Search: “local-ai”

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

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

DGX agent

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

local-aiarxiv-cs-lg

6 Oct 2026

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

Shared Geometry Is Not Shared Physics: A Layerwise Test of the Platonic Representation Hypothesis in Astronomy

arXiv:2610.04130v1 Announce Type: cross Abstract: In this paper we investigate whether geometrically aligned astronomical representations are also scientifically interchangeable. We analyze every laye

Slaying the Hydra: Interaction-Aware Circuit Discovery in Language Models

arXiv:2610.04017v1 Announce Type: new Abstract: Localizing behavior to individual components of a language model is a central goal of mechanistic interpretability. However, scoring components one at a

SPACE-CLIPv2: Decoding Local Geometry from Frozen CLIP for Monocular Depth Estimation

arXiv:2610.05029v1 Announce Type: new Abstract: Vision-language foundation models such as CLIP provide strong semantic representations, but their patch tokens are not directly optimized for dense metr

STILL: Selecting Tokens for Intra-Layer Hybrid Attention to Linearize LLMs

arXiv:2602.02180v2 Announce Type: replace Abstract: Linearizing pretrained large language models (LLMs) primarily relies on intra-layer hybrid attention mechanisms to alleviate the quadratic complexit

Taylor Representations for Model-Free RL in Networked MDPs

arXiv:2610.05456v1 Announce Type: cross Abstract: In Networked Markov Decision Processes, transition dynamics are often unknown and the state--action space grows rapidly with the number of agents. In

TempoBridge: Source-Conditioned Flow Matching with Optimal Transport Couplings for Single-Cell Population Transitions

arXiv:2610.04945v1 Announce Type: new Abstract: Destructive single-cell measurements provide unpaired population snapshots rather than observations of the same cells across conditions. Local cell stat

Tencent releases Octop, a self-hosted AI assistant

Octop is an open-source, self-hosted AI assistant. Through its multi-agent architecture, it builds an intelligent environment that is both independent and collaborative for teams, families, and indivi

local-air-localllama

The Poisoned Conversation: Privacy-Leaking Watermarks in Unified Multimodal Models

arXiv:2610.05453v1 Announce Type: cross Abstract: Multimodal models are increasingly shifting toward unified architectures that understand and generate text, images, and other modalities within a shar

TimeNet: An Extensible Unified Data Infrastructure for Next-Generation Temporal Foundation Models

arXiv:2610.04407v1 Announce Type: cross Abstract: Temporal Foundation Models (TFMs) aim to generalize across domains, datasets, and tasks. Yet, their development remains constrained by fragmented, tas

Tomorrow, see what’s next from Windows, @surface, and @NVIDIARTXSpark. Tune in live at 10:00 AM PT: https://msft.it/6011aoEeW

On October 6, 2026 Microsoft promoted a live announcement schedule featuring upcoming releases from Windows, Surface devices, and NVIDIA’s RTX Spark suite. The event was set to air at 10:00 AM Pacific

local-aiollama--x

TrustmeWatcher: An Application for Workplace Micro-Sensing and Explainable Well-Being Feedback

arXiv:2610.06657v1 Announce Type: new Abstract: Workplace sensing studies combine long-running behaviour traces with self-reports, yet the tools that collect those data often sit apart from the interf

v0.40.0-rc6: model: add multimodal embeddings (#18820)

Implements the EmbeddingGemma2Model architecture on the MLX runner: 24-layer bidirectional text encoder with PLE, shared gemma4 vision/audio towers, mean-pool + L2 output. /api/embed accepts per-item

local-aiollama-releases

Vela: Scaling Vision-Language-Action Models with Adaptive Action Curve Parametrization

arXiv:2610.05230v1 Announce Type: new Abstract: Most vision-language-action models represent future motion as fixed-rate action chunks, tying temporal resolution and prediction horizon to a fixed outp

local-aiarxiv-cs-ro

Verifier-Guided Synthetic Augmentation for 3D Human Shape Generation

arXiv:2610.04006v1 Announce Type: new Abstract: Limited training data diversity constrains generative modeling of 3D human bodies: conservative models remain close to observed examples, whereas explor

Which Ollama MLX model for medical stuff, charts etc?

Hi, I'm on M4 Pro 64GB Mac, I'm using Qwen3.8 27B for coding related stuff, but it's quite slow. I want a fast model that will be good when it comes to reasoning, medical stuff, would be nice if it co

local-air-ollama

A Locally Penalized Cross-Estimate Federated Method with Guarantees for Constrained Personalized Learning

arXiv:2603.19617v2 Announce Type: replace Abstract: Federated learning (FL) is a communication-efficient framework for solving distributed optimization problems. Standard FL methods aggregate local up

A Path Integral Surrogate for Multi-Step Gradient Inversion in Federated Learning

arXiv:2610.03597v1 Announce Type: new Abstract: Federated learning lets many clients train a shared model together without ever sending their private data to a central server. Each client shares only

Activation Sparsity with Weight Approximation for Faster LLM Decoding on Offloaded Weights

arXiv:2610.02598v1 Announce Type: new Abstract: Deploying LLMs on consumer-grade GPUs with insufficient memory to hold their weights can result in prohibitively slow inference, because decoding repeat

AdaStep: Adaptive Step Credit Weighting for Agentic Reinforcement Learning

arXiv:2610.03223v1 Announce Type: cross Abstract: Long-horizon LLM agents are typically trained with sparse outcome rewards, making trajectory-level objectives too coarse to distinguish the contributi

local-aiarxiv-cs-cl

AI-driven Thermal-aware Data Center Capacity Planning

arXiv:2610.02442v1 Announce Type: new Abstract: The emerging of large language models (LLMs) has posed significant challenges to the thermal management of data center. Intense GPU computation for LLMs

Beyond Entropy: Self-Diagnostic Multi-Role Token Optimization for Video Reasoning

arXiv:2610.03400v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards has substantially advanced multimodal reasoning, yet it remains fundamentally limited by ambiguous token-

Bridging Frontier Reasoning and Robot Execution: From Autonomous Demonstration Generation to Dense Language Supervision

arXiv:2610.03615v1 Announce Type: new Abstract: Recent advances in frontier models enable robot manipulation from only a few demonstrations, but high inference latency limits their use for real-time r

local-aiarxiv-cs-ro

Cordial Learning: Distributed Training with Correlated Data

arXiv:2610.03330v1 Announce Type: cross Abstract: We consider a distributed learning task with agents that have correlated data. Specifically, the label of an agent depends on the input of other agent

CORNAV: Construction-Aware Reasoning for Robot Navigation on Active Worksites

arXiv:2610.03622v1 Announce Type: new Abstract: The construction industry faces persistent labor shortages, low productivity that costs the global economy over $1.6 trillion annually, and one of the h

local-aiarxiv-cs-ro

Corrupted but Correct: Why Vision-Language Models Lie to Themselves Internally

arXiv:2610.03445v1 Announce Type: cross Abstract: A targeted adversarial perturbation can drive a vision-language model's (VLM's) teacher-forced training loss for a fixed target caption to near zero,

CreateScore: Domain-Theory-Informed Bayesian Routing for LLM-Based CV Screening

arXiv:2610.02972v1 Announce Type: new Abstract: Large language models (LLMs) can support rubric-based screening of CVs, but applying a high-capability model to every candidate and criterion is costly.

DecisionTune 1.0: a 395M encoder that picks from your options offline, about 10 ms per short decision on MLX (Apache-2.0)

Disclosure: I made this. Sharing it here because it is fully local and small, and I want feedback from people who run models on their own machines. What it is: a 395M decision model (ModernBERT-large

local-air-localllama

Depth Hypothesis Guided Iterative Refinement for Event-Image Monocular Depth Estimation

arXiv:2610.03439v1 Announce Type: new Abstract: Event cameras hold excellent dynamic properties, showing great potential for monocular depth estimation (MDE). However, existing methods mainly improve

Differential Privacy as a Perk: Federated Learning over Multiple-Access Fading Channels with a Multi-Antenna Base Station

arXiv:2510.23463v4 Announce Type: replace Abstract: Federated Learning (FL) is a distributed learning paradigm that preserves privacy by eliminating the need to exchange raw data during training. In i

Does Physics Live in the Activations? Localizing Physical Quantities in Video Diffusion Models

arXiv:2610.03154v1 Announce Type: new Abstract: Video generation models produce strikingly realistic sequences and are increasingly proposed as world models, yet recent benchmarks reveal pronounced de

Electronic Density versus Geometry for Machine-Learned Molecular Absorption Spectra

arXiv:2610.03444v1 Announce Type: cross Abstract: Molecular optical absorption spectroscopy provides a direct probe of electronic structure and is widely used for molecular identification, interpretat

EviDent-CBCT: Evidence-Bottlenecked Report Generation from Dental CBCT under Non-Exhaustive Report Supervision

arXiv:2610.02375v1 Announce Type: cross Abstract: Dento-maxillofacial cone-beam CT (CBCT) reports may contain dozens of tooth-specific, anatomical, and spatial findings from a single 3D scan. Learning

Excited about the new open model from @reflection_ai! More US models coming to Ollama!

Excited about the new open model from @reflection_ai! More US models coming to Ollama! Introducing Beam: a highly efficient agentic open model with 501B total parameters and 23B active. - Frontier rea

local-aiollama--x

FactorSplat: Appearance-Controllable Gaussian Proxies for Medical Volume Rendering

arXiv:2610.02382v1 Announce Type: new Abstract: Transfer functions (TFs) control color and visibility in medical volume rendering, but image-trained Gaussian proxies typically bake one transfer functi

Fed-ADApt: Federated Anytime Depth Adaptation for Resource-Aware Medical Image Segmentation

arXiv:2610.03474v1 Announce Type: new Abstract: Federated learning (FL) enables collaborative training of medical image segmentation models without sharing raw patient data, yet existing approaches as

From Fragments to Global Maps: Learning Vectorized Map Aggregation with Large Language Models

arXiv:2610.02513v1 Announce Type: cross Abstract: Large-scale vectorized HD maps provide structured road information that is essential for perception, localization, and planning in autonomous driving.

Harnessing LLMs as Agents: What Does It Cost?

arXiv:2610.02488v1 Announce Type: new Abstract: Language-model agents increasingly rely on harnesses that manage bounded context, persistent memory, tools, verification, and repeated execution, yet ex

How Artificial Intelligence LLM Engines Shape the Global Conflict Information Environment

arXiv:2607.14197v2 Announce Type: replace Abstract: Artificial Intelligence (AI) answer engines now field a growing share of the questions that analysts, scholars, and the public ask about issues of p

HXAI: Hierarchical Privacy-Preserving Explainable AI in Distributed Energy Systems

arXiv:2610.02504v1 Announce Type: new Abstract: Balancing electricity demand and supply is increasingly difficult due to the inherent intermittency of renewable power generation and the stochastic pow

I have trained a model to predict my blood sugar (Part 2) [P]

local-air-machinelearning

This is related to my previous post where I shared an encoder-only transformer model trained on ohiot1dm + shanghait1dm + azt1d datasets. This time I trained the model on the outputs of my T1DM patien

ItoTTS: two natural English voices in 4.89 MB for a $5 ESP32-S3

Hi everyone! I'm part of the Lokutor team. Last week we presented Oído here, and the response was amazing. We've received dozens of videos and messages from you guys saying you love it. Thank you! Now

local-air-localllama