Brady violations, child abduction, qualified immunity, and confessions of error
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. This week, the Supreme Court started […]The postBrady violations, child abduction, qualified immunity, and confessions...
Hegseth, Trump had no authority to order Anthropic to be blacklisted, judge says
“I don’t know”: Department of War fails to justify blacklisting Anthropic.
Conntour raises $7M from General Catalyst, YC to build an AI search engine for security video systems
Conntour uses AI models to let security teams query camera feeds using natural language to find any object, person, or situation.
Berta: an open-source, modular tool for AI-enabled clinical documentation
arXiv:2603.23513v1 Announce Type: new Abstract: Commercial AI scribes cost \$99-600 per physician per month, operate as opaque systems, and do not return data to institutional infrastructure, limiting organizational control over data governance, quality improvement, and clinical workflows. We developed Berta,...
S-Path-RAG: Semantic-Aware Shortest-Path Retrieval Augmented Generation for Multi-Hop Knowledge Graph Question Answering
arXiv:2603.23512v1 Announce Type: new Abstract: We present S-Path-RAG, a semantic-aware shortest-path Retrieval-Augmented Generation framework designed to improve multi-hop question answering over large knowledge graphs. S-Path-RAG departs from one-shot, text-heavy retrieval by enumerating bounded-length, semantically weighted candidate paths using a hybrid...
Infrequent Child-Directed Speech Is Bursty and May Draw Infant Vocalizations
arXiv:2603.23797v1 Announce Type: new Abstract: Children in many parts of the world hear relatively little speech directed to them, yet still reach major language development milestones. What differs about the speech input that infants learn from when directed input is...
StateLinFormer: Stateful Training Enhancing Long-term Memory in Navigation
arXiv:2603.23571v1 Announce Type: new Abstract: Effective navigation intelligence relies on long-term memory to support both immediate generalization and sustained adaptation. However, existing approaches face a dilemma: modular systems rely on explicit mapping but lack flexibility, while Transformer-based end-to-end models are...
Boost Like a (Var)Pro: Trust-Region Gradient Boosting via Variable Projection
arXiv:2603.23658v1 Announce Type: new Abstract: Gradient boosting, a method of building additive ensembles from weak learners, has established itself as a practical and theoretically-motivated approach to approximate functions, especially using decision tree weak learners. Comparable methods for smooth parametric learners,...
Probabilistic Geometric Alignment via Bayesian Latent Transport for Domain-Adaptive Foundation Models
arXiv:2603.23783v1 Announce Type: new Abstract: Adapting large-scale foundation models to new domains with limited supervision remains a fundamental challenge due to latent distribution mismatch, unstable optimization dynamics, and miscalibrated uncertainty propagation. This paper introduces an uncertainty-aware probabilistic latent transport framework...
Circuit Complexity of Hierarchical Knowledge Tracing and Implications for Log-Precision Transformers
arXiv:2603.23823v1 Announce Type: new Abstract: Knowledge tracing models mastery over interconnected concepts, often organized by prerequisites. We analyze hierarchical prerequisite propagation through a circuit-complexity lens to clarify what is provable about transformer-style computation on deep concept hierarchies. Using recent results...
An Invariant Compiler for Neural ODEs in AI-Accelerated Scientific Simulation
arXiv:2603.23861v1 Announce Type: new Abstract: Neural ODEs are increasingly used as continuous-time models for scientific and sensor data, but unconstrained neural ODEs can drift and violate domain invariants (e.g., conservation laws), yielding physically implausible solutions. In turn, this can compound...
Off-Policy Safe Reinforcement Learning with Constrained Optimistic Exploration
arXiv:2603.23889v1 Announce Type: new Abstract: When safety is formulated as a limit of cumulative cost, safe reinforcement learning (RL) aims to learn policies that maximize return subject to the cost constraint in data collection and deployment. Off-policy safe RL methods,...
Birthright citizenship: more on Pete Patterson’s claims
Attorney Pete Patterson’s latest post on birthright citizenship repeats the biggest mistakes of his original post and also makes some new mistakes, chasing irrelevances and mangling the key legal issues. […]The postBirthright citizenship: more on Pete Patterson’s claimsappeared first onSCOTUSblog.
Court to consider ability of federal courts to confirm arbitration awards
Next week’s argument in Jules v Andre Balazs Properties considers a technical question about the jurisdiction of federal courts to enforce an arbitration award. It is the immediate successor of […]The postCourt to consider ability of federal courts to confirm...
Justices dubious about “harsh” rules for omissions by bankrupt debtors
Yesterday’s argument in Keathley v. Buddy Ayers Construction displayed a bench almost uniformly skeptical of a lower court’s absolute standard for responding to the failure of a debtor in bankruptcy […]The postJustices dubious about “harsh” rules for omissions by bankrupt...
Justices to hear argument on whether a crime’s “contemplated effects” can expand venue beyond where offense was committed
The Supreme Court will hear oral argument on Monday in Abouammo v. United States, in which it will consider whether federal prosecutors can try a defendant not only in the […]The postJustices to hear argument on whether a crime’s “contemplated...
The Supreme Court and voting identification
Courtly Observations is a recurring series by Erwin Chemerinsky that focuses on what the Supreme Court’s decisions will mean for the law, for lawyers and lower courts, and for people’s lives. […]The postThe Supreme Court and voting identificationappeared first onSCOTUSblog.
SCOTUStoday for Wednesday, March 25
It’s going to be another busy day at the Supreme Court, and it’s expected to start with opinion announcements.The postSCOTUStoday for Wednesday, March 25appeared first onSCOTUSblog.
Intelligence Inertia: Physical Principles and Applications
arXiv:2603.22347v1 Announce Type: new Abstract: While Landauer's principle establishes the fundamental thermodynamic floor for information erasure and Fisher Information provides a metric for local curvature in parameter space, these classical frameworks function effectively only as approximations within regimes of sparse...
AI Mental Models: Learned Intuition and Deliberation in a Bounded Neural Architecture
arXiv:2603.22561v1 Announce Type: new Abstract: This paper asks whether a bounded neural architecture can exhibit a meaningful division of labor between intuition and deliberation on a classic 64-item syllogistic reasoning benchmark. More broadly, the benchmark is relevant to ongoing debates...
STEM Agent: A Self-Adapting, Tool-Enabled, Extensible Architecture for Multi-Protocol AI Agent Systems
arXiv:2603.22359v1 Announce Type: new Abstract: Current AI agent frameworks commit early to a single interaction protocol, a fixed tool integration strategy, and static user models, limiting their deployment across diverse interaction paradigms. To address these constraints, we introduce STEM Agent...
Describe-Then-Act: Proactive Agent Steering via Distilled Language-Action World Models
arXiv:2603.23149v1 Announce Type: new Abstract: Deploying safety-critical agents requires anticipating the consequences of actions before they are executed. While world models offer a paradigm for this proactive foresight, current approaches relying on visual simulation incur prohibitive latencies, often exceeding several...
From Static Templates to Dynamic Runtime Graphs: A Survey of Workflow Optimization for LLM Agents
arXiv:2603.22386v1 Announce Type: new Abstract: Large language model (LLM)-based systems are becoming increasingly popular for solving tasks by constructing executable workflows that interleave LLM calls, information retrieval, tool use, code execution, memory updates, and verification. This survey reviews recent methods...
ABSTRAL: Automatic Design of Multi-Agent Systems Through Iterative Refinement and Topology Optimization
arXiv:2603.22791v1 Announce Type: new Abstract: How should multi-agent systems be designed, and can that design knowledge be captured in a form that is inspectable, revisable, and transferable? We introduce ABSTRAL, a framework that treats MAS architecture as an evolving natural-language...
Reddit After Roe: A Computational Analysis of Abortion Narratives and Barriers in the Wake of Dobbs
arXiv:2603.22566v1 Announce Type: new Abstract: The 2022 U.S. Supreme Court decision in Dobbs v. Jackson Women's Health Organization reshaped the reproductive rights landscape, introducing new uncertainty and barriers to abortion access. We present a large-scale computational analysis of abortion discourse...
SAiW: Source-Attributable Invisible Watermarking for Proactive Deepfake Defense
arXiv:2603.23178v1 Announce Type: new Abstract: Deepfakes generated by modern generative models pose a serious threat to information integrity, digital identity, and public trust. Existing detection methods are largely reactive, attempting to identify manipulations after they occur and often failing to...
Beyond Hate: Differentiating Uncivil and Intolerant Speech in Multimodal Content Moderation
arXiv:2603.22985v1 Announce Type: new Abstract: Current multimodal toxicity benchmarks typically use a single binary hatefulness label. This coarse approach conflates two fundamentally different characteristics of expression: tone and content. Drawing on communication science theory, we introduce a fine-grained annotation scheme...
HGNet: Scalable Foundation Model for Automated Knowledge Graph Generation from Scientific Literature
arXiv:2603.23136v1 Announce Type: new Abstract: Automated knowledge graph (KG) construction is essential for navigating the rapidly expanding body of scientific literature. However, existing approaches struggle to recognize long multi-word entities, often fail to generalize across domains, and typically overlook the...
Beyond Hard Constraints: Budget-Conditioned Reachability For Safe Offline Reinforcement Learning
arXiv:2603.22292v1 Announce Type: new Abstract: Sequential decision making using Markov Decision Process underpins many realworld applications. Both model-based and model free methods have achieved strong results in these settings. However, real-world tasks must balance reward maximization with safety constraints, often...
CN-Buzz2Portfolio: A Chinese-Market Dataset and Benchmark for LLM-Based Macro and Sector Asset Allocation from Daily Trending Financial News
arXiv:2603.22305v1 Announce Type: new Abstract: Large Language Models (LLMs) are rapidly transitioning from static Natural Language Processing (NLP) tasks including sentiment analysis and event extraction to acting as dynamic decision-making agents in complex financial environments. However, the evolution of LLMs...