Search: “local-ai”

Critical Ollama Vulnerabilities: Memory Leak + Windows Updater RCE Risk

Ollama versions prior to 0.17.1 contain a critical out-of-bounds read vulnerability (CVE-2026-7482, CVSS 9.1) that allows remote unauthenticated attackers to leak entire process memory, potentially af

local-air-ollama

Local Ai

DeCo-DETR: Decoupled Cognition DETR for efficient Open-Vocabulary Object Detection

DGX agent

arXiv:2604.02753v2 Announce Type: replace Abstract: Open-vocabulary Object Detection (OVOD) enables models to recognize objects beyond predefined categories, but existing approaches remain limited in

local-aiarxiv-cs-cv

11 May 2026

Distributional simplicity bias and effective convexity in Energy Based Models

arXiv:2605.07844v1 Announce Type: new Abstract: Energy-based learning is a powerful framework for generative modelling, but its training is inherently non-convex, leading potentially to sensitivity to

DualResolution Residual Architecture with Artifact Suppression for Melanocytic Lesion Segmentation

arXiv:2508.06816v3 Announce Type: replace Abstract: Lesion segmentation, in contrast to natural scene segmentation, requires handling subtle variations in texture and color, frequent imaging artifacts

EditRefiner: A Human-Aligned Agentic Framework for Image Editing Refinement

arXiv:2605.07457v1 Announce Type: new Abstract: Recent text-guided image editing (TIE) models have made remarkable progress, yet edited images still frequently suffer from fine-grained issues such as

Emergent Manifold Separability during Reasoning in Large Language Models

arXiv:2602.20338v2 Announce Type: replace Abstract: Chain-of-Thought (CoT) prompting significantly improves reasoning in Large Language Models, yet the temporal dynamics of the underlying representati

Eulerian Motion Guidance: Robust Image Animation via Bidirectional Geometric Consistency

arXiv:2605.06280v2 Announce Type: replace Abstract: Recent advancements in image animation have utilized diffusion models to breathe life into static images. However, existing controllable frameworks

Federated Spatiotemporal Graph Learning for Passive Attack Detection in Smart Grids

arXiv:2510.02371v2 Announce Type: replace-cross Abstract: Smart grids are exposed to passive eavesdropping, where attackers listen silently to communication links. Although no data is actively altered

FLAM: Evaluating Model Performance with Aggregatable Measures in Federated Learning

arXiv:2605.07962v1 Announce Type: new Abstract: Performance evaluation is essential for assessing the quality of machine learning (ML) models and guiding deployment decisions. In federated learning (F

Future Validity is the Missing Statistic: From Impossibility to Phi-Estimation for Grammar-Faithful Speculative Decoding

arXiv:2605.07698v1 Announce Type: new Abstract: Grammar-constrained generation is often combined with local vocabulary masking and speculative decoding, but the resulting sampling law is not the gramm

Generate split-stack videos like this in a single click. The basic setup is simple, just upload an image and the system takes care of the re…

Generate split-stack videos like this in a single click. The basic setup is simple, just upload an image and the system takes care of the rest. Want more control? Switch to graph mode and fine-tune ea

local-aicomfyui--x

Generating training datasets for legal chatbots in Korean

arXiv:2605.07432v1 Announce Type: new Abstract: Chatbots are robots that can communicate with humans using text or voice signals. Legal chatbots improve access to justice, since legal representation a

local-aiarxiv-cs-cl

Geometric Kolmogorov--Arnold Network (GeoKAN)

arXiv:2605.06740v1 Announce Type: cross Abstract: We introduce Geometric Kolmogorov--Arnold Networks (GeoKANs), a family of geometry-aware KAN-type models in which approximation is carried out in lear

GESR: Graph-Based Edge Semantic Reconstruction for Stealthy Communication Detection with Benign-Only Training

arXiv:2605.07536v1 Announce Type: cross Abstract: Detecting stealthy malicious communications from flow logs under benign-only training remains a critical challenge in network security. Malicious comm

GRAPHLCP: Structure-Aware Localized Conformal Prediction on Graphs

arXiv:2605.08074v1 Announce Type: new Abstract: Conformal prediction (CP) provides a distribution-free approach to uncertainty quantification with finite-sample guarantees. However, applying CP to gra

HARMONY: Bridging the Personalization-Generalization Gap by Mitigating Representation Skew in Heterogeneous Split Federated Learning

arXiv:2605.07211v1 Announce Type: cross Abstract: Mobile devices face diverse resource constraints and non-IID data class distributions, requiring fast on-device inference for local in-distribution (I

HiDream-O1-Dev vs ZImage Base (style comparison)

local-air-stablediffusion

A Reddit discussion comparing HiDream-O1-Image-Dev (the newer, 8B pixel-native distilled model) with ZImage Base, examining stylistic and performance differences between the two text-to-image generati

HMACE: Heterogeneous Multi-Agent Collaborative Evolution for Combinatorial Optimization

arXiv:2605.07214v1 Announce Type: new Abstract: Large Language Models have recently emerged as a promising paradigm for automated heuristic design for NP-hard combinatorial optimization problems. Desp

🆕 Hugging Face 🤝 Hermes Agent 🔥 > we added Hermes Agent to local apps: run it locally with any compatible GGUF/MLX model > shipped native…

🆕 Hugging Face 🤝 Hermes Agent 🔥 > we added Hermes Agent to local apps: run it locally with any compatible GGUF/MLX model > shipped native traces support for Hermes Agent: visualize your Hermes traces

local-aiclem-delangue--x

I made a fixed-camera timelapse showing 2,000 years of Los Angeles evolution — from empty Tongva homeland to modern megacity. The camera never moves. Neither do the mountains.

local-air-stablediffusion

This post describes a fixed-camera timelapse visualization created using AI (likely Stable Diffusion) that depicts Los Angeles's transformation over 2,000 years, starting from its original state as To

Instruction Tuning Changes How Upstream State Conditions Late Readout: A Cross-Patching Diagnostic

arXiv:2605.07284v1 Announce Type: new Abstract: Recent interpretability work has identified model-internal handles on post-trained behavior, including refusal directions, assistant/persona axes, and s

Is She Even Relevant? When BERT Ignores Explicit Gender Cues

arXiv:2605.07622v1 Announce Type: new Abstract: Gender bias in large language models has primarily been investigated for English, while languages with grammatical or morphological gender remain compar

local-aiarxiv-cs-cl

Kurtosis-Guided Denoising Score Matching for Tabular Anomaly Detection

arXiv:2605.06955v1 Announce Type: cross Abstract: Denoising score matching (DSM) provides a way to learn data distributions by training a neural network to recover the score function, defined as the g

Learned Lagrangian Models of PDEs via Euler-Lagrange Residual Minimization

arXiv:2605.07157v1 Announce Type: new Abstract: We present the first method to directly use a learned continuous Lagrangian to forecast the dynamics of systems governed by partial differential equatio

Learning Multi-Relational Graph Representations for DNA Methylation-Based Biological Age Estimation

arXiv:2605.07175v1 Announce Type: cross Abstract: Aging clocks aim to estimate biological age, a measure of physiological state distinct from chronological age, from observable biomarkers, and are wid

Learning to Communicate Locally for Large-Scale Multi-Agent Pathfinding

arXiv:2605.07637v1 Announce Type: new Abstract: Multi-agent pathfinding (MAPF) is a widely used abstraction for multi-robot trajectory planning problems, where multiple homogeneous agents move simulta

LiteGUI: Distilling Compact GUI Agents with Reinforcement Learning

arXiv:2605.07505v1 Announce Type: new Abstract: Developing lightweight, on-device vision-language GUI agents is essential for efficient cross-platform automated interaction. However, current on-device

LoHGNet: Infrared Small Target Detection through Lorentz Geometric Encoding with High-Order Relation Learning

arXiv:2605.07213v1 Announce Type: new Abstract: Infrared small target detection (IRSTD) remains challenging due to the scarcity of useful target cues and the presence of severe background clutter. Mos

LTX 2.3 Distilled 1.1 using WwnGP.

local-air-stablediffusion

LTX-2.3 is a multimodal video generation model released by Lightricks in March 2026, available in four checkpoint variants including a distilled variant that completes generation in as few as 8 denois

Modulated learning for private and distributed regression with just a single sample per client device

arXiv:2605.07233v1 Announce Type: new Abstract: This work focuses on the question of learning from a large number of devices with each device holding only a single sample of data. Several real-world a

My @aiDotEngineer talk is live: 'On-device Intelligence using MLX' 🎥 Huge thanks to @swyx and the team for having me — hands down the best …

My @aiDotEngineer talk is live: 'On-device Intelligence using MLX' 🎥 Huge thanks to @swyx and the team for having me — hands down the best tech event I've been to. And a shoutout to the community ship

local-aiswyx--x

On the Tradeoffs of On-Device Generative Models in Federated Predictive Maintenance Systems

arXiv:2605.07860v1 Announce Type: cross Abstract: Federated Learning (FL) has emerged as a promising paradigm for preserving client data ownership and control over distributed Internet of Things (IoT)

Overcoming data scarcity through multi-center federated learning for organs-at-risk segmentation in pediatric upper abdominal radiotherapy

arXiv:2605.06820v1 Announce Type: cross Abstract: Deep learning-based organs/structures-at-risk(OARs) auto-contouring models can improve radiotherapy workflows, but models trained on adult data often

Predictive but Not Plannable: RC-aux for Latent World Models

arXiv:2605.07278v1 Announce Type: cross Abstract: A latent world model may achieve accurate short-horizon prediction while still inducing a latent space that is poorly aligned with planning. A key iss

Publish your workflows: http://links.comfy.org/hubearlyaccess

ComfyUI announced early access to a workflow publishing feature that allows users to share their AI image generation workflows on a hub or marketplace platform. This feature enables the community to d

local-aicomfyui--x

Reachy Mini ready to go! Audio on 🔉 Cleary I'll connect it to Local AI services and to my Hermes Agent really soon 💪

Clem Delangue announced the Reachy Mini robot is operational with audio capabilities enabled, with plans to integrate it with local AI services and a Hermes Agent in the near future. This indicates pr

local-aiclem-delangue--x

Reformulating KV Cache Eviction Problem for Long-Context LLM Inference

arXiv:2605.07234v1 Announce Type: cross Abstract: Large language models (LLMs) support long-context inference but suffer from substantial memory and runtime overhead due to Key-Value (KV) Cache growth

RNAGenScape: Property-Guided, Optimized Generation of mRNA Sequences with Manifold Langevin Dynamics

arXiv:2510.24736v3 Announce Type: replace-cross Abstract: Generating property-optimized mRNA sequences is central to applications such as vaccine design and protein replacement therapy, but remains ch

Search-based Robustness Testing of Laptop Refurbishing Robotic Software

arXiv:2605.07530v1 Announce Type: new Abstract: The Danish Technological Institute (DTI) focuses on transferring advanced technologies (including robots) to the industry and the public sector. One key

local-aiarxiv-cs-ro

Seeing Across Skies and Streets: Feedforward 3D Reconstruction from Satellite, Drone, and Ground Images

arXiv:2605.07978v1 Announce Type: new Abstract: Cross-view localization classically asks: where does this ground image lie on the satellite tile? Existing methods are typically limited to 3-DoF estima

Self Driving Datasets: From 20 Million Papers to Nuanced Biomedical Knowledge at Scale

arXiv:2605.07022v1 Announce Type: new Abstract: Manually curated biomedical repositories -- spanning bioactivity, genomics, and chemistry -- are expensive to maintain, lag behind primary literature, a

Signal Reshaping for GRPO in Weak-Feedback Agentic Code Repair

arXiv:2605.07276v1 Announce Type: new Abstract: Code-agent RL often receives weak feedback: rollout-time signals are reliable and executable, but capture only necessary or surface conditions for task

SoftSAE: Dynamic Top-K Selection for Adaptive Sparse Autoencoders

arXiv:2605.06610v2 Announce Type: replace-cross Abstract: Sparse Autoencoders (SAEs) have become an important tool in mechanistic interpretability, helping to analyze internal representations in both

ST-Gen4D: Embedding 4D Spatiotemporal Cognition into World Model for 4D Generation

arXiv:2605.07390v1 Announce Type: new Abstract: Generative models have achieved success in producing apparently coherent 2D videos, but remain challenging in the physical world due to lack of 4D spati

Susceptibilities and Patterning: A Primer on Linear Response in Bayesian Learning

arXiv:2605.07980v1 Announce Type: new Abstract: These notes introduce the theory of susceptibilities as developed in [arXiv:2504.18274, arXiv:2601.12703] for interpreting neural networks. The suscepti

TAP: Two-Stage Adaptive Personalization of Multi-Task and Multi-Modal Foundation Models in Federated Learning

arXiv:2509.26524v3 Announce Type: replace-cross Abstract: In federated learning (FL), local personalization of models has received significant attention, yet personalized fine-tuning of foundation mod

TCMIIES: A Browser-Based LLM-Powered Intelligent Information Extraction System for Academic Literature

arXiv:2605.07507v1 Announce Type: new Abstract: The exponential growth of academic publications has created an urgent need for automated tools capable of extracting structured knowledge from unstructu

local-aiarxiv-cs-cl

Teaching Prompts to Coordinate: Hierarchical Layer-Grouped Prompt Tuning for Continual Learning

arXiv:2511.12090v3 Announce Type: replace Abstract: Prompt-based continual learning methods fine-tune only a small set of additional learnable parameters while keeping the pre-trained model's paramete