Search: “local-ai”

Global Optimization on Graph-Structured Data via Gaussian Processes with Spectral Representations

arXiv:2511.07734v2 Announce Type: replace Abstract: Bayesian optimization (BO) is a powerful framework for optimizing expensive black-box objectives, yet extending it to graph-structured domains remai

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Local Ai

.@GoogleDeepMind EmbeddingGemma 2 is now available on Ollama. Made for consumer devices and is multimodal. ollama pull embeddinggemma-2

DGX agent

.@GoogleDeepMind EmbeddingGemma 2 is now available on Ollama. Made for consumer devices and is multimodal. ollama pull embeddinggemma-2 Meet EmbeddingGemma 2, our first natively multimodal open model

local-aiollama--x

6 Oct 2026

Greedy Local Learning for Language Model Pretraining: Gaps and Objective Design

arXiv:2610.04867v1 Announce Type: new Abstract: Greedy block-wise local learning splits a network into gradient-isolated blocks trained by local auxiliary losses, deleting the backward pass between bl

Hierarchical Credit Assignment for RLVR on Fused Gromov-Wasserstein Geometry

arXiv:2610.04344v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has been shown to improve the reasoning capability of large language models (LLMs) across diverse

HunyuanImage 3.0 (80B) running natively in ComfyUI on a single 12–24 GB GPU: text-to-image, editing and style transfer, ~30 s per image

local-air-stablediffusion

I've been working on native ComfyUI support for Tencent's HunyuanImage 3.0, the 80B mixture-of-experts image model (13B active per step). It isn't a wrapper around Tencent's pipeline: it uses the norm

Hybrid-Basis Feature Forecasting for Diffusion Sampling Acceleration

arXiv:2610.05254v1 Announce Type: new Abstract: We propose Hybrid-Basis Feature Forecasting (HybridFF), a training-free, plug-and-play framework for accelerating diffusion sampling. To capture local s

I made a Chrome extension that filters your YouTube feed with a small local model running in the browser (WebGPU, no server)

My YouTube feed was mostly songs, pranks and celebrity clips, so I built a filter that judges each video title with a small decision model running inside Chrome. Nothing is sent anywhere: no server, n

local-air-localllama

I made a Forge Neo extension for MiniMax H3: text or picture to video with sound, reference pictures, runs on 16 GB

local-air-stablediffusion

I've been working on an extension that runs MiniMax H3 inside Forge Neo. H3 makes the picture and the sound together, in one pass: footsteps, rain, engines, music and dialogue in pretty much any langu

I made a tiny (~8MB) photo editor for AI images with batch editing, LUTs, and ComfyUI workflow preservation [Free & Open Source]

local-air-stablediffusion

I was tired of opening heavy photo editors just to tweak lighting or color-grade a folder of AI generations. So I built TinyLuma - an instant, lightweight photo editor designed specifically for finish

I trained a model to be wrong 98% of the time and 96% sure about it. It took three tries.

Meet Bev. She is a decision model (the Jev / Nimble kind: you give her a situation and a question, she gives a probability for each answer), fine-tuned on Qwen3.5-9B to pick the worst answer on purpos

local-air-localllama

IGA-KAN: Isogeometric Analysis with Physics-Informed Closed-Form Kolmogorov-Arnold Networks for Forward and Inverse PDEs

arXiv:2610.06348v1 Announce Type: cross Abstract: Isogeometric analysis (IGA) solves partial differential equations accurately on exact NURBS geometry, whereas neural solvers are mesh-free but often o

In-Context Time Series Classification with Random Convolutional Features

arXiv:2607.19234v2 Announce Type: replace Abstract: Time series classification is central to domains such as medical signal analysis, industrial monitoring, and sensor-based activity recognition, wher

IRSTD-Agent: Agentic Infrared Small Target Detection via Zoom-Guided Interaction Learning

arXiv:2610.05342v1 Announce Type: new Abstract: Infrared small-target detection plays an important role in maritime monitoring and aerial surveillance. Although multimodal large language models (MLLMs

Is Escalation Worth It? On the Depth of LLM Cascades

arXiv:2605.06350v2 Announce Type: replace Abstract: LLM cascades, in which a cheap model defers to an expensive one on low-confidence queries, are widely used to reduce inference cost. Given a pool of

Kinematics-Centric Continuous Sign Language Retrieval with Gloss-Guided Boundary-Aware Alignment

arXiv:2610.05306v1 Announce Type: new Abstract: Sign language-text alignment remains a fundamental challenge for text-driven sign language understanding. Existing methods predominantly rely on appeara

Lens3D: Target-Conditioned Visual Foveation for Fine-Grained 3D Understanding

arXiv:2610.06611v1 Announce Type: new Abstract: Existing 3D large language models often overlook fine-grained attributes and less visually salient objects and parts, even when relevant evidence is pre

Leveraging Cost-effective Robotics for K-12 STEM Education through Water Quality Monitoring Tasks

arXiv:2610.04565v1 Announce Type: new Abstract: Engaging K-12 students in authentic scientific research remains a significant challenge, particularly at the intersection of environmental science and r

LightVLN: Efficient Aerial Vision-and-Language Navigation with Compact Memory and History-Guided Local Aggregation

arXiv:2610.05024v1 Announce Type: new Abstract: Aerial vision-and-language navigation (VLN) enables unmanned aerial vehicles to execute long-horizon natural-language instructions from visual observati

LLM-enhanced spatio-temporal learning for grid-level docked bike sharing demand prediction

arXiv:2610.03834v1 Announce Type: new Abstract: Short-term bike-sharing demand forecasting is complicated by spatial-temporal non-stationarity and the practical difficulty of incorporating unstructure

Localization Lens for Improving Medical Vision-Language Models

arXiv:2610.04502v1 Announce Type: new Abstract: Medical Vision-Language Models (Med-VLMs) have demonstrated strong capabilities in clinical tasks. However, they often struggle to understand anatomical

Localize-and-Detect: Auditing Task-Level Poisoning in Instruction-Tuned Models

arXiv:2610.03960v1 Announce Type: cross Abstract: Instruction fine-tuning adapts a pretrained language model to follow instructions by training it on instruction--response pairs from a collection of t

Look Where You Say You're Looking: Self-Grounded Attention for Visual Reasoning

arXiv:2610.05023v1 Announce Type: new Abstract: We introduce Self-Saliency, a method for training Vision-Language Models (VLMs) to increase the alignment between their visual attention and the image r

MercerFlow: Flow Matching in a Kernel-Induced Latent Space for Probabilistic Forecasting

arXiv:2610.06039v1 Announce Type: new Abstract: Recent work has shown that probabilistic flow matching for time series forecasting benefits from a data-matched prior. The resulting prior introduces lo

Microsoft confirms OpenAI has been using Looped Transformers in the GPT-6 series

Microsoft confirms on publicly accessible web page that OpenAI has been using Looped Transformers in the GPT-6 series, proving The Information's reporting was correct all along. GPT-6.1 Sol uses 2 inf

local-air-localllama

Moment-Accurate Gaussian Mixtures for Constant-Step Stochastic Approximation

arXiv:2610.05595v1 Announce Type: cross Abstract: Local Gaussian models of constant-step learning predict output variability and expected losses, but weak convergence alone does not justify these mome

MTV: Revisiting Multi-Task Visual Representation Learning

arXiv:2601.13886v2 Announce Type: replace Abstract: Current visual representation learning remains bifurcated: vision-language models (e.g., CLIP) excel at global semantic alignment but lack spatial p

No Concept Escapes the Audit: Auditing-Aware Unlearning for Verifiable Concept Erasure in Diffusion Models

arXiv:2610.05401v1 Announce Type: new Abstract: Text-to-image diffusion models can generate prohibited content, which motivates concept erasure through machine unlearning. Most erasure methods interve

Nonlinear Density-Driven Optimal Control (D2OC) for Multi-Agent Spatial Coverage via Sequential Convex Programming

arXiv:2610.04545v1 Announce Type: cross Abstract: This paper presents a nonlinear extension of Density-Driven Optimal Control (D2OC) for multi-agent spatial coverage with prescribed density distributi

Ollama Cloud Model Cost Table on Github

Ollama Cloud Model pricing monitor with tabled costs and calculator. https://kasp0r.github.io/ollama_cloud_models_comparison https://preview.redd.it/hxbpnuq7quth1.png?width=1372&format=png&auto=webp&s

local-air-ollama

OncoNoteBERT: A Foundation Representation Model for Natural Language Processing of Real-World Outpatient Oncology Notes

arXiv:2610.03829v1 Announce Type: cross Abstract: Real-world outpatient oncology notes contain specialised terminology, tumour staging expressions, treatment names, toxicity descriptions, and institut

Optimal Control with Learned Critics under Unmodeled State Dependencies

arXiv:2610.05359v1 Announce Type: new Abstract: Model Predictive Control (MPC) provides a structured and constraint-aware mechanism for decision-making, but its reliance on optimization-friendly analy

Organize Primitives into Semantic Parts: Reinforcement Reasoning for 3D Segmentation

arXiv:2610.04602v1 Announce Type: new Abstract: Primitive-based 3D segmentation offers a compact and explicit alternative to dense surface prediction, naturally supporting structural abstraction and b

Personal VAD: Speaker-Conditioned Voice Activity Detection

arXiv:1908.04284v5 Announce Type: replace-cross Abstract: In this paper, we propose 'personal VAD', a system to detect the voice activity of a target speaker at the frame level. This system is useful

PhaseGate: Phase-Aware CPU Retrieval Scheduling for On-Device LLMs on Unified Memory

arXiv:2610.04537v1 Announce Type: new Abstract: On-device assistants run GPU-based LLM inference alongside CPU retrieval on unified-memory systems. Under a saturated local-retrieval workload, four con

Population Scaling or Data Dilution? Dynamics of Local Topology Evolution in Decentralized Learning

arXiv:2610.05476v1 Announce Type: new Abstract: Scaling decentralized learning changes not only the number of clients N, but also the dynamics of information propagation and consensus. We argue that t

PreAct-Nav: Agentic Reasoning Before Action for Urban Navigation

arXiv:2610.04916v1 Announce Type: new Abstract: Urban navigation requires embodied agents to pursue long-horizon goals through local decisions based on egocentric observations. However, existing agent

Prompt and Refinement: Asymmetric Mutual Learning for Infrared Small Target Detection with Noisy Labels

arXiv:2610.05918v1 Announce Type: new Abstract: Existing data-driven infrared small target detection (ISTD) methods typically require large-scale datasets with accurate pixel-level annotations for mod

RAGrasp: Geometry-Semantic Template Retrieval and Grasp Transfer

arXiv:2610.04438v1 Announce Type: cross Abstract: We present RAGrasp, a retrieval-augmented pipeline for planar parallel-jaw grasping from a compact set of locally collected, grasp-annotated RGB-D (co

Reachability-Guided Sequential Quadratic Programming-Guarded Model Predictive Path Integral for Safe Nonlinear Predictive Control

arXiv:2610.04406v1 Announce Type: new Abstract: Safe robot control often requires combining long-horizon performance optimization with hard state and input constraints, but existing approaches tend to

RealtimeWAM: One-Step Asynchronous World Action Models

arXiv:2610.06617v1 Announce Type: new Abstract: World Action Models (WAMs) incorporate visual representations from video generation backbones to guide action prediction. Recent efficient WAMs adopt Mi

ReDiffNet: Differential RGB-Infrared Learning for Low-Light UAV Oriented Vehicle Detection

arXiv:2610.05074v1 Announce Type: new Abstract: Low-light UAV-based RGB-infrared oriented small-vehicle detection is important for nighttime traffic monitoring, emergency response, and urban inspectio

RepTC: Representation-Aware Optimization for Efficient Traffic Classification on Edge IoT Devices

arXiv:2610.04784v1 Announce Type: cross Abstract: Traffic classification (TC) is crucial to secure Internet of Things (IoT) networks, whose edge nodes often operate under privacy, bandwidth, and energ

Residual Visual Credit Optimization: Conserved Evidence Routing for Multimodal Reinforcement Learning

arXiv:2610.04918v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards scales multimodal reasoning, but an outcome reward says how much a trajectory is worth, not how that valu

Robust Ensemble Guidance for Scientific Inverse Problems

arXiv:2610.05371v1 Announce Type: new Abstract: Ensemble guidance combines pretrained diffusion priors with black-box forward models to solve inverse problems without differentiating through the physi

Robust Local Optimization Done Right

arXiv:2610.05743v1 Announce Type: new Abstract: RANSAC scoring and local optimization (LO) impose different robustness requirements, motivating the separation of hypothesis selection from refinement.

ROT: Rotating Hidden States towards Contextual Vectors for Hallucination Mitigation in LVLMs

arXiv:2610.06056v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs) frequently suffer from object hallucination. Existing training-free interventions primarily manipulate attention we

RPFQ-ViT: Rotated Phase-Frame Quantization for Extremely Low-Bit Weights in Vision Transformers

arXiv:2610.04457v1 Announce Type: new Abstract: Vision Transformers (ViTs) achieve strong performance on image recognition and mobile vision applications, but their high-dimensional linear projections

Scalable Minimal-Change Learning for Controllable Image Editing

arXiv:2610.06021v1 Announce Type: new Abstract: Image editing should change only the attributes specified by an instruction while preserving everything else, yet current methods often make unintended