local ai

Air Quality Downscaling with Station-Guided Pseudo-Supervision

arXiv:2607.05292v1 Announce Type: cross Abstract: Super-resolving coarse atmospheric fields to local PM_{2.5} variations is uniquely challenged by a mismatch in spatial support: while pixels represent

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And that's a wrap on World's Fair in SF 🎉 Thanks to everyone who stopped by the booth to say hi and dive into LanceDB internals. Some of th…

DGX agent

And that's a wrap on World's Fair in SF 🎉 Thanks to everyone who stopped by the booth to say hi and dive into LanceDB internals. Some of the best conversations happen at a conference booth and this ye

local-aiollama--x

7 Jul 2026

AULLM++: Structured-Token-Conditioned Large Language Models for Micro-Expression Action Unit Detection

arXiv:2603.08387v2 Announce Type: replace Abstract: Micro-expression Action Unit (AU) detection identifies localized AUs from subtle facial muscle activations, providing a foundation for decoding affe

b9893

b9893 is a release build of llama.cpp with Windows OpenVINO 2026.2.1 support . The llama.cpp project uses continuous build-tagged releases rather than traditional semantic versioning , making b9893 on

b9894

Release b9894 of llama.cpp was published on July 7, 2026 , and includes a Vulkan backend fix to check src0 type in GGML_OP_SET_ROWS to avoid failures due to unimplemented f16 support . Llama.cpp is th

b9895

Release b9895 of llama.cpp includes a fix for speculative inference out-of-bounds read in ngram-map on prompt shrink, with ~2x performance gains in PP_Speed for FP32, Q4_0 and Q8_0 models. The release

b9902

Release b9902 of llama.cpp was released on July 7, 2026 , and includes support for SYCL operations including cross_entropy_loss and cross_entropy_loss_back . The release provides builds across multipl

Btw my interview on Local AI from last week with Latent Space was published on the 2nd page of The Daily Context at AIE

Swyx appeared in an interview on Local AI that was subsequently featured in The Daily Context newsletter from AIEngineer, with the interview appearing on the second page of that publication. The inter

local-aiswyx--x

Can Model Merging Improve Aggregation in DiLoCo?

arXiv:2607.03011v1 Announce Type: cross Abstract: Model merging techniques, which aggregate independently finetuned models into one to combine their capabilities, have become a topic of significant in

Causal-RetiGraph: Cross-Cohort Retinal Support and Same-Subject Pathway Analysis for Diabetic Retinopathy

arXiv:2607.05204v1 Announce Type: new Abstract: Diabetic retinopathy (DR) is a local retinal lesion process and a visible manifestation of systemic microvascular injury. Modern retinal AI can grade im

CORA: Generalizable coronary artery disease assessment and risk stratification from coronary CT angiography using pathology-centric representation learning

arXiv:2603.24847v2 Announce Type: replace Abstract: Coronary artery disease, a leading cause of cardiovascular mortality worldwide, can be assessed non-invasively by coronary computed tomography angio

Ctrl-Z Sampling: Scaling Diffusion Sampling with Controlled Random Zigzag Explorations

arXiv:2506.20294v5 Announce Type: replace Abstract: Diffusion models generate conditional samples by progressively denoising Gaussian noise, yet the denoising trajectory can stall at visually plausibl

Curated retrieval versus open web search in public AI information services: a coverage-trust trade-off

arXiv:2607.05217v1 Announce Type: cross Abstract: Public institutions increasingly use large language models (LLMs) to answer citizens' questions, often pairing a curated knowledge base with live web

local-aiarxiv-cs-cl

Decentralised Federated Learning over Temporal Networks: The Role of Heterogeneities

arXiv:2607.03171v1 Announce Type: cross Abstract: Decentralised federated learning, based on peer-to-peer communication, is increasingly proposed for on-device training of machine learning models, pro

DELTA-TTS: Adapting Autoregressive Model into Diffusion Language Model for Text-to-Speech

arXiv:2607.04140v1 Announce Type: cross Abstract: Autoregressive (AR) text-to-speech (TTS) models generate discrete speech tokens sequentially, which makes inference slow and can degrade robustness by

local-aiarxiv-cs-cl

DELTAVID: Enhancing Fine-Grained Spatiotemporal Perception with Cross-Video Differences

arXiv:2607.02551v1 Announce Type: cross Abstract: Video multimodal large language models have made strong progress on open-ended video understanding, but they still lack precise local spatiotemporal p

Elastic Gang: Per-Token Membership Change for a Hard-Barriered LLM Inference Gang Co-Scheduled with OS Processes

arXiv:2607.04668v1 Announce Type: cross Abstract: On-device LLM decoding is a hard-barriered CPU-SIMD computation that wants every core for milliseconds per token, while the rest of the OS wants those

Enhancing Large Multimodal Models in Key Information Extraction via Scene-Aware Document Synthesis

arXiv:2607.04636v1 Announce Type: new Abstract: Key Information Extraction (KIE) converts visually rich documents into structured data, but practical deployment remains challenging: strong performance

Exploring Convolutional Neural Processes for Weather Downscaling

arXiv:2607.04190v1 Announce Type: new Abstract: Global reanalysis products such as ERA5-Land provide spatially complete weather fields but at resolutions too coarse for local applications, particularl

FAST: A Holistic Framework for Optimizing Memory-I/O, Computation, and Sampling in Temporal GNN Training

arXiv:2607.05095v1 Announce Type: new Abstract: Temporal Graph Neural Networks (TGNNs) are widely used for learning from dynamic graphs in applications such as recommendation, social network analysis,

FDR-Occ: Factorized Dense Routing for Full-Spectrum 3D Occupancy Prediction

arXiv:2607.03822v1 Announce Type: new Abstract: Vision-based 3D occupancy prediction fundamentally relies on the 2D-to-3D view transformation. Current paradigms predominantly utilize explicit physical

FedAvg for HAR: Exploring the Tradeoff Between Personalized and Generalization Accuracy

arXiv:2607.03334v1 Announce Type: cross Abstract: The federated learning (FL) paradigm fosters distributed pervasive computing combined with artificial intelligence techniques, allowing for optimized

Federated Learning for Object Detection: Enabling Collaborative Drone Learning Without Centralizing Data

arXiv:2607.02636v1 Announce Type: cross Abstract: Object detection is a fundamental capability for AI-driven perception in safety-critical drone and edge-vision systems, including disaster response, o

FedSPM: Routing-Enabled Federated Learning under Dual Heterogeneity via Semiparametric Mixture

arXiv:2607.04085v1 Announce Type: cross Abstract: Routing-prediction federated learning has emerged as a new paradigm that reframes inter-client heterogeneity as a resource for system-level intelligen

Flocking phase transition and threat responses in bio-inspired autonomous drone swarms

arXiv:2512.21196v2 Announce Type: replace Abstract: Collective motion inspired by animal groups offers powerful design principles for autonomous aerial swarms. We present a bio-inspired 3D flocking al

local-aiarxiv-cs-ro

Framework for Grouping Local Process Models

arXiv:2607.04856v1 Announce Type: new Abstract: Local Process Models (LPMs) are an underexplored concept in process mining. LPMs describe patterns in event data considering sequence, choice, concurren

From Global to Local: Efficient Regional Weather Downscaling with Global Weather Foundation Model

arXiv:2607.03279v1 Announce Type: new Abstract: Accurate regional weather prediction requires resolving fine-scale structure while remaining consistent with global dynamics. Traditional limited area m

From Reasoning Traces to Reusable Modules: Understanding Compositional Generalization in Language Model Reasoning

arXiv:2606.18089v2 Announce Type: replace Abstract: Post-training pipelines that combine supervised fine-tuning (SFT) with reinforcement learning (RL) have emerged as the key recipe for transforming l

FunPhase: A Periodic Functional Autoencoder for Motion Generation via Phase Manifolds

arXiv:2512.09423v2 Announce Type: replace Abstract: Learning natural body motion remains challenging due to the strong coupling between spatial geometry and temporal dynamics. Embedding motion in phas

G^2TAM: Geometry Grounded Track Anything Model

arXiv:2607.03789v1 Announce Type: new Abstract: Human spatial understanding arises from jointly perceiving geometry and semantics, enabling consistent object identification and localization across vie

Global Logic and Local Search: Dual-Stream Multimodal In-Context Learning for Verifiable Industrial Anomaly Detection

arXiv:2607.03817v1 Announce Type: new Abstract: Large Multimodal Models (LMMs) show strong few-shot generalization, but industrial anomaly detection remains difficult because defects are small, input

GPU-Accelerated Polygonal Signed Distance Functions for Real-Time Collision Avoidance

arXiv:2607.04310v1 Announce Type: new Abstract: Optimization-based local planning and control require high-rate collision-avoidance constraint evaluation over a prediction horizon. In obstacle-dense e

local-aiarxiv-cs-ro

Graph Neural Networks are Heuristics

arXiv:2601.13465v4 Announce Type: replace Abstract: Graph neural networks are usually treated as auxiliaries for combinatorial optimization: they imitate algorithms, guide search, or supply scores to

GRCD: Grounded Region Change Detection for Multi-Finding Chest X-Ray Pairs

arXiv:2607.02719v1 Announce Type: new Abstract: Radiologists routinely compare current and prior chest X-rays to track disease progression, producing follow-up reports that describe multiple findings,

Harmonic-Aware Transformer for Real-Time Catheter Localization in Interventional Procedures of Magnetic Particle Imaging

arXiv:2607.02919v1 Announce Type: cross Abstract: Magnetic particle imaging (MPI) enables real-time, radiation-free tracking of magnetic nanoparticle-coated instruments, making it highly suitable for

Hierarchical Multi-Agent Reinforcement Learning for Carbon-Aware AI Data Centers in Power Distribution Systems

arXiv:2607.03324v1 Announce Type: cross Abstract: Eco-friendly energy management for artificial intelligence data centers (AIDCs) is crucial because of the significant increase in energy consumption-i

How a local-first personal AI agent uses orchestration, memory, tools, LangGraph, background workflows, and child agents

local-aiharrison-chase--x

This post describes architectural patterns for building a local-first personal AI agent, covering key components including orchestration frameworks, memory systems, tool integration, LangGraph for wor

Inpainting U-Net for seamless pedestrian-level wind prediction across urban morphologies

arXiv:2607.02560v1 Announce Type: new Abstract: Pedestrian-level wind prediction is essential for urban design and wind-comfort assessment, but high-fidelity simulations such as LES remain computation

Internal Pluralism and the Limits of Pairwise Comparisons

arXiv:2607.02672v1 Announce Type: new Abstract: Local pairwise comparisons are a standard tool for learning how people want decision rules to work, e.g., in participatory design or alignment. However,

Interpretable Nanoporous Materials Design with Symmetry-Aware Networks

arXiv:2509.15908v3 Announce Type: replace-cross Abstract: Nanoporous materials hold promise for diverse sustainable applications, yet their vast chemical space poses challenges for efficient design. M

Joint Velocity Slope Diffusion Prior for Structurally Constrained Velocity Model Building

arXiv:2607.04982v1 Announce Type: cross Abstract: High-resolution velocity models are crucial for reservoir characterization and subsurface delineation. However, the band limited nature of our surface

Kairos: A Regret-Aware Native World-Action Model Stack for Physical AI

arXiv:2606.16533v3 Announce Type: replace Abstract: We introduce extbf{Kairos}, a regret-aware native world-action model stack for Physical AI. Kairos is motivated by the view that a physical world mo

KAM-WM: Kinematic Affordance Maps from Latent World Models for Robot Manipulation

arXiv:2607.04652v1 Announce Type: new Abstract: Learning manipulation from few demonstrations requires visual priors that capture not only where to interact, but also how the interaction should begin;

local-aiarxiv-cs-ro

LLM for the development of FCM

arXiv:2607.04983v1 Announce Type: cross Abstract: This article is about the development of a fuzzy cognitive map using a local large language model. In the light of recent advances it is evident that

LoMa: Local Feature Matching Revisited

arXiv:2604.04931v2 Announce Type: replace Abstract: Local feature matching has long been a fundamental component of 3D vision systems such as Structure-from-Motion (SfM), yet progress has lagged behin

LP-SFT: Local-Preserving Supervised Fine-Tuning via Multimodal Entropy Structure

arXiv:2607.04733v1 Announce Type: new Abstract: Supervised fine-tuning (SFT) is the standard approach for adapting pretrained language models to downstream domains, yet it often improves target-domain

local-aiarxiv-cs-cl

MambaLIE: Scene Light Intensity-Boosted Low-Light Image Enhancement with State Space Model

arXiv:2607.03013v1 Announce Type: cross Abstract: Images captured by consumer electronic devices, such as mobile phones and digital cameras, often suffer from low-light degradation due to sensor limit

Masked Generative-Contrastive Representation Learning for Cross-Dataset EEG-Based Emotion Recognition

arXiv:2607.04139v1 Announce Type: new Abstract: Self-supervised learning (SSL) shows strong potential for cross-dataset transfer by improving feature representation and generalization. However, its ap