All entries

Privacy-Preserving Person Re-Identification from Temporal Sequences with Transformer and Hungarian Optimization

arXiv:2606.23230v1 Announce Type: new Abstract: Person re-identification (Re-ID) is a crucial task in surveillance and human behavior analysis, often used in public spaces such as transport hubs. Trad

Research

Probabilistic Analysis of Least Squares, Orthogonal Projection, and QR Factorization Algorithms Subject to Gaussian Noise

DGX agent

arXiv:2409.18905v3 Announce Type: replace-cross Abstract: We consider the effect of Gaussian perturbations on least-squares residuals, orthogonal projections, and QR-type algorithms. The problem that

researcharxiv-cs-lg

23 Jun 2026

Probabilistic Retrofitting of Learned Simulators

arXiv:2603.01949v2 Announce Type: replace Abstract: Dominant approaches for modelling Partial Differential Equations (PDEs) rely on deterministic predictions, yet many physical systems of interest are

Probe-and-Refine Tuning of Repository Guidance for Coding Agents

arXiv:2606.20512v2 Announce Type: replace-cross Abstract: LLM-based coding agents need higher-level operational knowledge about a repository (which files house which subsystems, how to run the test su

Programmable magnetic soft robots with controlled locomotion and directional liquid cargo release

arXiv:2606.21737v1 Announce Type: new Abstract: Magnetically programmable soft elastomers enable complex shape morphing and locomotion dynamics in small scale soft robots under external magnetic field

safetyarxiv-cs-ro

Projection-Volume Fidelity Divergence: Diagnosing and Controlling Optimization Drift in Sparse-View 3D Gaussian Tomography

arXiv:2606.22525v1 Announce Type: new Abstract: Sparse-view computed tomography is a severely ill-posed inverse problem, where recent 3D Gaussian Splatting methods offer an efficient explicit represen

Prompt-Calibrated SAM 3 for Open-Vocabulary Remote Sensing Semantic Segmentation

arXiv:2606.21863v1 Announce Type: new Abstract: Open-vocabulary semantic segmentation (OVSS) in remote sensing images aims to segment categories beyond a fixed label space. Recent SAM 3-based methods

PromptDyG: Test-Time Prompt Adaptation on Dynamic Graphs

arXiv:2606.22914v1 Announce Type: new Abstract: Activities in numerous evolving systems can be represented as dynamic graphs in snapshot form at different time intervals, i.e., discrete-time dynamic g

Prompting Diffusion Models for Zero-Shot Instance Segmentation

arXiv:2606.22660v1 Announce Type: new Abstract: Several disruptive research directions have recently emerged in computer vision, including foundation models achieving previously unseen zero-shot perfo

Prosper AI nabs $30M to help healthcare providers streamline patient interactions

Prosper AI Inc., a provider of artificial intelligence software for healthcare organizations, today announced that it has raised 30 million in funding. The Series A round was led by Andreessen Horowit

applicationssiliconangle

Protein contacts are already in the attention: a single-forward-pass alternative to the Categorical Jacobian

arXiv:2606.21876v1 Announce Type: new Abstract: The Categorical Jacobian (CJ) of Zhang et al. (2024) reads protein contacts from a language model by perturbing every residue with every alternative ami

Protocol-Aware Tokenization and Architecture Co-Design for Wireless Packet Foundation Models

arXiv:2606.20587v1 Announce Type: cross Abstract: What matters more for building foundation models for wireless packet traces: the tokenizer or the architecture or both? To answer this question, we bu

PROTON: Prototype-Based Test-Time Online OOD Detection for Medical VLMs

model-releasesarxiv-cs-cv

arXiv:2606.20913v1 Announce Type: new Abstract: Medical vision-language models (VLMs) enable zero-shot clinical image classification, yet reliably detecting out-of-distribution (OOD) inputs at deploym

Tutorials

Provable Benefits of RLVR over SFT for Reasoning Models: Learning to Backtrack Efficiently

arXiv:2606.22938v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have demonstrated that reinforcement fine-tuning of pretrained base models can lead to significant gains

tutorialsarxiv-cs-lg

Provable Filter for Real-world Graph Clustering

arXiv:2403.03666v3 Announce Type: replace Abstract: Graph clustering, an important unsupervised problem, has been shown to be more resistant to advances in Graph Neural Networks (GNNs). In addition, a

applicationsarxiv-cs-lg

Tutorials

Provable Learning of Random Hierarchy Models and Hierarchical Shallow-to-Deep Chaining

arXiv:2601.19756v2 Announce Type: replace Abstract: The empirical success of deep learning is often attributed to deep networks' ability to exploit hierarchical structure in data, constructing increas

tutorialsarxiv-cs-lg

Provably Efficient Policy-Reward Co-Pretraining for Adversarial Imitation Learning

arXiv:2606.22056v1 Announce Type: new Abstract: Adversarial imitation learning (AIL) achieves high-quality imitation compared to behavioral cloning (BC), but demands substantial online environment int

safetyarxiv-cs-lg

Provably Sub-Linear Two-Timescale NeuroEvolution with Online Plasticity

arXiv:2606.20817v1 Announce Type: cross Abstract: NeuroEvolution of Augmenting Topologies (NEAT) is a widely used neuroevolution algorithm for learning neural network architectures and weights for con

PsyBridge: A Hybrid Intelligent Framework for Multi-Dimensional Mental Health Assessment and Decision Support

arXiv:2606.23673v1 Announce Type: cross Abstract: Mental health assessment commonly relies on isolated screening instruments or data-driven models that often lack interpretability and multi-dimensiona

applicationsarxiv-cs-lg

Tutorials

Published by @OReillyMedia here: https://www.oreilly.com/radar/drivetrain-approach-data-products/

tutorialsjeremy-howard--x

The Drivetrain Approach is a framework for building effective data products, developed by Jeremy Howard and published by O'Reilly Media, that focuses on defining business objectives, identifying lever

QeHDC: Hyperdimensional Computing based on Quantum-enhanced binding and SuperClass Construction

arXiv:2606.22421v1 Announce Type: new Abstract: Hyperdimensional Computing (HDC) is a robust computational framework inspired by human cognition characterized by simple and efficient operations within

Quantifying the Agreement Between Data-Influence and Data-Similarity to Understand LLM Behavior

arXiv:2606.23591v1 Announce Type: new Abstract: One way to understand LLM behavior is to trace its output back to the training data. Two types of measures are commonly used for output tracing: data-si

Quantile Adaptive Temperature Scaling for Confidence Calibration

arXiv:2606.21749v1 Announce Type: new Abstract: Deep neural networks often produce poorly calibrated confidence estimates, overstating their certainty even when predictions are incorrect. Temperature

QuantKAN: A Unified Quantization Framework for Kolmogorov Arnold Networks

arXiv:2511.18689v4 Announce Type: replace Abstract: Kolmogorov--Arnold Networks (KANs) replace linear weights with spline-based functions, offering strong expressivity but posing challenges for low-pr

Quantum-classical physics-informed Kolmogorov-Arnold networks for PDEs

arXiv:2606.20326v2 Announce Type: replace Abstract: We develop QCPIKAN, the first quantum-classical physics-informed Kolmogorov-Arnold network designed to solve partial differential equations (PDEs).

Quantum Convolutional Neural Networks for Groundwater Heat Plume Prediction: A Surrogate Modeling Approach

arXiv:2606.23411v1 Announce Type: cross Abstract: Quantum machine learning methods are increasingly explored for modeling complex environmental systems, including groundwater heat plume dynamics. In t

Local Ai

Quantum Neural Physics: Solving Partial Differential Equations on Quantum Simulators using Quantum Convolutional Neural Networks

arXiv:2603.24196v2 Announce Type: replace-cross Abstract: Neural Physics recasts local discretisations of partial differential equations (PDEs) as fixed convolutional operators, providing a physics-pr

local-aiarxiv-cs-lg

Quantum Visual Fields with Neural Amplitude Encoding

arXiv:2508.10900v2 Announce Type: replace Abstract: Quantum Implicit Neural Representations (QINRs) have emerged as a promising paradigm that leverages parametrised quantum circuits to encode and proc

R2HandoverSim: A Simulation Framework and Benchmark for Robot-to-Human Object Handovers

model-releasesarxiv-cs-ro

arXiv:2606.21011v1 Announce Type: new Abstract: We present R2HandoverSim, a simulation benchmark for robot-to-human (R2H) object handovers. Although R2H handover methods have advanced rapidly, the lac

Radial Basis Function Networks as Projection Heads in Self-Supervised Learning

arXiv:2606.21590v1 Announce Type: new Abstract: Self-supervised learning (SSL) typically relies on a backbone encoder followed by a small multilayer perceptron (MLP) projection head, which is conventi

Ramanujan Graph Rewiring with Non Negative Resistance Curvature

arXiv:2606.21333v1 Announce Type: new Abstract: Graph Neural Networks (GNNs) have emerged as a powerful paradigm for learning on graph-structured data by iteratively propagating and aggregating inform

Tools

Ran 10 more tests comparing GLM 5.2 & Opus. On average, GLM 5.2 produced 2x the tokens but was still faster + 3x cheaper with similar qualit…

Ran 10 more tests comparing GLM 5.2 & Opus. On average, GLM 5.2 produced 2x the tokens but was still faster + 3x cheaper with similar quality! I'm open sourcing all these tests tomorrow, including the

toolstogether-ai--x

Ranking-and-Selection with Multiple Correct Answers and Non-Answerable Estimates

arXiv:2606.21889v1 Announce Type: new Abstract: We study fixed-precision ranking-and-selection in structured settings where the answer may be non-unique and where noisy estimates may temporarily admit

Agents

RAPID: A Reproducible Multi-Agent Pipeline for Interpretable Disaster Damage Assessment from Satellite and Street-View Imagery

arXiv:2606.21819v1 Announce Type: new Abstract: Due to the increasing frequency and intensity of extreme climate events, there is a clear demand for intelligent, scalable, and autonomous approaches to

agentsarxiv-cs-cv

Rapid Quantification of Outdoor Object Visibility in Urban Setting Using Connected-Vehicle Fields of View

arXiv:2506.03365v3 Announce Type: replace-cross Abstract: Identifying locations that offer maximum visual exposure to passing vehicular traffic is a core problem in urban analytics, with applications

RARM: Confidence-Gated Progress Reward Modeling for RL in Manipulation

arXiv:2606.22027v1 Announce Type: new Abstract: Reinforcement learning for robot manipulation is often bottlenecked by reward design, especially in long-horizon tasks: sparse success rewards provide w

applicationsarxiv-cs-ro

Hardware

RAVEN: Agentic RAG for Automated Vulnerability Repair

arXiv:2606.22647v1 Announce Type: cross Abstract: Automated vulnerability repair has emerged as a promising direction to mitigate the growing number of software vulnerabilities. Recent advances in Lar

hardwarearxiv-cs-lg

RaysUp: Ultra-light Universal Feature Upsampling via Geometry-Aware Ray Representation

arXiv:2606.22749v1 Announce Type: new Abstract: Pre-trained Vision Foundation Models (VFMs) have become central to modern computer vision due to their powerful semantic representations and strong gene

Read the technical paper on Krea 2 https://www.krea.ai/blog/krea-2-technical-report Download the model weights https://github.com/krea-ai/kr…

Krea 2 is a technical advancement in AI image generation with newly released model weights available for download on GitHub. The technical report details the improvements and capabilities of this vers

local-aicomfyui--x

Real-Time Multimodal Activity-Aware Error Detection in Robot-Assisted Surgery

arXiv:2606.23593v1 Announce Type: cross Abstract: Robot-assisted minimally invasive surgery improves surgical precision but introduces complexity, making technical error detection essential for ensuri

safetyarxiv-cs-cv

Hardware

Real-time pedestrian attribute recognition with YOLOv8 and ResNet18

arXiv:2606.21200v1 Announce Type: new Abstract: Pedestrian attribute recognition (PAR) assigns semantic labels to detected pedestrians and is useful in surveillance, video retrieval, and human-centere

hardwarearxiv-cs-cv

Hardware

Real-World Deployment of Massively Parallel Sampling-Based MPC for Contact-Rich Manipulation

arXiv:2606.20712v1 Announce Type: new Abstract: Sampling-based Model Predictive Control (SMPC) is a promising strategy for contact-rich robotic manipulation, combining gradient-free optimization with

hardwarearxiv-cs-ro

Real5-OmniDocBench: A Full-Scale Physical Reconstruction Benchmark for Robust Document Parsing in the Wild

model-releasesarxiv-cs-cv

arXiv:2603.04205v2 Announce Type: replace Abstract: While Vision-Language Models (VLMs) achieve near-perfect scores on digital document benchmarks like OmniDocBench, their performance in the unpredict

Rebuttals Move Peer-Review Scores, but Initial-Review Structure Bounds the Movement

arXiv:2606.22166v1 Announce Type: cross Abstract: Author rebuttals are the main post-submission window in peer review, but their effect on reviewer scores remains hard to measure because score updates

RECALL: Recovery Experience Collection for Active Lifelong Learning in Vision-Language-Action Models

arXiv:2606.23617v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models are commonly fine-tuned through passive imitation learning, where additional demonstrations are collected for task

safetyarxiv-cs-lg

Recency/Frequency Adaptive KV Caching for Large Language Model Serving

arXiv:2606.21238v1 Announce Type: cross Abstract: Key-value (KV) caching is a powerful technique for accelerating large language model inference and generation. Inference workloads are large and diver

safetyarxiv-cs-lg

Reciprocal Latent Fields for Precomputed Sound Propagation

arXiv:2602.06937v2 Announce Type: replace-cross Abstract: Realistic sound propagation is essential for immersion in a virtual scene, yet physically accurate wave-based simulations remain computational