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arXiv:2511.03724v3 Announce Type: replace Abstract: AI researchers have long focused on poker-like games as a testbed for environments characterized by multi-player dynamics, imperfect information, an

agentsarxiv-cs-ai

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Research

P1-KAN: an effective Kolmogorov-Arnold network with application to hydraulic valley optimization

DGX agent

arXiv:2410.03801v5 Announce Type: replace Abstract: A new Kolmogorov-Arnold network (KAN) is proposed to approximate potentially irregular functions in high dimensions. We provide error bounds for thi

researcharxiv-cs-lg

5 May 2026

P3-LLM: An Integrated NPU-PIM Accelerator for Edge LLM Inference Using Hybrid Numerical Formats

arXiv:2511.06838v4 Announce Type: replace-cross Abstract: The substantial memory bandwidth and computational demands of large language models (LLMs) present critical challenges for efficient inference

PACE: Parameter Change for Unsupervised Environment Design

arXiv:2605.01358v1 Announce Type: new Abstract: Unsupervised Environment Design (UED) offers a promising paradigm for improving reinforcement learning generalization by adaptively shaping training env

Agents

PACE: Post-Causal Entropy Modeling for Learned LiDAR Point Cloud Compression

arXiv:2605.01320v1 Announce Type: new Abstract: LiDAR point cloud compression is vital for autonomous systems to handle massive data from high-resolution sensors. While learned entropy modeling built

agentsarxiv-cs-cv

Page image classification for content-specific data processing

arXiv:2507.21114v3 Announce Type: replace-cross Abstract: Digitization projects in humanities often generate vast quantities of page images from historical documents, presenting significant challenges

researcharxiv-cs-cv

Pair2Score: Pairwise-to-Absolute Transfer for LLM-Based Essay Scoring

arXiv:2605.02069v1 Announce Type: new Abstract: Many scoring applications require absolute predictions, while pairwise comparisons can provide a simpler learning objective. We present Pair2Score, a tw

PanDORA: Casual HDR Radiance Acquisition of Indoor Scenes for Image-based Lighting

arXiv:2407.06150v3 Announce Type: replace Abstract: Most novel view synthesis methods -- including Neural Radiance Fields (NeRF) -- struggle to capture the high dynamic range (HDR) radiance required f

applicationsarxiv-cs-cv

Pandora's Regret: A Proper Scoring Rule for Evaluating Sequential Search

arXiv:2605.01936v1 Announce Type: new Abstract: In sequential search, alternatives are tested until the true class is found. Standard proper scoring rules like log loss are local, ignoring the ranking

Parameter Space Analysis through Guided Visual Interpolations

arXiv:2509.19202v2 Announce Type: replace-cross Abstract: We propose Parameter Space Analysis through Guided Visual Interpolations (ParamInter), a novel tool for high-dimensional input parameter space

ParaRNN: An Interpretable and Parallelizable Recurrent Neural Network for Time-Dependent Data

arXiv:2605.02692v1 Announce Type: cross Abstract: The proliferation of large-scale and structurally complex data has spurred the integration of machine learning methods into statistical modeling. Recu

Parking Assistance for Trailer-Truck Transport Vehicles Using Sensor Fusion and Motion Planning

arXiv:2605.02716v1 Announce Type: new Abstract: Autonomous driving technology has rapidly evolved over the past decade, offering significant improvements in transportation efficiency, safety, and cost

safetyarxiv-cs-ro

Local Ai

Parllama -- a terminal UI for Ollama model management and multi-provider LLM chat

Parllama is a TUI (Text UI) application designed for easy management and use of Ollama-based LLMs that also works with major cloud-provided LLMs. It provides core model management features including f

local-air-ollama

Patient-Specific Optimization for Mandibular Reconstruction Planning with Enhanced Bone Union

arXiv:2605.01084v1 Announce Type: new Abstract: Mandibular reconstruction with vascularized bone grafts is complicated by donor-host nonunion, and current virtual surgical planning produces a geometri

safetyarxiv-cs-cv

Industry

PayPal reports Q1 net revenue up 7% YoY to 8.4B, total payment volume up 11% YoY to 464B, active accounts up 1% to 439M, and seeks $1.5B+ in cost savings (Paige Smith/Bloomberg)

Paige Smith / Bloomberg: PayPal reports Q1 net revenue up 7% YoY to 8.4B, total payment volume up 11% YoY to 464B, active accounts up 1% to 439M, and seeks $1.5B+ in cost savings — PayPal Holdings Inc

industrytechmeme

PC-MNet: Dual-Level Congruity Modeling for Multimodal Sarcasm Detection via Polarity-Modulated Attention

arXiv:2605.02447v1 Announce Type: new Abstract: Multimodal sarcasm detection, which aims to precisely identify pragmatic incongruities between literal text and nonverbal cues, has gained substantial a

Pedagogical Promise and Peril of AI: A Text Mining Analysis of ChatGPT Research Discussions in Programming Education

arXiv:2605.00361v1 Announce Type: cross Abstract: GenAI systems such as ChatGPT are increasingly discussed in programming education, but the ways in which the research literature conceptualizes and fr

applicationsarxiv-cs-ai

Agents

People ask me what my AI agent team does. The reality is that it is incredibly horizontal, incredibly open and flexible, and fully driven by…

People ask me what my AI agent team does. The reality is that it is incredibly horizontal, incredibly open and flexible, and fully driven by a flywheel of verbalized, documented, and reviewed goals-co

agentsallie-k--miller--x

PepSpecBench: A Unified Evaluation Benchmark for Peptide Tandem Mass Spectrometry Prediction

arXiv:2605.01945v1 Announce Type: new Abstract: Tandem mass spectrometry provides a high-throughput framework for identifying and quantifying proteins in complex biological samples. In computational p

Perceptual Flow Network for Visually Grounded Reasoning

arXiv:2605.02730v1 Announce Type: new Abstract: Despite the success of Large-Vision Language Models (LVLMs), general optimization objectives (e.g., standard MLE) fail to constrain visual trajectories,

safetyarxiv-cs-cv

Industry

Peril Predicts: Precision Payouts for a Volatile World

This Databricks blog post likely discusses how predictive analytics and machine learning can improve insurance payouts and risk assessment in volatile market conditions. The article probably covers te

industrydatabricks

Tools

Perplexity and Computer now connect to premium health sources, starting with NEJM and BMJ Group, with 9 more medical journals and clinical d…

Perplexity and Computer now connect to premium health sources, starting with NEJM and BMJ Group, with 9 more medical journals and clinical databases on the way. Ask health questions and get answers ci

toolsperplexity--x

Local Ai

Personalized Federated Learning for Gradient Alignment

arXiv:2605.02143v1 Announce Type: new Abstract: Personalized federated learning (pFL) aims to adapt models to client specific data distributions, yet it often fails to reliably preserve personalized i

local-aiarxiv-cs-lg

Perturb and Correct: Post-Hoc Ensembles using Affine Redundancy

arXiv:2605.01632v1 Announce Type: new Abstract: Models that are indistinguishable on in-distribution data can behave very differently under distribution shift. We introduce Perturb-and-Correct (P&C),

Perturbation Dose Responses in Recursive LLM Loops: Raw Switching, Stochastic Floors, and Persistent Escape under Append, Replace, and Dialog Updates

arXiv:2605.02236v1 Announce Type: cross Abstract: Recursive language-model loops often settle into recognizable attractor-like patterns. The practical question is how much injected text is needed to m

Phase-map synthesis from magnitude-only MR images using conditional score-based diffusion models with application in training of accelerated MRI reconstruction models

arXiv:2605.01185v1 Announce Type: new Abstract: Accelerated magnetic resonance imaging (MRI) enabled by the training of deep learning (DL)-based image recon. models requires large and diverse raw k-sp

researcharxiv-cs-cv

PhaseNet++: Phase-Aware Frequency-Domain Anomaly Detection for Industrial Control Systems via Phase Coherence Graphs

arXiv:2605.00929v1 Announce Type: new Abstract: Multivariate time series anomaly detection in ICS has attracted growing attention due to the increasing threat of cyber-physical attacks on critical inf

phi-Table: A Statistical Explanation for Global SHAP

arXiv:2512.07578v3 Announce Type: replace-cross Abstract: Global SHAP explanations are typically presented as feature-importance rankings, which identify variables that matter to a black-box model but

Phone2Act: A Low-Cost, Hardware-Agnostic Teleoperation System for Scalable VLA Data Collection

arXiv:2605.01948v1 Announce Type: new Abstract: Collecting diverse, high-quality manipulation data for Vision-Language-Action (VLA) model training remains prohibitively expensive for many research gro

applicationsarxiv-cs-ro

Physics-Informed Neural Learning for State Reconstruction and Parameter Identification in Coupled Greenhouse Climate Dynamics

arXiv:2605.02524v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) have recently emerged as a promising framework for integrating data-driven learning with physical knowledge. In

Physiology-Aware Masked Cross-Modal Reconstruction for Biosignal Representation Learning

arXiv:2605.00973v1 Announce Type: new Abstract: Biosignals acquired from different locations on the body often provide temporally ordered views of the same underlying physiological process. However, m

Pi-Change: A Prior-Informed Multiple Change Point Detection Algorithm

arXiv:2605.01003v1 Announce Type: cross Abstract: Statistical change point (CP) detection methods typically rely on likelihood-based inference and ignore contextual information about plausible CP loca

Tutorials

PiCSRL: Physics-Informed Contextual Spectral Reinforcement Learning

arXiv:2603.26816v2 Announce Type: replace Abstract: High-dimensional low-sample-size (HDLSS) datasets constrain reliable environmental model development, where labeled data remain sparse. Reinforcemen

tutorialsarxiv-cs-lg

Tools

Pinecone Expands in Europe with New Frankfurt Cloud Region, Delivering the Knowledge Infrastructure for AI to Central European Enterprises

Pinecone launched a new cloud region in Frankfurt, Germany to expand its vector database infrastructure in Europe and better serve Central European enterprises building AI applications. This regional

toolspinecone

Pinecone Marketplace, live today. Until now, building an internal app that answers questions over a company's own docs, contracts, tickets, …

Pinecone Marketplace, live today. Until now, building an internal app that answers questions over a company's own docs, contracts, tickets, and wikis meant months of retrieval pipeline work: embedding

applicationspinecone--x

Pixel Perfect: Relational Image Quality Assessment with Spatially-Aware Distortions

arXiv:2605.02863v1 Announce Type: new Abstract: Traditional image quality assessment (IQA) methods rely on mean opinion scores (MOS), which are resource-intensive to collect and fail to provide interp

researcharxiv-cs-cv

Pixel-to-4D: Camera-Controlled Image-to-Video Generation with Dynamic 3D Gaussians

arXiv:2601.00678v2 Announce Type: replace Abstract: Humans excel at forecasting the future dynamics of a scene given just a single image. Video generation models that can mimic this ability are an ess

applicationsarxiv-cs-cv

Planner Matters! An Efficient and Unbalanced Multi-agent Collaboration Framework for Long-horizon Planning

arXiv:2605.02168v1 Announce Type: cross Abstract: Language model (LM)-based agents have demonstrated promising capabilities in automating complex tasks from natural language instructions, yet they con

PointCSP: Cross-Sample Semantic Propagation and Stability Preservation in Self-Supervised Point Cloud Learning

model-releasesarxiv-cs-cv

arXiv:2605.01759v1 Announce Type: new Abstract: Scene-level point cloud self-supervised learning (PC-SSL) has demonstrated potential in enhancing the generalization capability of 3D vision models. Des

Polynomial-Time Optimal Group Selection via the Double-Commutator Eigenvalue Problem

arXiv:2605.00834v1 Announce Type: new Abstract: The algebraic diversity framework replaces temporal averaging over multiple observations with algebraic group action on a single observation for second-

Poodle: Seamlessly Scaling Down Large Language Models with Just-in-Time Model Replacement

arXiv:2512.05525v2 Announce Type: replace-cross Abstract: Businesses increasingly rely on large language models (LLMs) to automate simple repetitive tasks instead of developing custom machine learning

PPO guided Agentic Pipeline for Adaptive Prompt Selection and Test Case Generation

arXiv:2605.00942v1 Announce Type: cross Abstract: Developing effective test cases capable of thoroughly exercising large-scale software systems is inherently difficult, especially if such systems have

PRCD-MAP: Learning How Much to Trust Imperfect Priors in Causal Discovery

arXiv:2605.01669v1 Announce Type: cross Abstract: External priors of unknown reliability create a brittle trade-off in causal discovery: blind trust amplifies errors, blind rejection wastes signal. Re

safetyarxiv-cs-lg

Predicting Post Virality with Temporal Cross-Attention over Trend Signals

arXiv:2605.02358v1 Announce Type: new Abstract: Current models for predicting social media virality rely heavily on static textual and structural features, effectively ignoring the highly dynamic natu

applicationsarxiv-cs-lg

Prescriptive Scaling Laws for Data Constrained Training

arXiv:2605.01640v1 Announce Type: cross Abstract: Training compute is increasingly outpacing the availability of high-quality data. This shifts the central challenge from optimal compute allocation to

Pretraining A Large Language Model using Distributed GPUs: A Memory-Efficient Decentralized Paradigm

arXiv:2602.11543v2 Announce Type: replace Abstract: Pretraining large language models (LLMs) typically requires centralized clusters with thousands of high-memory GPUs (e.g., H100/A100). Recent decent

Pretraining on Sleep Data Improves non-Sleep Biosignal Tasks

arXiv:2605.02500v1 Announce Type: new Abstract: Sleep foundation models have recently demonstrated strong performance on in-domain polysomnography tasks, including sleep staging, apnea detection, and

Industry

pretty excited for voice models to get great its interesting to watch how people are already starting to change the way they interface with …

Sam Altman expresses enthusiasm about the advancement of voice AI models and their potential to improve human-computer interaction. He notes the emerging trend of users already adapting their communic

industrysam-altman--x