All entries

PG-LRF: Physiology-Guided Latent Rectified Flow for Electro-Hemodynamic PPG-to-ECG Generation

arXiv:2605.12541v1 Announce Type: cross Abstract: Electrocardiography (ECG) is the clinical standard for cardiac assessment but requires dedicated hardware that does not scale to daily-life monitoring

Phasor Memory Networks: Stable Backpropagation Through Time for Scalable Explicit Memory

DGX agent

arXiv:2605.13370v1 Announce Type: new Abstract: For over a decade, explicit memory architectures like the Neural Turing Machine have remained theoretically appealing yet practically intractable for la

model-releasesarxiv-cs-lg

14 May 2026

Phy-CoSF: Physics-Guided Continuous Spectral Fields Reconstruction and Super-Resolution for Snapshot Compressive Imaging

arXiv:2605.13583v1 Announce Type: new Abstract: Recent advances have demonstrated that coded aperture snapshot spectral imaging (CASSI) systems show great potential for capturing 3D hyperspectral imag

researcharxiv-cs-cv

PhysEditBench: A Protocol-Conditioned Benchmark for Dense Physical-Map Prediction with Image Editors

model-releasesarxiv-cs-cv

arXiv:2605.13493v1 Announce Type: new Abstract: Can general-purpose image editors predict physical maps from a single RGB image? General-purpose image editors differ from standard task-specific dense-

Physics Guided Generative Optimization for Trotter Suzuki Decomposition

arXiv:2605.13268v1 Announce Type: cross Abstract: Product formulas for Trotter Suzuki simulation remain a practical route to Hamiltonian evolution on noisy intermediate scale quantum (NISQ) hardware,

Physics-informed neural particle flow for the Bayesian update step

arXiv:2602.23089v2 Announce Type: replace Abstract: The Bayesian update step poses significant computational challenges in high-dimensional nonlinear estimation. While log-homotopy particle flow filte

Pitfalls of Unlabeled Disagreement-Based Drift Detection in Streaming Tree Ensembles

model-releasesarxiv-cs-lg

arXiv:2605.12803v1 Announce Type: new Abstract: Detecting concept drift in high-speed data streams remains challenging, particularly when models must operate on unlabeled data and avoid false alarms c

Plan Before You Trade: Inference-Time Optimization for RL Trading Agents

arXiv:2605.12653v1 Announce Type: cross Abstract: Reinforcement learning agents for portfolio management are typically trained and deployed as static policies, with no mechanism for using price foreca

Plan for Speed: Dilated Scheduling for Masked Diffusion Language Models

arXiv:2506.19037v4 Announce Type: replace-cross Abstract: Masked diffusion language models (MDLMs) promise fast, non-autoregressive text generation, yet existing samplers, which pick tokens to unmask

Industry

Please don't use the offensive word 'rape.' It is Undocumented Love Making as I explain in Suicidal Empathy.

Please don't use the offensive word 'rape.' It is Undocumented Love Making as I explain in Suicidal Empathy. Elon Musk: 'These lovely small towns in England, Scotland, Ireland, are living their lives

industryelon-musk--x

Plug-In Classification of Drift Functions in Diffusion Processes Using Neural Networks

arXiv:2602.02791v2 Announce Type: replace-cross Abstract: We study supervised multiclass classification for diffusion processes, where each class is characterized by a distinct drift function and traj

Polyhedral Instability Governs Regret in Online Learning

arXiv:2605.13692v1 Announce Type: new Abstract: Many online decision problems over combinatorial actions are addressed via convex relaxations, leading to online convex optimization with piecewise line

PolySHAP: Extending KernelSHAP with Interaction-Informed Polynomial Regression

arXiv:2601.18608v3 Announce Type: replace Abstract: Shapley values have emerged as a central game-theoretic tool in explainable AI (XAI). However, computing Shapley values exactly requires 2^d game ev

Population Risk Bounds for Kolmogorov-Arnold Networks Trained by DP-SGD with Correlated Noise

arXiv:2605.12648v1 Announce Type: new Abstract: We establish the first population risk bounds for Kolmogorov-Arnold Networks (KANs) trained by mini-batch SGD with gradient clipping, covering non-priva

Agents

Position: Agentic AI System Is a Foreseeable Pathway to AGI

arXiv:2605.12966v1 Announce Type: new Abstract: Is monolithic scaling the only path to AGI? This paper challenges the dogma that purely scaling a single model is sufficient to achieve Artificial Gener

agentsarxiv-cs-ai

Position: Assistive Agents Need Accessibility Alignment

arXiv:2605.13579v1 Announce Type: new Abstract: Assistive agents for Blind and Visually Impaired (BVI) users require accessibility alignment as a first-class design objective. Despite rapid progress i

Posterior Bayesian Neural Networks with Dependent Weights

arXiv:2507.22095v5 Announce Type: replace-cross Abstract: We consider fully connected and feedforward deep neural networks with dependent and possibly heavy-tailed weights, as introduced in [26], to a

Potential and challenges of generative adversarial networks for super-resolution in 4D Flow MRI

arXiv:2508.14950v2 Announce Type: replace-cross Abstract: 4D Flow Magnetic Resonance Imaging (4D Flow MRI) enables non-invasive quantification of blood flow and hemodynamic parameters. However, its cl

PRA-PoE: Robust Alzheimer's Diagnosis with Arbitrary Missing Modalities

arXiv:2605.13081v1 Announce Type: new Abstract: Missing modalities are prevalent in real-world Alzheimer's disease (AD) assessment and pose a significant challenge to multimodal learning, particularly

safetyarxiv-cs-cv

Pragmatic Curiosity: A Unified Framework for Hybrid Learning and Optimization via Active Inference

arXiv:2602.06104v2 Announce Type: replace Abstract: Many engineering and scientific workflows rely on expensive black-box evaluations, requiring sequential decisions that must both improve task perfor

Precautionary Governance of Autonomous AI: Legal Personhood as Functional Instrument

arXiv:2605.12505v1 Announce Type: cross Abstract: Autonomous AI systems generate responsibility gaps: consequential actions that cannot be satisfactorily attributed to developers, operators, or users

Preconditioned Flow Matching

arXiv:2603.02337v2 Announce Type: replace-cross Abstract: Flow matching (FM) learns vector fields by regressing stochastic velocity targets along intermediate distributions p_t. We identify a geometri

Predict-Project-Renoise: Sampling Diffusion Models under Hard Constraints

arXiv:2601.21033v2 Announce Type: replace Abstract: Diffusion models cannot enforce hard constraints, yet applications in the physical sciences demand exact satisfaction of conservation laws, boundary

Predicting Channel Closures in the Lightning Network with Machine Learning

model-releasesarxiv-cs-lg

arXiv:2605.12759v1 Announce Type: new Abstract: The Lightning Network (LN) is a second-layer protocol for Bitcoin designed to enable fast and cost-efficient off-chain transactions. Channels in the LN

Prediction of Rectal Cancer Regrowth from Longitudinal Endoscopy

arXiv:2605.12855v1 Announce Type: new Abstract: Clinical trial studies indicate benefit of watch-and-wait (WW) surveillance for patients with rectal cancer showing a complete or near clinical response

researcharxiv-cs-cv

PreFIQs: Face Image Quality Is What Survives Pruning

model-releasesarxiv-cs-cv

arXiv:2605.13396v1 Announce Type: new Abstract: Face Image Quality Assessment (FIQA) evaluates the utility of a face image for automated face recognition (FR) systems. In this work, we propose PreFIQs

Preserve-Then-Quantize: Balancing Rank Budgets for Quantization Error Reconstruction in LLMs

arXiv:2602.02001v2 Announce Type: replace-cross Abstract: Quantization Error Reconstruction (QER) reduces accuracy loss in Post-Training Quantization (PTQ) by approximating weights as mathbf{W} approx

Pretraining Language Models with Subword Regularization: An Empirical Study of BPE Dropout in Low-Resource NLP

arXiv:2605.13436v1 Announce Type: cross Abstract: Subword regularization methods such as BPE dropout are typically applied only during fine-tuning, while pretraining is usually done with deterministic

safetyarxiv-cs-lg

Prime Successor Irreducibility: Turing Machine Complexity, Kolmogorov Complexity, and Weakness-Based Formulations

arXiv:2605.12504v1 Announce Type: cross Abstract: We develop conjectures and theorems expressing the idea that the prime sequence exhibits computational irreducibility in the transition from one prime

PRISM: Perinuclear Ring-based Image Segmentation Method for Acute Lymphoblastic Leukemia Classification

arXiv:2605.12851v1 Announce Type: cross Abstract: Automated analysis of peripheral blood smears for Acute Lymphoblastic Leukemia (ALL) is hindered by low contrast and substantial variability in cytopl

Local Ai

PRISM: Prior Rectification and Uncertainty-Aware Structure Modeling for Diffusion-Based Text Image Super-Resolution

arXiv:2605.13027v1 Announce Type: new Abstract: Text image super-resolution (Text-SR) requires more than visually plausible detail synthesis: slight errors in stroke topology may alter character ident

local-aiarxiv-cs-cv

Prismatic World Model: Learning Compositional Dynamics for Planning in Hybrid Systems

arXiv:2512.08411v2 Announce Type: replace Abstract: Model-based planning in robotic domains is challenged by the hybrid nature of physical dynamics, where continuous motion is punctuated by discrete e

Tutorials

Probabilistic Prediction Markets with Intermittent Contributions

arXiv:2510.13385v3 Announce Type: replace Abstract: Although both data availability and the demand for accurate forecasts are increasing, collaboration between stakeholders is often constrained by dat

tutorialsarxiv-cs-lg

Probing Persona-Dependent Preferences in Language Models

arXiv:2605.13339v1 Announce Type: cross Abstract: Large language models (LLMs) can be said to have preferences: they reliably pick certain tasks and outputs over others, and preferences shaped by post

Procedural Refinement by LLM-driven Algorithmic Debugging for ARC-AGI-2

arXiv:2603.20334v2 Announce Type: replace-cross Abstract: In high-complexity abstract reasoning, a system must infer a latent rule from a few examples or structured observations and apply it to unseen

Profit Maximization in Bilateral Trade against a Smooth Adversary

arXiv:2605.12664v1 Announce Type: cross Abstract: Bilateral trade models the task of intermediating between two strategic agents, a seller and a buyer, who wish to trade a good. We study this problem

Applications

Progressively Sampled Equality-Constrained Optimization

arXiv:2510.00417v2 Announce Type: replace-cross Abstract: An algorithm is proposed, analyzed, and tested for solving continuous nonlinear-equality-constrained optimization problems where the objective

applicationsarxiv-cs-lg

Local Ai

PROMETHEUS: Automating Deep Causal Research Integrating Text, Data and Models

arXiv:2605.12835v1 Announce Type: new Abstract: Large language models can extract local causal claims from text, but those claims become more useful when organized as persistent, navigable world model

local-aiarxiv-cs-ai

Tools

Protected Source Maps: Ship browser source maps securely

Protected Source Maps is a Vercel feature that enables developers to securely ship browser source maps to production without exposing them publicly. This allows for proper error tracking and debugging

toolsvercel-blog

Tutorials

Protein Circuit Tracing via Cross-layer Transcoders

arXiv:2602.12026v2 Announce Type: replace Abstract: Protein language models (pLMs) have emerged as powerful predictors of protein structure and function. However, the computational circuits underlying

tutorialsarxiv-cs-lg

Protocol-Driven Development: Governing Generated Software Through Invariants and Evidence

arXiv:2605.12981v1 Announce Type: cross Abstract: Automated program synthesis has reduced the cost of producing candidate implementations, but it introduces a harder governance problem: determining wh

Provable Quantization with Randomized Hadamard Transform

arXiv:2605.13810v1 Announce Type: new Abstract: Vector quantization via random projection followed by scalar quantization is a fundamental primitive in machine learning, with applications ranging from

Provably avoiding over-optimization in Direct Preference Optimization without knowing the data distribution

arXiv:2602.06239v2 Announce Type: replace Abstract: We introduce PEPO (Pessimistic Ensemble based Preference Optimization), a single-step Direct Preference Optimization (DPO)-like algorithm to mitigat

safetyarxiv-cs-lg

Proximal-Based Generative Modeling for Bayesian Inverse Problems

arXiv:2605.13278v1 Announce Type: cross Abstract: Score-based diffusion models demonstrate superior performance in generative tasks but encounter fundamental bottlenecks in inverse problems due to the

safetyarxiv-cs-lg

PwC expands Anthropic alliance, will train 30,000 staff on Claude

model-releasessiliconangle

PricewaterhouseCoopers LLP and Anthropic PBC today announced a major expansion of their alliance, as the consulting giant is set to roll out Claude Code and Claude Cowork across its workforce and trai

Pyramid Forcing: Head-Aware Pyramid KV Cache Policy for High-Quality Long Video Generation

arXiv:2605.13111v1 Announce Type: new Abstract: Autoregressive video generation enables streaming and open-ended long video synthesis, but still suffers from long-term degradation caused by accumulate

safetyarxiv-cs-cv

Pyramid Self-contrastive Learning Framework for Test-time Ultrasound Image Denoising

arXiv:2605.12567v1 Announce Type: cross Abstract: The inherent electronic and speckle noise complicates clinical interpretation of ultrasound images. Conventional denoising methods rely on explicit no

Q-Flow: Stable and Expressive Reinforcement Learning with Flow-Based Policy

arXiv:2605.13435v1 Announce Type: cross Abstract: There is growing interest in utilizing flow-based models as decision-making policies in reinforcement learning due to their high expressive capacity.