local ai

DCD-PFN: A Decoupling-Aware Foundation Model for Causal Discovery

arXiv:2606.21212v1 Announce Type: new Abstract: Causal discovery is critical for understanding complex data-generating mechanisms, yet traditional algorithms often struggle with highly non-linear and

Dead-Direction Signatures: A Cheap Spectral Reading of Singular Complexity

DGX agent

arXiv:2606.21158v1 Announce Type: new Abstract: Singular learning theory characterises the complexity of a deep network through the geometry of its loss singularities. The local learning coefficient (

local-aiarxiv-cs-lg

23 Jun 2026

Deep EM with Hierarchical Latent Label Modelling for Multi-Site Prostate Lesion Segmentation

arXiv:2603.14418v2 Announce Type: replace Abstract: Label variability is a major challenge for prostate lesion segmentation. In multi-site datasets, annotations often reflect centre-specific contourin

Deep RL- Tuned Mo del-Free Adaptive Control for Lower-Limb Exoskeletons During Sit-to-Stand Transitions

arXiv:2606.22040v1 Announce Type: new Abstract: Sit-to-stand (STS) transitions impose significant joint-loading demands on elderly individuals, making them a primary target for lower-limb exoskeleton

Efficient Document Tampering Localization with Multi-Level Discrepancy Features and Unified DCT-Quantization Embedding

arXiv:2606.22285v1 Announce Type: new Abstract: Localizing document tampering is extremely challenging, as manipulations are crafted to appear visually consistent and often leave only subtle traces th

Efficient Traffic State Prediction With Dynamic Joint Spatio-Temporal Relation Inference

arXiv:2504.08061v2 Announce Type: replace Abstract: Traffic prediction is difficult due to the complex interplay of temporal evolution, spatial interactions, and delayed spatio-temporal propagation ov

Eigenspace-Based Clustering for Personalized System Identification

arXiv:2606.20811v1 Announce Type: cross Abstract: We study the problem of system identification in heterogeneous settings, where different systems may follow distinct underlying dynamics. Existing clu

Enabling Cloud-Level Accuracy in Edge AI through IoT Data Preprocessing

arXiv:2606.22496v1 Announce Type: cross Abstract: Large language models (LLMs) offer a natural-language interface for interpreting Internet of Things (IoT) sensor data in smart environments; however,

Energy-based Compositional Diffusion Planning

arXiv:2606.21646v1 Announce Type: new Abstract: Compositional diffusion planners aim to solve long-horizon robotic tasks using short training trajectories. Yet, current approaches often rely on the he

Enlight: Fast Low-Light Image Enhancement via Multi-Objective Optimization and Shadow-Aware Refinement

arXiv:2606.21674v1 Announce Type: new Abstract: We present ENLIGHT, a fast and training free framework for low-light image enhancement based on direct optimization of a perceptual objective. Unlike de

EnTrust: Modeling Inter-Modal Conflict for Trustworthy Multimodal Medical Image Analysis

arXiv:2606.21384v1 Announce Type: new Abstract: Multimodal medical imaging fuses complementary anatomical and functional information, yet modalities frequently disagree in pathologically heterogeneous

Error Highways: Scaling Predictive Coding to Very Deep Networks

arXiv:2606.22744v1 Announce Type: new Abstract: Predictive coding networks (PCNs) offer a biologically-plausible, local-learning alternative to back-propagation of errors (backprop). Nevertheless, the

Explanations for Automatic Speech Recognition

arXiv:2302.14062v2 Announce Type: replace-cross Abstract: We address quality assessment for neural network based ASR by providing explanations that help increase our understanding of the system and ul

Fed-CausalDiff: Decoupled Synchronization for Federated Do-Simulation and Policy Evaluation

arXiv:2606.22510v1 Announce Type: new Abstract: While federated learning enables collaborative modelling on decentralised data, standard methods merely fit historical observations. This purely observa

Federated learning with heavy-tailed gradient noise and communication noise: a variance-reduction based algorithm

arXiv:2606.22466v1 Announce Type: new Abstract: Federated learning (FL) is an emerging distributed machine learning paradigm that enables local devices to jointly train a global model while keeping da

FedSA-GCL: A Semi-Asynchronous Federated Graph Learning Framework with Personalized Aggregation and Cluster-Aware Broadcasting

arXiv:2507.18219v3 Announce Type: replace Abstract: Federated Graph Learning (FGL) is a distributed learning paradigm that enables collaborative training over large-scale subgraphs located on multiple

FLM-Occ: Feed-forward Likelihood Maximization for Efficient Indoor Occupancy Prediction

arXiv:2606.21373v1 Announce Type: new Abstract: Recent indoor occupancy prediction methods adopt Gaussian primitives as a sparse 3D representation for computational efficiency. However, their training

Flow6D: Discrete-to-Continuous Flow Matching for Efficient and Accurate Category-Level 6D Pose Estimation

arXiv:2606.23293v1 Announce Type: new Abstract: 6D pose estimation is a key task in computer vision and embodied AI, widely used in robotic manipulation, augmented reality, etc. Existing methods direc

GreenRFM: Learning a resource-efficient radiology vision-language foundation model via supervision-centric pre-training

arXiv:2603.06467v2 Announce Type: replace Abstract: Radiology foundation models (RFMs) have largely inherited the scale-first recipe of natural-image vision--language pre-training. This recipe is diff

Homographic Navigation: Geometry-Driven Camera Guidance for Deterministic Planar Capture

arXiv:2606.22834v1 Announce Type: new Abstract: We present homographic navigation, a geometry-centric framework for guiding camera acquisition toward precise capture of planar regions. Rather than tre

ITNet: A Learnable Integral Transform That Subsumes Convolution, Attention, and Recurrence

arXiv:2606.19538v2 Announce Type: replace-cross Abstract: Convolutional networks, recurrent networks, and transformers each encode different inductive biases -- locality, sequential memory, and conten

Johnson-Lindenstrauss Lemma Guided Network for Efficient 3D Medical Segmentation

arXiv:2509.22307v2 Announce Type: replace Abstract: Lightweight 3D medical image segmentation remains constrained by a fundamental extit{``efficiency / robustness conflict''}, particularly when proces

Keeping the Evidence Chain: Semantic Evidence Allocation for Training-Free Token Pruning in Video Temporal Grounding

arXiv:2603.05663v2 Announce Type: replace Abstract: Video Temporal Grounding (VTG) localizes the temporal boundaries of query-relevant moments in long videos, making video-language-model prohibitively

Krea 2 is back and this time the weights are OPEN. This open source release ships with two models designed to work together — @krea_ai 2 RAW…

Krea 2 is back and this time the weights are OPEN. This open source release ships with two models designed to work together — @krea_ai 2 RAW and Krea 2 Turbo. RAW is for training, Turbo is for inferen

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Krea x Comfy: Founders Live A special live conversation with our guests Victor Perez (CEO, Krea), Miguel Lara (Krea Team), and ComfyAnonymou…

Krea x Comfy: Founders Live A special live conversation with our guests Victor Perez (CEO, Krea), Miguel Lara (Krea Team), and ComfyAnonymous (Co-Founder, Comfy Org), hosted by Purz & Julien. Today at

local-aicomfyui--x

Krea X Comfy: Founders Live https://x.com/i/broadcasts/1rGmqqnoqevGy

This appears to be a live broadcast event featuring the founders of Krea and Comfy discussing their projects and potentially their collaboration or integration. The session likely covers updates on Co

local-aicomfyui--x

Latent Goal Prediction from Language for Model-Based Planning

arXiv:2606.20627v1 Announce Type: cross Abstract: Planning with world models is bottlenecked by compounding prediction errors and the difficulty of defining optimizable goals. Visual targets provide p

Live Stream: Welcome to open source AI Lots of new folk are starting out on their journey with open models. Come join our livestream with al…

Live Stream: Welcome to open source AI Lots of new folk are starting out on their journey with open models. Come join our livestream with all your questions about local models, open coding agents, and

local-aiclem-delangue--x

Local Causal Attribution of Chain-of-Thought Reasoning

arXiv:2606.21821v1 Announce Type: new Abstract: Understanding the causal structure of a language model's thought process is a problem of significant importance for both transparency and safety. In thi

Local Flow Matching Generative Models

arXiv:2410.02548v4 Announce Type: replace-cross Abstract: Flow Matching (FM) is a simulation-free method for learning a continuous, invertible flow that interpolates between two distributions, and in

Look Before You Zoom: Adaptive Routing for the Resolution-Context Trade-off in Visual RAG

arXiv:2606.21968v1 Announce Type: new Abstract: Vision-Language Models (VLMs) struggle as query-relevant objects become smaller. To address this, recent training-free approaches dynamically retrieve a

MambaADv2: Evolving Duality-enhanced State Space Model for Unsupervised Anomaly Detection

arXiv:2606.23126v1 Announce Type: new Abstract: While recent advancements in anomaly detection have demonstrated the efficacy of CNN- and Transformer-based approaches, these architectures face inheren

MedFedPure: A Medical Federated Framework with MAE-based Detection and Diffusion Purification for Inference-Time Attacks

arXiv:2511.11625v2 Announce Type: replace Abstract: Artificial intelligence (AI) has shown great potential in medical imaging, particularly for brain tumor detection using Magnetic Resonance Imaging (

Mind the Noise: Sensitivity of Transformer-based Interaction-Aware Trajectory Prediction Models to Noisy Data

arXiv:2606.21344v1 Announce Type: cross Abstract: Trajectory prediction allows autonomous vehicles to anticipate the future behavior of surrounding objects (or agents) and, accordingly, maximize the s

MIRAGE: Stealthy Visual Prompt Injection for Vulnerability Detection in Web Agents

arXiv:2606.20717v1 Announce Type: new Abstract: Multimodal Large Language Model (MLLM)-based web agents provide practical, high-precision solutions for visual browser automation; however, they inheren

mlx-vis: GPU-Native Dimensionality Reduction on Apple Silicon

arXiv:2603.04035v4 Announce Type: replace Abstract: Dimensionality reduction is a foundational tool for visualizing high-dimensional data, yet its reference implementations span a fragmented stack of

Modular Diffusion Models for Structured Visual Recognition

arXiv:2606.22702v1 Announce Type: new Abstract: Traditional supervised methods for structured visual recognition tasks -- such as object detection, segmentation, and scene graph generation -- often pr

Multi-AUV Marine Life Tracking with Single Hydrophone Payloads via a Hidden Markov Model Equipped Particle Filter

arXiv:2606.22335v1 Announce Type: new Abstract: Researchers tag and track marine animals to study migration patterns, human impacts on behavior, and behavioral shifts due to climate change. Accurate d

N2M: Bridging Navigation and Manipulation by Learning Pose Preference from Rollout

arXiv:2509.18671v2 Announce Type: replace Abstract: Determining where to execute the manipulation policy is a fundamental challenge in mobile manipulation. Most approaches have formulated this as a ge

NeoLoc-68: End-to-end 68-point neonatal facial landmark localisation in neonatal clinical environments

arXiv:2606.20823v1 Announce Type: new Abstract: Facial landmark localisation is a prerequisite for developing automated, non-contact neonatal pain assessment methods. Clinicians use pain scales to jud

Numerical stability analysis of large language models

arXiv:2503.10251v2 Announce Type: replace-cross Abstract: Transformers are the state-of-the-art architecture for large language models, and a key to their scalability is the strategic usage of low-pre

One-Shot Data Selection for Medical Image Classification via Graph Coverage

arXiv:2606.22002v1 Announce Type: new Abstract: Training medical image classifiers on entire datasets is wasteful when annotation budgets are limited: not all samples contribute equally, yet acquiring

Over-the-Air Federated Learning: Rethinking Edge AI Through Signal Processing

arXiv:2512.03719v2 Announce Type: replace-cross Abstract: Over-the-Air Federated Learning (AirFL) is an emerging paradigm that tightly integrates wireless signal processing and distributed machine lea

P-JEPA: Procedural Video Representation Learning via Joint Embedding Predictive Architecture

arXiv:2606.23256v1 Announce Type: new Abstract: The increasing maturity of embodied AI platforms has driven a growing interest in procedural video representation learning to support intelligent assist

Patched Flow Matching: Generative Wall-Pressure Reconstruction Beyond Training-Domain Scales from Sparse Sensors

arXiv:2606.22084v1 Announce Type: cross Abstract: Characterizing the complete wall-pressure spectrum in turbulent wall-bounded flows requires simultaneous access to the viscous-scale high-wavenumber c

Perturbation-Based Uncertainty for Failure Detection in Vision-Language-Action Models

arXiv:2606.20754v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have shown strong performance in robotic manipulation, but reliable uncertainty quantification remains challenging,

Prediction of Solar Flares Using Photospheric Magnetic Field Parameters with Deep Learning

arXiv:2606.21896v1 Announce Type: cross Abstract: Solar flares, particularly those of the M- and X-class, have a significant impact on human life because of their potential to disrupt critical infrast

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