Justices seem dubious of government’s argument in criminal venue case
The Supreme Court on Monday considered whether federal prosecutors can try a defendant not only in the district where the offense occurs, but also where the crime’s “contemplated effects” are […]The postJustices seem dubious of government’s argument in criminal venue...
Court repudiates extension of federal supervised release while a defendant absconds
After completing a term of imprisonment, federal criminal defendants often serve terms of supervised release that usually last between one to five years, depending on the offense for which they […]The postCourt repudiates extension of federal supervised release while a...
Anthropic wins injunction against Trump administration over Defense Department saga
A federal judge has ordered that the Trump administration rescind recent restrictions it placed on the AI company.
MedMT-Bench: Can LLMs Memorize and Understand Long Multi-Turn Conversations in Medical Scenarios?
arXiv:2603.23519v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated impressive capabilities across various specialist domains and have been integrated into high-stakes areas such as medicine. However, as existing medical-related benchmarks rarely stress-test the long-context memory, interference robustness, and...
PoiCGAN: A Targeted Poisoning Based on Feature-Label Joint Perturbation in Federated Learning
arXiv:2603.23574v1 Announce Type: new Abstract: Federated Learning (FL), as a popular distributed learning paradigm, has shown outstanding performance in improving computational efficiency and protecting data privacy, and is widely applied in industrial image classification. However, due to its distributed nature,...
LineMVGNN: Anti-Money Laundering with Line-Graph-Assisted Multi-View Graph Neural Networks
arXiv:2603.23584v1 Announce Type: new Abstract: Anti-money laundering (AML) systems are important for protecting the global economy. However, conventional rule-based methods rely on domain knowledge, leading to suboptimal accuracy and a lack of scalability. Graph neural networks (GNNs) for digraphs (directed...
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...
Chain-of-Authorization: Internalizing Authorization into Large Language Models via Reasoning Trajectories
arXiv:2603.22869v1 Announce Type: new Abstract: Large Language Models (LLMs) have become core cognitive components in modern artificial intelligence (AI) systems, combining internal knowledge with external context to perform complex tasks. However, LLMs typically treat all accessible data indiscriminately, lacking inherent...
ARYA: A Physics-Constrained Composable & Deterministic World Model Architecture
arXiv:2603.21340v1 Announce Type: new Abstract: This paper presents ARYA, a composable, physics-constrained, deterministic world model architecture built on five foundational principles: nano models, composability, causal reasoning, determinism, and architectural AI safety. We demonstrate that ARYA satisfies all canonical world model...
The production of meaning in the processing of natural language
arXiv:2603.20381v1 Announce Type: new Abstract: Understanding the fundamental mechanisms governing the production of meaning in the processing of natural language is critical for designing safe, thoughtful, engaging, and empowering human-agent interactions. Experiments in cognitive science and social psychology have demonstrated...
Alignment Whack-a-Mole : Finetuning Activates Verbatim Recall of Copyrighted Books in Large Language Models
arXiv:2603.20957v1 Announce Type: new Abstract: Frontier LLM companies have repeatedly assured courts and regulators that their models do not store copies of training data. They further rely on safety alignment strategies via RLHF, system prompts, and output filters to block...
Graph-Aware Text-Only Backdoor Poisoning for Text-Attributed Graphs
arXiv:2603.20339v1 Announce Type: new Abstract: Many learning systems now use graph data in which each node also contains text, such as papers with abstracts or users with posts. Because these texts often come from open platforms, an attacker may be...
Spatio-Temporal Grid Intelligence: A Hybrid Graph Neural Network and LSTM Framework for Robust Electricity Theft Detection
arXiv:2603.20488v1 Announce Type: new Abstract: Electricity theft, or non-technical loss (NTL), presents a persistent threat to global power systems, driving significant financial deficits and compromising grid stability. Conventional detection methodologies, predominantly reactive and meter-centric, often fail to capture the complex...
LJ-Bench: Ontology-Based Benchmark for U.S. Crime
arXiv:2603.20572v1 Announce Type: new Abstract: The potential of Large Language Models (LLMs) to provide harmful information remains a significant concern due to the vast breadth of illegal queries they may encounter. Unfortunately, existing benchmarks only focus on a handful types...
As teens await sentencing for nudifying girls, parents aim to sue school
Teens will be sentenced Wednesday after admitting to creating AI CSAM.
Elizabeth Warren calls Pentagon’s decision to bar Anthropic ‘retaliation’
In a letter to Defense Secretary Pete Hegseth, Senator Elizabeth Warren (D-MA) equated the DOD's decision to label Anthropic a "supply-chain risk" as retaliation, arguing that the Pentagon could simply have terminated its contract with the AI lab.
Jury finds Musk owes damages to Twitter investors for his tweets
The verdict, while not a complete loss, could still cost him billions.
MedForge: Interpretable Medical Deepfake Detection via Forgery-aware Reasoning
arXiv:2603.18577v1 Announce Type: new Abstract: Text-guided image editors can now manipulate authentic medical scans with high fidelity, enabling lesion implantation/removal that threatens clinical trust and safety. Existing defenses are inadequate for healthcare. Medical detectors are largely black-box, while MLLM-based explainers...
When Names Change Verdicts: Intervention Consistency Reveals Systematic Bias in LLM Decision-Making
arXiv:2603.18530v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for high-stakes decisions, yet their susceptibility to spurious features remains poorly characterized. We introduce ICE-Guard, a framework applying intervention consistency testing to detect three types of spurious feature...
Beyond Passive Aggregation: Active Auditing and Topology-Aware Defense in Decentralized Federated Learning
arXiv:2603.18538v1 Announce Type: new Abstract: Decentralized Federated Learning (DFL) remains highly vulnerable to adaptive backdoor attacks designed to bypass traditional passive defense metrics. To address this limitation, we shift the defensive paradigm toward a novel active, interventional auditing framework. First,...
Does the Supreme Court have a strong “unitary” judicial power?
ScotusCrim is a recurring series by Rory Little focusing on intersections between the Supreme Court and criminal law. The first sentence of Article II of the Constitution introduces the executive […]The postDoes the Supreme Court have a strong “unitary” judicial...
Patreon CEO calls AI companies’ fair use argument ‘bogus,’ says creators should be paid
Patreon CEO Jack Conte says AI companies should pay creators for training data, arguing their fair use defense falls apart when they license content from major publishers.
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.
MOSAIC: Composable Safety Alignment with Modular Control Tokens
arXiv:2603.16210v1 Announce Type: new Abstract: Safety alignment in large language models (LLMs) is commonly implemented as a single static policy embedded in model parameters. However, real-world deployments often require context-dependent safety rules that vary across users, regions, and applications. Existing...
DynaTrust: Defending Multi-Agent Systems Against Sleeper Agents via Dynamic Trust Graphs
arXiv:2603.15661v1 Announce Type: new Abstract: Large Language Model-based Multi-Agent Systems (MAS) have demonstrated remarkable collaborative reasoning capabilities but introduce new attack surfaces, such as the sleeper agent, which behave benignly during routine operation and gradually accumulate trust, only revealing malicious...
Steering Frozen LLMs: Adaptive Social Alignment via Online Prompt Routing
arXiv:2603.15647v1 Announce Type: new Abstract: Large language models (LLMs) are typically governed by post-training alignment (e.g., RLHF or DPO), which yields a largely static policy during deployment and inference. However, real-world safety is a full-lifecycle problem: static defenses degrade against...
Beyond Reward Suppression: Reshaping Steganographic Communication Protocols in MARL via Dynamic Representational Circuit Breaking
arXiv:2603.15655v1 Announce Type: new Abstract: In decentralized Multi-Agent Reinforcement Learning (MARL), steganographic collusion -- where agents develop private protocols to evade monitoring -- presents a critical AI safety threat. Existing defenses, limited to behavioral or reward layers, fail to detect...
Game-Theory-Assisted Reinforcement Learning for Border Defense: Early Termination based on Analytical Solutions
arXiv:2603.15907v1 Announce Type: new Abstract: Game theory provides the gold standard for analyzing adversarial engagements, offering strong optimality guarantees. However, these guarantees often become brittle when assumptions such as perfect information are violated. Reinforcement learning (RL), by contrast, is adaptive...
A Depth-Aware Comparative Study of Euclidean and Hyperbolic Graph Neural Networks on Bitcoin Transaction Systems
arXiv:2603.16080v1 Announce Type: new Abstract: Bitcoin transaction networks are large scale socio- technical systems in which activities are represented through multi-hop interaction patterns. Graph Neural Networks(GNNs) have become a widely adopted tool for analyzing such systems, supporting tasks such as...
Arizona indicts prediction market Kalshi for running illegal gambling operation
Desert state becomes first to file criminal case against prediction platform.