All entries

OnePred: Next-Query Prediction via Recursive Intent Memory in Multi-Turn Conversations

arXiv:2605.23668v1 Announce Type: cross Abstract: Although large language model (LLM) conversational systems process millions of multi-turn dialogues daily, they remain fundamentally reactive: they re

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Online Hand Gesture Recognition Using 3D Convolutional Neural Networks

DGX agent

arXiv:2605.23409v1 Announce Type: cross Abstract: In human computer interaction, real-time detection and classification of dynamic hand gestures is challenging as: 1) the system must run in a real-tim

researcharxiv-cs-ai

25 May 2026

Online Learning with Multiple Fairness Regularizers via Graph-Structured Feedback

arXiv:2508.14311v2 Announce Type: replace-cross Abstract: There is an increasing need to enforce multiple, often competing, measures of fairness within automated decision systems. The appropriate weig

safetyarxiv-cs-ai

Online monotone density estimation and log-optimal calibration

arXiv:2602.08927v3 Announce Type: replace-cross Abstract: We study the problem of online monotone density estimation, where density estimators must be constructed in a predictable manner from sequenti

researcharxiv-cs-lg

Online Partitioned Local Depth for semi-supervised applications

arXiv:2512.15436v2 Announce Type: replace-cross Abstract: We introduce an extension of the partitioned local depth (PaLD) algorithm that is adapted to online applications such as semi-supervised predi

Industry

Only Restore Britain can save Britain

Only Restore Britain can save Britain Right. Just so we’re all clear. Farage and Reform tried to put me in prison because I backed the mass deportation of Pakistani child rapists and their foreign wiv

industryelon-musk--x

Tutorials

Onsager-Machlup Posterior Transport for Deep Gaussian Processes

arXiv:2605.23434v1 Announce Type: new Abstract: Approximate inference over inducing variables is the central computational bottleneck of Deep Gaussian Processes (DGPs). Existing methods either fit an

tutorialsarxiv-cs-lg

Ontological Knowledge Blocks: Executable Compliance and Profile-Based Validation for Trustworthy AI Systems

arXiv:2605.23297v1 Announce Type: new Abstract: AI-enabled services deployed in critical digital infrastructure are subject to governance obligations spanning transparency, accountability, fairness, a

Open Multimodal Datasets and Open-Source Software for Data-Driven Modeling of Multiphase Transport and Thermal Systems

arXiv:2605.23037v1 Announce Type: new Abstract: Data-driven modeling is becoming central to multiphase transport, electronics cooling, acoustic diagnostics, and thermal-fluid digital twins, but progre

OpenAI, Grupo Folha and Grupo UOL announce strategic content partnership

OpenAI announced a strategic partnership with Grupo Folha and Grupo UOL, major Brazilian media companies, to integrate their content into OpenAI's AI models and products. The partnership enables OpenA

model-releasesopenai

OpenSkillEval: Automatically Auditing the Open Skill Ecosystem for LLM Agents

model-releasesarxiv-cs-cl

arXiv:2605.23657v1 Announce Type: new Abstract: Skills, i.e., structured workflow instructions distilled for large language models (LLMs), are becoming an increasingly important mechanism for improvin

Local Ai

OpenStudio - Hybrid local/cloud (openrouter) AI router

OpenStudio is a hybrid AI router that combines local model inference with cloud-based model access through OpenRouter, a unified API providing access to hundreds of AI models through a single endpoint

local-air-ollama

Operationalizing Individual Fairness via Gradient Descent and Bradley-Terry Models

arXiv:2605.23145v1 Announce Type: cross Abstract: Individual fairness, the notion that 'similar individuals should be treated similarly,' provides a strong and flexible fairness guarantee for algorith

safetyarxiv-cs-lg

Operator-Based Generalization Bound for Deep Learning: Insights on Multi-Task Learning

arXiv:2512.19184v2 Announce Type: replace-cross Abstract: This paper presents novel generalization bounds for vector-valued neural networks and deep kernel methods, focusing on multi-task learning thr

Operator Learning for Reconstructing Flow Fields from Sparse Measurements: a Language Model Approach

arXiv:2605.23712v1 Announce Type: cross Abstract: Reconstructing flow fields from sparse measurements is a fundamental problem in fluid mechanics with broad implications for modeling, control, and des

Optimal Dimension-Free Sampling for Regularized Classification

arXiv:2605.23726v1 Announce Type: new Abstract: We prove optimal sampling bounds achieving (1pmarepsilon)-relative error for a broad class of Lipschitz continuous classification loss functions under v

researcharxiv-cs-lg

Optimization of randomized neural networks for transfer operator approximation

arXiv:2605.23689v1 Announce Type: new Abstract: RaNNDy is a randomized neural network architecture for the data-driven approximation of transfer operators associated with complex dynamical systems. Th

Orbax: Distributed Checkpointing with JAX

arXiv:2605.23066v1 Announce Type: cross Abstract: In a landscape of high-performance distributed ML systems, JAX has emerged as a framework of choice. However, JAX's modular design philosophy leaves i

researcharxiv-cs-lg

Order-Optimal Sequential 1-Bit Mean Estimation in General Tail Regimes

arXiv:2604.07796v2 Announce Type: replace-cross Abstract: In this paper, we study the problem of mean estimation under 1-bit communication constraints. We propose a novel adaptive mean estimator based

PACE: Two-Timescale Self-Evolution for Small Language Model Agents

arXiv:2605.23019v1 Announce Type: new Abstract: Deploying language-model agents in production often requires substantial compute and human effort to tune prompts, parsers, validators, and other compon

Applications

PaP-NF: Probabilistic Long-Term Time Series Forecasting via Prefix-as-Prompt Reprogramming and Normalizing Flows

arXiv:2605.23219v1 Announce Type: cross Abstract: Time series forecasting plays a central role in many real-world applications and has been extensively studied. Most existing approaches rely on determ

applicationsarxiv-cs-ai

Parallel Context Compaction for Long-Horizon LLM Agent Serving

arXiv:2605.23296v1 Announce Type: new Abstract: Long-horizon LLM agents accumulate growing conversation histories that eventually exceed the model's context window. Context compaction via LLM-based su

Parametric Prior Mapping Framework for Non-stationary Probabilistic Time Series Forecasting

arXiv:2605.23402v1 Announce Type: cross Abstract: Effectively modeling non-stationary dynamics in probabilistic multivariate time series(MTS) forecasting requires balancing expressiveness with robustn

PathCal: State-Aware Reflection-Marker Calibration for Efficient Reasoning

arXiv:2605.23074v1 Announce Type: new Abstract: The emergence of Large Reasoning Language Models (LRMs) has paved the way for tackling complex reasoning tasks through test-time scaling by generating l

Local Ai

PathNavigate: A Training-Free Pathology Agent with Surprise-Guided Scan and Shared Slide Memory for Whole-Slide Image VQA

arXiv:2605.23559v1 Announce Type: cross Abstract: Whole-slide image visual question answering (WSI-VQA) frames pathology as an extreme-context search problem: to answer a free-form clinical query, a s

local-aiarxiv-cs-ai

People are often confused that I am against the framing of 'tool AI' This is hands down the best post explaining (some of) the issues with t…

People are often confused that I am against the framing of 'tool AI' This is hands down the best post explaining (some of) the issues with the term. Give it a read! Many in AI safety advocacy argue th

safetyconnor-leahy--x

people in glass houses should not throw stones, Zuck

people in glass houses should not throw stones, Zuck Mark Zuckerberg says Apple's lack of innovation since the iPhone will lead to its decline 'They haven't really invented anything great in a while.

safetygary-marcus--x

PGT: Procedurally Generated Tasks for improving visual grounding in MLLMs

arXiv:2605.23883v1 Announce Type: cross Abstract: Despite remarkable progress in Multimodal Large Language Models (MLLMs), these models still struggle with fine-grained understanding tasks. In this wo

Tutorials

PhenoYieldNet: Learning Crop-Aware Phenological Responses for Multi-Crop Yield Prediction

arXiv:2605.23478v1 Announce Type: cross Abstract: Accurate crop yield prediction is crucial for sustainable agriculture and global food security. While existing methods are predominantly developed for

tutorialsarxiv-cs-ai

Philosophical Dispositions as Behavioral Constraints for AI-Assisted Code Review: An Empirical Study

arXiv:2605.23108v1 Announce Type: cross Abstract: AI-assisted code review tools typically operate as generic 'expert reviewer' agents, producing homogeneous findings regardless of the analysis type ne

PhotoFlow: Agentic 3D Virtual Photography Missions

arXiv:2605.23771v1 Announce Type: cross Abstract: Virtual photography asks an agent to enter a prepared 3D scene with no preselected camera pose or reference image, infer a suitable shot from scene in

Physics-Informed Machine Learning Regulated by Finite Element Analysis for Simulation Acceleration of Melt Pool Dynamics in Laser Powder Bed Fusion

arXiv:2506.20537v3 Announce Type: replace Abstract: Efficient simulation of Laser Powder Bed Fusion (LPBF) is crucial for process prediction due to the lasting issue of high computational cost associa

Physiome-ODE: A Benchmark for Irregularly Sampled Multivariate Time Series Forecasting Based on Biological ODEs

arXiv:2502.07489v2 Announce Type: replace Abstract: State-of-the-art methods for forecasting irregularly sampled time series with missing values predominantly rely on just four datasets and a few smal

pi_0-EqM: Equilibrium Matching for Closed-Loop Vision-Language-Action Control

arXiv:2605.23128v1 Announce Type: new Abstract: Currently, Vision-Language-Action (VLA) models have become the most adopted paradigm for robotic manipulation for its great potential for task generaliz

safetyarxiv-cs-ro

Hardware

PiD: Fast and High-Resolution Latent Decoding with Pixel Diffusion

arXiv:2605.23902v1 Announce Type: new Abstract: Most practical high-resolution text-to-image systems, including latent diffusion and autoregressive models, perform generation in a compact latent space

hardwarearxiv-cs-cv

PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels

arXiv:2605.22856v1 Announce Type: cross Abstract: Channel foundation models assume access to fully observed channels, an assumption that fails in deployment. We introduce PilotWiMAE, a self-supervised

safetyarxiv-cs-ai

PIMbot: A Self-Adaptive Attack Framework for Adversarial Manipulation of Multi-Robot Reinforcement Learning

arXiv:2605.23027v1 Announce Type: new Abstract: Recent research has demonstrated the potential of reinforcement learning in effective multi-robot collaboration, particularly in social dilemmas where r

safetyarxiv-cs-ro

PixelPonder: Dynamic Patch Adaptation for Enhanced Multi-Conditional Text-to-Image Generation

model-releasesarxiv-cs-cv

arXiv:2503.06684v3 Announce Type: replace Abstract: Recent advances in diffusion-based text-to-image generation have demonstrated promising results through visual condition control. However, existing

PixIE: Prompted Pixel-Space Low-Light Image Enhancement

arXiv:2605.23531v1 Announce Type: new Abstract: Low-light images exhibit severe noise, contrast loss, and semantic ambiguity, making enhancement a joint problem of denoising and detail recovery. We pr

researcharxiv-cs-cv

Local Ai

PixlStash 1.3: grid loading speed, JoyCaption and bulk tag selections with your chosen model

local-air-stablediffusion

PixlStash 1.3 is a Python-based image management and tagging web app that improves grid loading performance and introduces JoyCaption integration for AI-powered image captioning. The update adds suppo

Applications

PLACE: Prompt Learning for Attributed Community Search in Large Graphs

arXiv:2507.05311v2 Announce Type: replace-cross Abstract: In this paper, we propose PLACE (Prompt Learning for Attributed Community Search), an innovative graph prompt learning framework for ACS. Enli

applicationsarxiv-cs-ai

Agents

Plugins can also affect the empty state of the new menu - the latest datasette-agent adds a form for kicking off a new agent conversation - …

Plugins can also affect the empty state of the new menu - the latest datasette-agent adds a form for kicking off a new agent conversation - live demo (if you sign in with GitHub) on https://agent.data

agentssimon-willison--x

Point Tracking Improves World Action Models

arXiv:2605.23856v1 Announce Type: new Abstract: Robot policy learning benefits from world-action models that capture environment dynamics, but pixel-level prediction entangles dynamics with nuisance f

safetyarxiv-cs-ro

Pointwise Metrics Mislead: An Evaluation Protocol for Multimodal Inverse Problems

arXiv:2605.22891v1 Announce Type: new Abstract: Evaluation in scientific reconstruction is dominated by pointwise metrics - RMSE, MAE, per-event resolution - under the implicit assumption that lower e

PoisonForge: Task-Level Targeted Poisoning Benchmark for Instruction-Tuned LLMs

arXiv:2605.23168v1 Announce Type: cross Abstract: When practitioners fine-tune LLMs on unvetted datasets, an adversary can exploit the data supply chain through task-level poisoning: inserting a small

Pooling and Semantic Shift: The Fundamental Challenges in Long Text Embedding and Retrieval

arXiv:2603.21437v2 Announce Type: replace Abstract: Transformer-based embedding models frequently exhibit geometric pathologies, such as anisotropy and length-induced representation collapse, which ca

researcharxiv-cs-cl

Pope Leo calls for being ‘profoundly human’ in the age of AI

model-releasesthe-verge-ai

Pope Leo XIV warned of the risks of AI and unconstrained technological power in his first major papal document released on Monday. Magnifica Humanitas is the pope's manifesto on 'safeguarding the huma

Pope Leo warns AI revolution driven by ‘idolatry of profit’ https://ft.trib.al/UGP9H8b

Pope Leo has warned that the artificial intelligence revolution is being driven primarily by profit motives rather than ethical considerations, characterizing this as a form of 'idolatry of profit.' T

safetygary-marcus--x