Duality Models: An Embarrassingly Simple One-step Generation Paradigm
arXiv:2602.17682v1 Announce Type: new Abstract: Consistency-based generative models like Shortcut and MeanFlow achieve impressive results via a target-aware design for solving the Probability Flow ODE (PF-ODE). Typically, such methods introduce a target time $r$ alongside the current time $t$ to...
AnCoder: Anchored Code Generation via Discrete Diffusion Models
arXiv:2602.17688v1 Announce Type: new Abstract: Diffusion language models offer a compelling alternative to autoregressive code generation, enabling global planning and iterative refinement of complex program logic. However, existing approaches fail to respect the rigid structure of programming languages and, as...
Parallel Complex Diffusion for Scalable Time Series Generation
arXiv:2602.17706v1 Announce Type: new Abstract: Modeling long-range dependencies in time series generation poses a fundamental trade-off between representational capacity and computational efficiency. Traditional temporal diffusion models suffer from local entanglement and the $\mathcal{O}(L^2)$ cost of attention mechanisms. We address these...
Provable Adversarial Robustness in In-Context Learning
arXiv:2602.17743v1 Announce Type: new Abstract: Large language models adapt to new tasks through in-context learning (ICL) without parameter updates. Current theoretical explanations for this capability assume test tasks are drawn from a distribution similar to that seen during pretraining. This...
Grassmannian Mixture-of-Experts: Concentration-Controlled Routing on Subspace Manifolds
arXiv:2602.17798v1 Announce Type: new Abstract: Mixture-of-Experts models rely on learned routers to assign tokens to experts, yet standard softmax gating provides no principled mechanism to control the tradeoff between sparsity and utilization. We propose Grassmannian MoE (GrMoE), a routing framework...
MePoly: Max Entropy Polynomial Policy Optimization
arXiv:2602.17832v1 Announce Type: new Abstract: Stochastic Optimal Control provides a unified mathematical framework for solving complex decision-making problems, encompassing paradigms such as maximum entropy reinforcement learning(RL) and imitation learning(IL). However, conventional parametric policies often struggle to represent the multi-modality of...
Two Calm Ends and the Wild Middle: A Geometric Picture of Memorization in Diffusion Models
arXiv:2602.17846v1 Announce Type: new Abstract: Diffusion models generate high-quality samples but can also memorize training data, raising serious privacy concerns. Understanding the mechanisms governing when memorization versus generalization occurs remains an active area of research. In particular, it is unclear...
JAX-Privacy: A library for differentially private machine learning
arXiv:2602.17861v1 Announce Type: new Abstract: JAX-Privacy is a library designed to simplify the deployment of robust and performant mechanisms for differentially private machine learning. Guided by design principles of usability, flexibility, and efficiency, JAX-Privacy serves both researchers requiring deep customization...
Breaking the Correlation Plateau: On the Optimization and Capacity Limits of Attention-Based Regressors
arXiv:2602.17898v1 Announce Type: new Abstract: Attention-based regression models are often trained by jointly optimizing Mean Squared Error (MSE) loss and Pearson correlation coefficient (PCC) loss, emphasizing the magnitude of errors and the order or shape of targets, respectively. A common...
Court grapples with disputes over efforts to recover losses from Cuban confiscations
In a pair of oral arguments on Monday, the Supreme Court wrestled with disputes over whether U.S. companies can recover under U.S. law for losses resulting from the confiscation of […]The postCourt grapples with disputes over efforts to recover losses...
Birthright citizenship: under the flag
Brothers in Law is a recurring series by brothers Akhil and Vikram Amar, with special emphasis on measuring what the Supreme Court says against what the Constitution itself says. For more content from […]The postBirthright citizenship: under the flagappeared first...
A Meta AI security researcher said an OpenClaw agent ran amok on her inbox
The viral X post from an AI security researcher reads like satire. But it's really a word of warning about what can go wrong when handing tasks to an AI agent.
With AI, investor loyalty is (almost) dead: At least a dozen OpenAI VCs now also back Anthropic
While some dual investors are understandable, others were more shocking, and signal the disregard of a longstanding ethical conflict-of-interest rule.
Anthropic accuses Chinese AI labs of mining Claude as US debates AI chip exports
Anthropic accuses DeepSeek, Moonshot, and MiniMax of using 24,000 fake accounts to distill Claude’s AI capabilities, as U.S. officials debate export controls aimed at slowing China’s AI progress.
Google’s Cloud AI leads on the three frontiers of model capability
AI models are pushing against three frontiers at once: raw intelligence, response time, and a third quality you might call "extensibility."
Particle’s AI news app listens to podcasts for interesting clips so you you don’t have to
AI news app Particle can now pull in key moments from podcasts, letting readers instantly play short, relevant clips alongside related stories.
Spotify rolls out AI-powered Prompted Playlists to the UK and other markets
Spotify continues to test its AI-powered “Prompted Playlist” feature, now rolling out the tool to Premium subscribers in the U.K., Ireland, Australia, and Sweden.
5 days left to lock in the lowest TechCrunch Disrupt 2026 ticket rates
Five days to save up to $680 on your TechCrunch Disrupt 2026 ticket. These lowest rates of the year disappear on February 27 at 11:59 p.m. PT.
How AI agents could destroy the economy
Citrini Research imagines a report from two years in the future, in which unemployment has doubled and the total value of the stock market has fallen by more than a third.
Defense Secretary summons Anthropic’s Amodei over military use of Claude
Defense Secretary Pete Hegseth has summoned Anthropic CEO Dario Amodei to the Pentagon for a tense discussion over the military's use of Claude. Hegseth has threatened to designate Anthropic a "supply chain risk."
Enhancing Diversity and Feasibility: Joint Population Synthesis from Multi-source Data Using Generative Models
arXiv:2602.15270v1 Announce Type: new Abstract: Generating realistic synthetic populations is essential for agent-based models (ABM) in transportation and urban planning. Current methods face two major limitations. First, many rely on a single dataset or follow a sequential data fusion and...
When Remembering and Planning are Worth it: Navigating under Change
arXiv:2602.15274v1 Announce Type: new Abstract: We explore how different types and uses of memory can aid spatial navigation in changing uncertain environments. In the simple foraging task we study, every day, our agent has to find its way from its...
X-MAP: eXplainable Misclassification Analysis and Profiling for Spam and Phishing Detection
arXiv:2602.15298v1 Announce Type: new Abstract: Misclassifications in spam and phishing detection are very harmful, as false negatives expose users to attacks while false positives degrade trust. Existing uncertainty-based detectors can flag potential errors, but possibly be deceived and offer limited...
World-Model-Augmented Web Agents with Action Correction
arXiv:2602.15384v1 Announce Type: new Abstract: Web agents based on large language models have demonstrated promising capability in automating web tasks. However, current web agents struggle to reason out sensible actions due to the limitations of predicting environment changes, and might...
Common Belief Revisited
arXiv:2602.15403v1 Announce Type: new Abstract: Contrary to common belief, common belief is not KD4. If individual belief is KD45, common belief does indeed lose the 5 property and keep the D and 4 properties -- and it has none of...
RUVA: Personalized Transparent On-Device Graph Reasoning
arXiv:2602.15553v1 Announce Type: new Abstract: The Personal AI landscape is currently dominated by "Black Box" Retrieval-Augmented Generation. While standard vector databases offer statistical matching, they suffer from a fundamental lack of accountability: when an AI hallucinates or retrieves sensitive data,...
How Vision Becomes Language: A Layer-wise Information-Theoretic Analysis of Multimodal Reasoning
arXiv:2602.15580v1 Announce Type: new Abstract: When a multimodal Transformer answers a visual question, is the prediction driven by visual evidence, linguistic reasoning, or genuinely fused cross-modal computation -- and how does this structure evolve across layers? We address this question...
On inferring cumulative constraints
arXiv:2602.15635v1 Announce Type: new Abstract: Cumulative constraints are central in scheduling with constraint programming, yet propagation is typically performed per constraint, missing multi-resource interactions and causing severe slowdowns on some benchmarks. I present a preprocessing method for inferring additional cumulative...
CARE Drive A Framework for Evaluating Reason-Responsiveness of Vision Language Models in Automated Driving
arXiv:2602.15645v1 Announce Type: new Abstract: Foundation models, including vision language models, are increasingly used in automated driving to interpret scenes, recommend actions, and generate natural language explanations. However, existing evaluation methods primarily assess outcome based performance, such as safety and...
Recursive Concept Evolution for Compositional Reasoning in Large Language Models
arXiv:2602.15725v1 Announce Type: new Abstract: Large language models achieve strong performance on many complex reasoning tasks, yet their accuracy degrades sharply on benchmarks that require compositional reasoning, including ARC-AGI-2, GPQA, MATH, BBH, and HLE. Existing methods improve reasoning by expanding...