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...
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.
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.
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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.
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...
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...
Combining scEEG and PPG for reliable sleep staging using lightweight wearables
arXiv:2602.15042v1 Announce Type: cross Abstract: Reliable sleep staging remains challenging for lightweight wearable devices such as single-channel electroencephalography (scEEG) or photoplethysmography (PPG). scEEG offers direct measurement of cortical activity and serves as the foundation for sleep staging, yet exhibits limited...
Structure-Aware Piano Accompaniment via Style Planning and Dataset-Aligned Pattern Retrieval
arXiv:2602.15074v1 Announce Type: cross Abstract: We introduce a structure-aware approach for symbolic piano accompaniment that decouples high-level planning from note-level realization. A lightweight transformer predicts an interpretable, per-measure style plan conditioned on section/phrase structure and functional harmony, and a retriever...
MB-DSMIL-CL-PL: Scalable Weakly Supervised Ovarian Cancer Subtype Classification and Localisation Using Contrastive and Prototype Learning with Frozen Patch Features
arXiv:2602.15138v1 Announce Type: cross Abstract: The study of histopathological subtypes is valuable for the personalisation of effective treatment strategies for ovarian cancer. However, increasing diagnostic workloads present a challenge for UK pathology departments, leading to the rise in AI approaches....
The Vision Wormhole: Latent-Space Communication in Heterogeneous Multi-Agent Systems
arXiv:2602.15382v1 Announce Type: new Abstract: Multi-Agent Systems (MAS) powered by Large Language Models have unlocked advanced collaborative reasoning, yet they remain shackled by the inefficiency of discrete text communication, which imposes significant runtime overhead and information quantization loss. While latent...
Perspectives - Interactive Document Clustering in the Discourse Analysis Tool Suite
arXiv:2602.15540v1 Announce Type: new Abstract: This paper introduces Perspectives, an interactive extension of the Discourse Analysis Tool Suite designed to empower Digital Humanities (DH) scholars to explore and organize large, unstructured document collections. Perspectives implements a flexible, aspect-focused document clustering...
Agent Skill Framework: Perspectives on the Potential of Small Language Models in Industrial Environments
arXiv:2602.16653v1 Announce Type: new Abstract: Agent Skill framework, now widely and officially supported by major players such as GitHub Copilot, LangChain, and OpenAI, performs especially well with proprietary models by improving context engineering, reducing hallucinations, and boosting task accuracy. Based...
Towards a Science of AI Agent Reliability
arXiv:2602.16666v1 Announce Type: new Abstract: AI agents are increasingly deployed to execute important tasks. While rising accuracy scores on standard benchmarks suggest rapid progress, many agents still continue to fail in practice. This discrepancy highlights a fundamental limitation of current...
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Super Early Bird pricing for TechCrunch Disrupt 2026 ends February 27 at 11:59 p.m. PT. That means you have just 6 days left to secure up to $680 of ticket savings.
Surrogate Modeling for Neutron Transport: A Neural Operator Approach
arXiv:2602.15890v1 Announce Type: cross Abstract: This work introduces a neural operator based surrogate modeling framework for neutron transport computation. Two architectures, the Deep Operator Network (DeepONet) and the Fourier Neural Operator (FNO), were trained for fixed source problems to learn...
Improved Upper Bounds for Slicing the Hypercube
arXiv:2602.16807v1 Announce Type: new Abstract: A collection of hyperplanes $\mathcal{H}$ slices all edges of the $n$-dimensional hypercube $Q_n$ with vertex set $\{-1,1\}^n$ if, for every edge $e$ in the hypercube, there exists a hyperplane in $\mathcal{H}$ intersecting $e$ in its...
HQFS: Hybrid Quantum Classical Financial Security with VQC Forecasting, QUBO Annealing, and Audit-Ready Post-Quantum Signing
arXiv:2602.16976v1 Announce Type: new Abstract: Here's the corrected paragraph with all punctuation and formatting issues fixed: Financial risk systems usually follow a two-step routine: a model predicts return or risk, and then an optimizer makes a decision such as a...
Cinder: A fast and fair matchmaking system
arXiv:2602.17015v1 Announce Type: new Abstract: A fair and fast matchmaking system is an important component of modern multiplayer online games, directly impacting player retention and satisfaction. However, creating fair matches between lobbies (pre-made teams) of heterogeneous skill levels presents a...
M2F: Automated Formalization of Mathematical Literature at Scale
arXiv:2602.17016v1 Announce Type: new Abstract: Automated formalization of mathematics enables mechanical verification but remains limited to isolated theorems and short snippets. Scaling to textbooks and research papers is largely unaddressed, as it requires managing cross-file dependencies, resolving imports, and ensuring...
Continual learning and refinement of causal models through dynamic predicate invention
arXiv:2602.17217v1 Announce Type: new Abstract: Efficiently navigating complex environments requires agents to internalize the underlying logic of their world, yet standard world modelling methods often struggle with sample inefficiency, lack of transparency, and poor scalability. We propose a framework for...
One-step Language Modeling via Continuous Denoising
arXiv:2602.16813v1 Announce Type: new Abstract: Language models based on discrete diffusion have attracted widespread interest for their potential to provide faster generation than autoregressive models. In practice, however, they exhibit a sharp degradation of sample quality in the few-step regime,...
Bridging the Domain Divide: Supervised vs. Zero-Shot Clinical Section Segmentation from MIMIC-III to Obstetrics
arXiv:2602.17513v1 Announce Type: new Abstract: Clinical free-text notes contain vital patient information. They are structured into labelled sections; recognizing these sections has been shown to support clinical decision-making and downstream NLP tasks. In this paper, we advance clinical section segmentation...
MMCAformer: Macro-Micro Cross-Attention Transformer for Traffic Speed Prediction with Microscopic Connected Vehicle Driving Behavior
arXiv:2602.16730v1 Announce Type: new Abstract: Accurate speed prediction is crucial for proactive traffic management to enhance traffic efficiency and safety. Existing studies have primarily relied on aggregated, macroscopic traffic flow data to predict future traffic trends, whereas road traffic dynamics...
Construction of a classification model for dementia among Brazilian adults aged 50 and over
arXiv:2602.16887v1 Announce Type: new Abstract: To build a dementia classification model for middle-aged and elderly Brazilians, implemented in Python, combining variable selection and multivariable analysis, using low-cost variables with modification potential. Observational study with a predictive modeling approach using a...
Malliavin Calculus as Stochastic Backpropogation
arXiv:2602.17013v1 Announce Type: new Abstract: We establish a rigorous connection between pathwise (reparameterization) and score-function (Malliavin) gradient estimators by showing that both arise from the Malliavin integration-by-parts identity. Building on this equivalence, we introduce a unified and variance-aware hybrid estimator...
Transforming Behavioral Neuroscience Discovery with In-Context Learning and AI-Enhanced Tensor Methods
arXiv:2602.17027v1 Announce Type: new Abstract: Scientific discovery pipelines typically involve complex, rigid, and time-consuming processes, from data preparation to analyzing and interpreting findings. Recent advances in AI have the potential to transform such pipelines in a way that domain experts...