local ai

According to AMD, Arm, and Microsoft, agentic AI could push CPU-to-GPU ratios from 1:4 to even1:1

In OCP APAC 2026, Tai AMD SVP of compute and enterprise AI said agents don't cut GPU demand but they just pile on a whole extra layer of orchestration, retrieval, and tool-calling work that runs on CP

local-air-localllama

Local Ai

Beyond Detection: Evaluating Defensive LLMs Against AI-Generated Social Engineering in Live Turn-by-Turn Interaction

DGX agent

arXiv:2608.10239v1 Announce Type: new Abstract: Generative AI makes social-engineering attacks more fluent, adaptive, and scalable, increasing the need for LLM-based de- fenders that can protect users

local-aiarxiv-cs-ai

12 Aug 2026

Certify or Refuse: A Cross-Model Map for Selective Risk Control with Coverage Floors under Covariate Shift

arXiv:2608.10893v1 Announce Type: new Abstract: Certified selective predictors attain whatever coverage they attain; operators impose an automation floor: answer at least a eta-fraction of shifted tar

local-aiarxiv-cs-cl

Conversational Orchestration for Organic 6G

arXiv:2608.10714v1 Announce Type: cross Abstract: The Organic 6G vision of a network of networks spanning an edge-cloud continuum complemented by non-terrestrial resources requires, to realize its pro

Easy3D-Labels: Supervising Semantic Occupancy Estimation with 3D Pseudo-Labels for Automotive Perception

arXiv:2509.26087v5 Announce Type: replace Abstract: In perception for automated vehicles, safety is critical not only for the driver but also for other agents in the scene, particularly vulnerable roa

Embedding Rotation Invariance for Provable Multi-Oriented Scene Text Recognition

arXiv:2608.10684v1 Announce Type: new Abstract: Multi-oriented text is ubiquitous in real-world scenes and remains a major challenge for scene text recognition (STR). Existing rotation-aware methods e

Embodied Multimodal Grounding for Open-Vocabulary Mobile Manipulation via Semantic 3D Gaussian Splatting

arXiv:2608.10756v1 Announce Type: cross Abstract: Embodied mobile manipulation requires language, visual observations, three-dimensional scene structure, and action feasibility to be aligned before ex

ENCORE: Efficient Noise Context-Aware Representation for Low-Dose CT Denoising

arXiv:2608.10343v1 Announce Type: new Abstract: While deep learning-based denoising has become widely adopted in low-dose CT, conventional models use generic architectures designed for natural images,

FITTER: Vocabulary-Agnostic Cross-Domain Inference on Temporal Knowledge Graphs

arXiv:2608.10668v1 Announce Type: new Abstract: Temporal knowledge graphs are central to many uses of the Semantic Web, but existing completion methods assume the entities, relation names, and timesta

Grid-Preserving Knowledge Distillation: Transferring Convolutional Inductive Bias to Vision Transformers under Data Scarcity

arXiv:2608.10723v1 Announce Type: new Abstract: Vision Transformers underperform convolutional networks when training data is scarce, and distilling convolutional inductive biases from a CNN teacher i

How to do clean uninstall of chatgpt desktop app on windows?

ChatGPT desktop app will not download images even after a complete reinstall I am on Windows 11 and the Download button in the ChatGPT desktop app does nothing when I try to download generated images.

local-air-chatgpt

JEPA-WAM: Stage-Level Joint-Embedding Prediction for World-Action Models in Robot Manipulation

arXiv:2608.10780v1 Announce Type: new Abstract: Generalist robot policies aim to map multimodal observations and linguistic task instructions to actions across diverse tasks. However, existing methods

Learning Gaussian Structure: Intervention-Guided Density Control for Feed-Forward Driving Reconstruction

arXiv:2608.11077v1 Announce Type: new Abstract: Feed-forward Gaussian reconstruction has recently emerged as an efficient approach for driving scene reconstruction. However, prevailing LiDAR-based met

Lesion-Aware Adaptive Fourier Neural Operator for CT-to-PSMA PET Synthesis in Prostate Cancer

arXiv:2608.10429v1 Announce Type: new Abstract: Deep learning models that synthesize PET from CT or MRI can reduce patient dose and scanner demand, but are typically optimized with global losses such

LiquidAI/LFM2.5-VL-3B · Hugging Face

LFM2.5-VL-3B is a multimodal variant of LFM2.5, a family of hybrid models designed for on-device deployment. It builds on LFM2-VL-3B with further mid- and post-training. LFM2.5-VL-3B can process both

local-air-localllama

Local AI is exploding! Transformers.js, that we've been building @huggingface for the past three years has now become the most popular open-…

Local AI is exploding! Transformers.js, that we've been building @huggingface for the past three years has now become the most popular open-source library to run AI models directly in your browser and

local-aiclem-delangue--x

MultiModal Code-Switching: Interleaving Visual Objects into Language for Explicit Object-Level Alignment

arXiv:2608.11167v1 Announce Type: cross Abstract: Existing Multimodal Large Language Models (MLLMs) predominantly rely on image-text pairs for modality alignment pretraining, mapping global image repr

local-aiarxiv-cs-cl

P3CA: Encoder-Agnostic Interpretation of Vision Foundation Model Embeddings via Spatial Probing

arXiv:2608.10131v1 Announce Type: new Abstract: Vision foundation models are increasingly used as reusable encoders in medical image computing, yet their high-dimensional spatial embeddings are diffic

PBD-AG: Persistent Baseline-Delta Active Graphs with Uncertainty-Aware Inspection for Long-Horizon Service Robots

arXiv:2608.10449v1 Announce Type: new Abstract: Long-horizon service robots require persistent world models that can be built autonomously in unseen environments and revised as task-relevant objects c

Quantum Coordination Advantages in AI State-Tracking Tasks: Semantic Compilation and Latent Memory

arXiv:2608.11066v1 Announce Type: cross Abstract: We prove inference-time quantum coordination advantages for specified AI state-tracking tasks. A solver compresses semantic history into a future-acce

R4DSG: Relative 4D Scene Graph Memory for Object-Centric Question Answering in Long Egocentric Video

arXiv:2608.11017v1 Announce Type: cross Abstract: Long-horizon egocentric video is a rich substrate for wearable AI assistants, but object-centric questions such as where an item was moved, when it la

RAG for regular users?

One of the reasons I got into local LLMs was the possibility of getting answers using my own documents and books (a few hundreds) instead of having to search through them manually. However since I'm n

local-air-localllama

Reconfiguration of pivoting cube ensembles under local sensing constraints using geometric deep learning

arXiv:2509.03140v2 Announce Type: replace-cross Abstract: We demonstrate that local sensing is sufficient for effective global reconfiguration of homogeneous pivoting cube modular robots in two dimens

Retrieval-Corrected Conformal Prediction for Time Series

arXiv:2608.10553v1 Announce Type: cross Abstract: Conformal prediction (CP) provides distribution-free prediction intervals for fixed forecasters, but its standard calibration procedure is often ineff

SafeCA: Safe Cross-Attention Localization and Regulation for Text-to-Video Jailbreak Defense

arXiv:2608.10933v1 Announce Type: new Abstract: Text-to-Video (T2V) generative models are vulnerable to jailbreak attacks in real-world deployment, leading them to produce harmful or inappropriate con

SCOUT: Symmetric Consensus Outlier Detection for Failure Localization in LLM Pre-Training

arXiv:2608.11034v1 Announce Type: cross Abstract: In LLM pre-training, synchronization propagates rank-local stalls, slowdowns, and numerical errors into job-wide symptoms, obscuring their origin. Exi

local-aiarxiv-cs-lg

Sensor-Informed Per-Point Covariance for Structured-Light 3D Imaging

arXiv:2608.10888v1 Announce Type: new Abstract: Per-point uncertainty models are important in structured-light 3D reconstruction for probabilistic registration, fusion, and quality assessment. In prac

Sheaf-Based Federated Representation Learning

arXiv:2608.10016v1 Announce Type: cross Abstract: Heterogeneous federated systems require agents to learn and exchange informative representations despite differences in data distributions, sensing mo

Structural Guidance for Unified Joint Demosaicing and Denoising

arXiv:2608.09995v1 Announce Type: cross Abstract: Joint demosaicing and denoising is a fundamental step in camera image signal processing, yet remains challenging because different Bayer-like color fi

Temporal Straightening for Latent Planning

arXiv:2603.12231v3 Announce Type: replace Abstract: Learning good representations is essential for latent planning with world models. While pretrained visual encoders produce strong semantic visual fe

local-aiarxiv-cs-lg

The Illusion of Cross-Lingual Safety in Low-Resource Languages

arXiv:2608.11146v1 Announce Type: new Abstract: Safety alignment in large language models (LLMs) is largely developed in English, assuming these safeguards generalize across multilingual settings. How

local-aiarxiv-cs-cl

The Kuramoto Neural Operator: Learning to Solve PDEs via Coupled Oscillator Dynamics

arXiv:2608.10234v1 Announce Type: cross Abstract: Operator learning is a rapidly advancing area of computational science. It is particularly well suited to problems where a partial differential equati

local-aiarxiv-cs-lg

ThinkAfford: Affordance-Centric Reasoning for Fine-Grained 3D Grounding in Cluttered Scenes

arXiv:2608.10981v1 Announce Type: new Abstract: Task-driven 3D affordance grounding aims to localize the functional region in a cluttered 3D scene that enables an action specified by a natural-languag

Token-Based Detection of Spurious Correlations in Vision Transformers

arXiv:2509.04009v2 Announce Type: replace-cross Abstract: Due to their powerful feature association capabilities, neural network-based computer vision models have the ability to detect and exploit uni

Toward the Cognitive--Physical Limits of Embodied Intelligence through a World-Model-Centric Autonomous Racing Agent

arXiv:2608.10618v1 Announce Type: new Abstract: Embodied artificial intelligence aims to develop agents that perceive, reason, and act through continuous interaction with the physical world. However,

UniProbe: A Learnable Token-Level Hallucination Detector for Large VLMs using Multi-Structural Internal Representations

arXiv:2608.10835v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs) achieve impressive visual reasoning and dialogue capabilities, yet frequently hallucinate content unsupported by th

VidForensics-M1: Meta-Detection Reinforcement Learning with Verifiable Temporal Grounding for AI-Generated Video Forensics

arXiv:2608.11201v1 Announce Type: new Abstract: Recent advances in video generation models have significantly improved the realism of synthetic videos, blurring the boundary between generated and auth

When Vision Becomes Text: Visual Token Pruning via Cross-Modal Residual Guidance in VLMs

arXiv:2608.10489v1 Announce Type: new Abstract: Abundant visual information strengthens vision-language model (VLM) perception, yet massive visual tokens raise inference costs. Existing visual token p

You can now use Ollama as a provider in GitHub Copilot for JetBrains. https://github.blog/changelog/2026-08-11-copilot-memory-and-ollama-in-…

GitHub announced on August 12 2026 that users can now integrate Ollama as a provider in **GitHub Copilot for JetBrains**. This update allows JetBrains developers to switch to or add locally‑hosted (or

local-aiollama--x

4D-WAM: Infusing Spatiotemporal Awareness into World Action Models through Trajectory Fields

arXiv:2608.08023v1 Announce Type: new Abstract: Building on recent advances in world models, World Action Models (WAMs) jointly model video prediction and action generation. However, they typically re

Agentic AI-driven Immersive Simulation: A Knowledge-Aware Virtual Training Platform forHigh Dose Rate (HDR) Brachytherapy

arXiv:2608.08163v1 Announce Type: new Abstract: The convergence of the Metaverse and Large Language Model (LLM)-based AI agent is catalyzing a shift toward autonomous, immersive, and personalized peda

Agentic Stage-One Stellarator Optimization: Autonomous Multi-Objective Search for Finite-Beta Equilibria

arXiv:2608.01344v2 Announce Type: replace Abstract: Stage-one stellarator design searches a high-dimensional family of three-dimensional plasma boundaries and fixed-boundary MHD equilibria for configu

An AI Scientist that Doesn't Drift: Taste, Structure, and Falsifiable Findings in a Quadruped Navigation Research Loop

arXiv:2608.07542v1 Announce Type: new Abstract: Autonomous research loops driven by large language models can run machine-learning experiments at scale but tend to drift toward local refinements of wh

AquiLLM: An Architecture for Supporting Tacit Knowledge Capture in Research Groups

arXiv:2608.08883v1 Announce Type: new Abstract: Recent advances in retrieval-augmented generation (RAG) and large language models (LLMs) enable researchers to integrate AI into scientific workflows. H

Auditing Medical Vision-Language Models on Chest Radiographs: Estimating Reference Agreement Across Institutions

arXiv:2608.07550v1 Announce Type: new Abstract: Vision-language models return structured chest-radiograph findings through interfaces exposing no confidence score, so a receiving institution cannot re

Beyond Hazard Resemblance: Contrastive Event Adjudication for Training-Free Video Anomaly Detection

arXiv:2608.09908v1 Announce Type: new Abstract: Video anomaly detection (VAD) aims to identify and temporally localize abnormal events in videos. Supervised methods learn anomaly decision boundaries f

Beyond the Plane: Coupling Planar Vehicle Dynamics with Three-Dimensional Road Geometry

arXiv:2608.09402v1 Announce Type: new Abstract: Simulation is crucial for developing and testing autonomous driving systems. In particular, the development of localization and control algorithms relie

Beyond Uniform Restoration: Empowering All-in-One Restoration with Pixel-Level Multimodal Guidance

arXiv:2608.09482v1 Announce Type: cross Abstract: All-in-one image restoration is a unified low-level vision task that aims to effectively recover high-quality images from inputs degraded by various t