Search: “local-ai”

An Ontology-Guided, Deduplication-Aware Extraction Layer for Knowledge Graph Construction from Heterogeneous Documents

arXiv:2607.28662v1 Announce Type: new Abstract: Large language models extract entities and relationships from unstructured documents fluently but inconsistently: type vocabularies fracture across docu

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Artifact detection and localization in single-channel mobile EEG for sleep research using deep learning and attention mechanisms

DGX agent

arXiv:2504.08469v3 Announce Type: replace-cross Abstract: Current methods for detecting artifacts in sleep EEG range from threshold-based algorithms to machine learning approaches, yet applications re

local-aiarxiv-cs-lg

3 Aug 2026

Best Friends, Not Forever: Evaluating Long-Horizon Persona Collapse and Behavioral Drift in AI Companions

arXiv:2607.28818v1 Announce Type: new Abstract: As AI companions increasingly mediate repeated social interaction, users may rely on a stable role and shared history, yet locally acceptable replies do

CENDRe: Concept Extraction with Natural Domain Representations

arXiv:2607.29621v1 Announce Type: cross Abstract: Convolutional neural networks (CNNs) are widely used for time-series classification, but their deployment in critical domains requires understanding t

Classification of COVID-19 cases from chest CT volumes using hybrid model of 3D CNN and 3D MLP-Mixer

arXiv:2607.28978v1 Announce Type: new Abstract: This paper proposes an automated classification method of COVID-19 chest CT volumes using improved 3D MLP-Mixer. Novel coronavirus disease 2019 (COVID-1

CoDe-SSM: Context-Detail Decoupled State Space Model for Efficient UHD Image Restoration

arXiv:2607.29595v1 Announce Type: new Abstract: Ultra-high-definition (UHD) image restoration must balance the aggregation of spatially recurring degradation cues with the preservation of localized im

CPInj: Uncovering Prompt Injection Risks in Textual Collaborative Prompt Optimization

arXiv:2607.18622v2 Announce Type: replace-cross Abstract: Textual Collaborative Prompt Optimization (TCPO) extends TextGrad (Yuksekgonul et al., 2025) to a decentralized setting by allowing multiple c

Deconstructing Off-Policy Ratios: Entropy-Scaled Trust Regions for Asynchronous Reinforcement Learning

arXiv:2607.22186v2 Announce Type: replace Abstract: Asynchronous reinforcement learning (RL) accelerates large language model (LLM) post-training by overlapping rollout generation with policy optimiza

DFSC: Error-Controlled Differentiable Mittag-Leffler Propagation for Fractional Scientific Machine Learning

arXiv:2607.29038v1 Announce Type: new Abstract: Fractional scientific machine learning requires numerical operators that can be differentiated, batched, accelerated, and composed with neural networks.

GQ-FSL: Green Quantized Federated Split Learning

arXiv:2607.29659v1 Announce Type: new Abstract: Deploying state-of-the-art deep neural networks (DNNs) at the wireless edge is severely bottlenecked by the strict energy and resource constraints of mo

HERO: History-Enriched Rollout Training for Long-Horizon Autoregressive Neural Operators

arXiv:2607.29135v1 Announce Type: cross Abstract: Neural operators provide fast surrogates for time-dependent partial differential equations (PDEs) by applying a learned evolution operator recursively

LightningRL: Breaking the Accuracy-Parallelism Trade-off of Block-wise dLLMs via Reinforcement Learning

arXiv:2603.13319v2 Announce Type: replace Abstract: Diffusion Large Language Models (dLLMs) have emerged as a promising paradigm for parallel token generation, with block-wise variants garnering signi

MBDiff: Multi-view Behavior-aware Diffusion Model for Probabilistic Utility Data Imputation

arXiv:2607.29177v1 Announce Type: cross Abstract: Utility data (e.g., electricity, water, and gas consumption), collected by ubiquitous sensors and embedded devices, often contains substantial missing

Mitigating Class-Tail Undercoverage in Medical Vision-Language Models under Clinical Shift

arXiv:2607.28696v1 Announce Type: cross Abstract: Medical vision-language models (VLMs) can retain high observed marginal coverage after clinical shift while substantially under-covering an individual

MMFGU: Multimodal Federated Graph Unlearning

arXiv:2607.28708v1 Announce Type: new Abstract: Multimodal federated graph learning enables clients to collaboratively train graph models over structural, textual, and visual signals without sharing p

MOT-SR: Multi-Objective Tool-Augmented Scientific Equation Discovery with Large Language Models

arXiv:2607.29561v1 Announce Type: cross Abstract: Symbolic Regression (SR) aims to discover analytical equations from observational data and plays a central role in scientific modeling. While recent L

Multimodal Reinforcement Learning with Adaptive Verifier for AI Agents

arXiv:2512.03438v3 Announce Type: replace Abstract: Agentic reasoning models trained with multimodal reinforcement learning (MMRL) have become increasingly capable, yet they are almost universally opt

OnlineCache: Learning Dynamic Caching Policies with Error Correction for Efficient Diffusion Inference

arXiv:2607.29398v1 Announce Type: new Abstract: Diffusion models have revolutionized generative tasks but incur high latency due to iterative denoising. While cache-based strategies accelerate inferen

Optimal Resource Allocation for ML Model Training and Deployment under Concept Drift

arXiv:2512.12816v2 Announce Type: replace Abstract: We study how to allocate resources for training and deployment of machine learning (ML) models under concept drift and limited budgets. We consider

Progressive Decision-Making for Localizing Open-Ended AI-Generated Image Forgeries

arXiv:2607.29156v1 Announce Type: new Abstract: AI-generated image forgeries are becoming increasingly realistic and difficult to characterize with fixed manipulation patterns. As generative models co

RecHarness: A Bandit-Routed Agentic Harness for Self-Evolving Recommender Systems

arXiv:2607.29241v1 Announce Type: cross Abstract: Optimizing modern recommender models still depends heavily on engineers manually iterating over architectural, objective, and training-strategy change

Reflection or Re-Generation? Why LLM Revision Fails Where Human Revision Succeeds

arXiv:2607.28908v1 Announce Type: new Abstract: Reflection, the ability to revisit and revise prior reasoning, is central to how humans improve their answers. Large language models (LLMs) are increasi

SafeNexus: Discovering and Steering Modality-Universal Safety Neurons in MLLMs

arXiv:2607.28969v1 Announce Type: new Abstract: Although Large Language Models (LLMs) have demonstrated promising safety performance, extending them to Multimodal Large Language Models (MLLMs) exposes

Small Is Enough: Per-User Style Rewriting of AI-Edited Text via LoRA Adapters

arXiv:2607.29238v1 Announce Type: cross Abstract: InMyStyle is a privacy first, single user system that adapts small language models to rewrite AI-edited text towards an individual user's writing styl

TacPrint: A Wearable Fingertip Tactile Sensor for Human-to-Robot Contact Reproduction

arXiv:2607.29231v1 Announce Type: new Abstract: Human-centric data collection is emerging as a significant paradigm for robot skill acquisition, but seamlessly integrating low-cost, scalable tactile s

local-aiarxiv-cs-ro

Versatile On-device Adaptation at the Edge by Unifying Few-shot, Zero-shot, Continual, and In-context Learning

arXiv:2607.29353v1 Announce Type: cross Abstract: With the ever-increasing pervasiveness of smart edge devices, the demand is growing for applications that can be tailored to users (e.g., custom keywo

WaiT for the Signal: Simple Frequency-Aware Flow-Matching

arXiv:2607.28760v1 Announce Type: cross Abstract: As image generation models scale to ever higher resolutions, global coherence, local detail, and texture fidelity become critical axes for generation

Who Wins Where? Conformal Model Comparison for Local Superiority

arXiv:2607.29053v1 Announce Type: new Abstract: Standard model comparison is global, aggregating losses across the covariate space to declare a single winner. This can obscure heterogeneous performanc

Zero-Mem: Zero-Token Memory Operations for LLM Agents

arXiv:2607.29377v1 Announce Type: new Abstract: LLM agents need memory to act consistently over long interactions, yet many systems use additional LLM calls to operate that memory. Generating intermed

local-aiarxiv-cs-cl

AlphaSchema: Exploring the Space of Trading Semantics for LLM-Based Alpha Mining

arXiv:2607.26642v1 Announce Type: new Abstract: Automated alpha mining has increasingly adopted large language model (LLM) agents for factor generation and iterative discovery. However, existing LLM-b

Auto Research for Materials: Auditable AI-Scientist Workflows with Held-Out Transfer

arXiv:2607.17100v2 Announce Type: replace-cross Abstract: Auto Research uses language-model agents to propose, implement, and evaluate machine-learning changes in a closed loop, but is usually judged

Beyond the Best Teacher: Expanding and Compressing the Reasoning Solution Manifold

arXiv:2607.27770v1 Announce Type: new Abstract: A single reinforcement-learning run can produce a strong reasoner yet an incomplete teacher: it often amplifies only a subset of the valid solution mode

Can Vision-Language Models Reason about AI Edits in Images?

arXiv:2607.28464v1 Announce Type: new Abstract: Detection and localization of AI-tampered images are critical for trustworthy AI, yet modern generative models have made such manipulations increasingly

Capturing Token Tendencies for Training-Free Token Pruning in Multimodal Large Language Models

arXiv:2607.28341v1 Announce Type: new Abstract: While visual token pruning is essential for efficient Multimodal Large Language Models (MLLMs), existing training-free methods suffer from a critical li

Compact Task-Aligned Imitation Learning for Laboratory Automation

arXiv:2603.01110v2 Announce Type: replace Abstract: Robotic laboratory automation has traditionally relied on carefully engineered motion pipelines and task-specific hardware interfaces, resulting in

local-aiarxiv-cs-ro

DinoLizer: Separating VAE and Diffusion Artifacts in Generative Inpainting Localization

arXiv:2511.20722v2 Announce Type: replace Abstract: We introduce DinoLizer, a DINOv2-based localizer of manipulated areas in generative inpainting. The model is trained to focus on semantically altere

Emulating Cosmic Structure Formation with a Lagrangian Neural Cellular Automaton

arXiv:2607.27320v1 Announce Type: cross Abstract: Field-level inference of cosmological initial conditions from galaxy surveys requires a forward model that is simultaneously accurate in the non-linea

Explaining Image Similarity with Automatically Extracted Concept Activation Vectors

arXiv:2607.28386v1 Announce Type: new Abstract: Image similarity underlies many computer vision applications, yet it is often unclear why two images receive a high or low similarity score. Existing ex

FeatFix: Reuse What You Verify through Local Exact-Feature Correction for Faster Cached Diffusion Inference

arXiv:2607.27842v1 Announce Type: new Abstract: Diffusion models are widely used to generate high-quality images and videos, but their iterative denoising process remains computationally intensive. A

First-order Constrained Trilevel Optimization Over Distributed Networks for Robust Coreset Selection

arXiv:2607.27632v1 Announce Type: new Abstract: With the rapid advancement of the Internet of Things (IoT), massive amounts of data are generated across distributed edge networks. Training models on f

Kohn-Sham Spectral Embedding on Sparse Graphs at the Nishimori Temperature for Image Classification

arXiv:2607.28428v1 Announce Type: cross Abstract: We introduce Kohn--Sham Spectral Embedding (KSSE), a physics-inspired energy-based model replacing dense CNN classifiers with a sparse-graph spectral

LightRot: A Light-Weighted Rotation Scheme and Architecture for Accurate Low-Bit Large Language Model Inference

arXiv:2607.27704v1 Announce Type: cross Abstract: As large language models (LLMs) continue to demonstrate exceptional capabilities across various domains, the challenge of achieving energy-efficient a

Now You Have My Healthy Attention: A U-DiT for Brain-MRI Inpainting

arXiv:2607.27974v1 Announce Type: new Abstract: The ASNR-MICCAI BraTS Local Synthesis (Inpainting) task asks for the anatomically plausible completion of healthy brain tissue within a masked region of

ScaFE: Data-Efficient Scar Classification with LLM-Generated Clinical Feature Programs

arXiv:2607.28538v1 Announce Type: new Abstract: Classifying pathological scars from clinical photographs requires distinguishing keloids from hypertrophic scars despite limited expert-labeled data and

Secure Aggregation for Privacy-Preserving Federated Learning on Clinical EEG Data

arXiv:2607.28191v1 Announce Type: cross Abstract: Federated learning enables multiple institutions to train shared models without exchanging raw clinical EEG data, but it does not fully prevent privac

VCP-DCN: Beyond Visual Concealed Property via Depth Collaborative Network for Camouflaged Object Detection

arXiv:2607.27843v1 Announce Type: new Abstract: Camouflaged Object Detection (COD) aims to identify and segment camouflaged objects in complex environments, which are often concealed because their col

When Should AI Follow? Task Structure and Joint Adaptation by Human and AI Agents

arXiv:2504.20903v4 Announce Type: replace-cross Abstract: How should organizations divide and sequence decision tasks between human and artificial agents? We develop a computational model of joint seq

Write-Safe Flow Field Mapping under Ambiguous Onboard Sensing and Localization Drift

arXiv:2607.27713v1 Announce Type: new Abstract: Mobile robots can infer local flow structure from onboard sensing, but a locally plausible estimate is not always safe to write into a global map. Simil

local-aiarxiv-cs-ro