook, Jr., has suggested swapping the White House’s “graceful […]The postSCOTUStoday for Wednesday, March 18appeared first onSCOTUSblog.
DOD says Anthropic’s ‘red lines’ make it an ‘unacceptable risk to national security’
The Defense Department said concerns that Anthropic might "attempt to disable its technology" during "warfighting operations" validate its decision to label the AI firm a supply-chain risk.
Optimizing Hospital Capacity During Pandemics: A Dual-Component Framework for Strategic Patient Relocation
arXiv:2603.15960v1 Announce Type: new Abstract: The COVID-19 pandemic has placed immense strain on hospital systems worldwide, leading to critical capacity challenges. This research proposes a two-part framework to optimize hospital capacity through patient relocation strategies. The first component involves developing...
AsgardBench - Evaluating Visually Grounded Interactive Planning Under Minimal Feedback
arXiv:2603.15888v1 Announce Type: new Abstract: With AsgardBench we aim to evaluate visually grounded, high-level action sequence generation and interactive planning, focusing specifically on plan adaptation during execution based on visual observations rather than navigation or low-level manipulation. In the landscape...
SQL-ASTRA: Alleviating Sparse Feedback in Agentic SQL via Column-Set Matching and Trajectory Aggregation
arXiv:2603.16161v1 Announce Type: new Abstract: Agentic Reinforcement Learning (RL) shows promise for complex tasks, but Text-to-SQL remains mostly restricted to single-turn paradigms. A primary bottleneck is the credit assignment problem. In traditional paradigms, rewards are determined solely by the final-turn...
CounterRefine: Answer-Conditioned Counterevidence Retrieval for Inference-Time Knowledge Repair in Factual Question Answering
arXiv:2603.16091v1 Announce Type: new Abstract: In factual question answering, many errors are not failures of access but failures of commitment: the system retrieves relevant evidence, yet still settles on the wrong answer. We present CounterRefine, a lightweight inference-time repair layer...
Spectral Edge Dynamics of Training Trajectories: Signal--Noise Geometry Across Scales
arXiv:2603.15678v1 Announce Type: new Abstract: Despite hundreds of millions of parameters, transformer training trajectories evolve within only a few coherent directions. We introduce \emph{Spectral Edge Dynamics} (SED) to measure this structure: rolling-window SVD of parameter updates reveals a sharp boundary...
Evidential Domain Adaptation for Remaining Useful Life Prediction with Incomplete Degradation
arXiv:2603.15687v1 Announce Type: new Abstract: Accurate Remaining Useful Life (RUL) prediction without labeled target domain data is a critical challenge, and domain adaptation (DA) has been widely adopted to address it by transferring knowledge from a labeled source domain to...
Mastering the Minority: An Uncertainty-guided Multi-Expert Framework for Challenging-tailed Sequence Learning
arXiv:2603.15708v1 Announce Type: new Abstract: Imbalanced data distribution remains a critical challenge in sequential learning, leading models to easily recognize frequent categories while failing to detect minority classes adequately. The Mixture-of-Experts model offers a scalable solution, yet its application is...
Discovery of interaction and diffusion kernels in particle-to-mean-field multi-agent systems
arXiv:2603.15927v1 Announce Type: new Abstract: We propose a data-driven framework to learn interaction kernels in stochastic multi-agent systems. Our approach aims at identifying the functional form of nonlocal interaction and diffusion terms directly from trajectory data, without any a priori...
Residual Stream Duality in Modern Transformer Architectures
arXiv:2603.16039v1 Announce Type: new Abstract: Recent work has made clear that the residual pathway is not mere optimization plumbing; it is part of the model's representational machinery. We agree, but argue that the cleanest way to organize this design space...
MDM-Prime-v2: Binary Encoding and Index Shuffling Enable Compute-optimal Scaling of Diffusion Language Models
arXiv:2603.16077v1 Announce Type: new Abstract: Masked diffusion models (MDM) exhibit superior generalization when learned using a Partial masking scheme (Prime). This approach converts tokens into sub-tokens and models the diffusion process at the sub-token level. We identify two limitations of...
The remaining questions after the Supreme Court’s tariffs ruling
Last month, the Supreme Court ruled that the International Emergency Economic Powers Act, a 1977 law giving the president the power to regulate commerce during national emergencies created by foreign […]The postThe remaining questions after the Supreme Court’s tariffs rulingappeared...
OpenAI expands government footprint with AWS deal, report says
OpenAI has reportedly signed a partnership with AWS to sell its AI systems to the U.S. government for classified and unclassified work, marking an expansion beyond its Pentagon deal last month.
Why Grokking Takes So Long: A First-Principles Theory of Representational Phase Transitions
arXiv:2603.13331v1 Announce Type: new Abstract: Grokking is the sudden generalization that appears long after a model has perfectly memorized its training data. Although this phenomenon has been widely observed, there is still no quantitative theory explaining the length of the...
Multi-Axis Trust Modeling for Interpretable Account Hijacking Detection
arXiv:2603.13246v1 Announce Type: new Abstract: This paper proposes a Hadith-inspired multi-axis trust modeling framework, motivated by a structurally analogous problem in classical Hadith scholarship: assessing the trustworthiness of information sources using interpretable, multidimensional criteria rather than a single anomaly score....
GroupGuard: A Framework for Modeling and Defending Collusive Attacks in Multi-Agent Systems
arXiv:2603.13940v1 Announce Type: new Abstract: While large language model-based agents demonstrate great potential in collaborative tasks, their interactivity also introduces security vulnerabilities. In this paper, we propose and model group collusive attacks, a highly destructive threat in which multiple agents...
Automating Document Intelligence in Statutory City Planning
arXiv:2603.13245v1 Announce Type: new Abstract: UK planning authorities face a legislative conflict between the Planning Act, which mandates public access to application documents, and the Data Protection Act, which requires protection of personal information. This situation creates a manually intensive...
When Alpha Breaks: Two-Level Uncertainty for Safe Deployment of Cross-Sectional Stock Rankers
arXiv:2603.13252v1 Announce Type: new Abstract: Cross-sectional ranking models are often deployed as if point predictions were sufficient: the model outputs scores and the portfolio follows the induced ordering. Under non-stationarity, rankers can fail during regime shifts. In the AI Stock...
From Refusal Tokens to Refusal Control: Discovering and Steering Category-Specific Refusal Directions
arXiv:2603.13359v1 Announce Type: new Abstract: Language models are commonly fine-tuned for safety alignment to refuse harmful prompts. One approach fine-tunes them to generate categorical refusal tokens that distinguish different refusal types before responding. In this work, we leverage a version...
How Transformers Reject Wrong Answers: Rotational Dynamics of Factual Constraint Processing
arXiv:2603.13259v1 Announce Type: new Abstract: When a language model is fed a wrong answer, what happens inside the network? Current understanding treats truthfulness as a static property of individual-layer representations-a direction to be probed, a feature to be extracted. Less...