Search: “local-ai”

DAG-Based QoS-Aware Dynamic Task Placement for Networked Multi-Stage Control Pipelines

arXiv:2605.19887v1 Announce Type: cross Abstract: Current Physical AI (PAI) relies heavily on closed-loop visual-servoing pipelines, whose perception and planning stages may become computationally int

local-aiarxiv-cs-ro

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Local Ai

Descriptive versus Regulatory Uncertainty in Bounded Predictive Systems

DGX agent

arXiv:2605.18909v1 Announce Type: new Abstract: Any system that models the world under finite representational capacity must compress; any compression entails a prior; and the prior is the system's bi

local-aiarxiv-cs-lg

20 May 2026

Draft Less, Retrieve More: Hybrid Tree Construction for Speculative Decoding

arXiv:2605.20104v1 Announce Type: cross Abstract: Speculative decoding (SD) accelerates large language model inference by leveraging a draft-then-verify paradigm. To maximize the acceptance rate, rece

Dual-Channel Tensor Neural Networks: Finite-Sample Theory and Conformal Structure Selection

arXiv:2605.19122v1 Announce Type: cross Abstract: Tensor-valued data arise naturally in neuroimaging, genomics, climate science, and spatiotemporal networks, where multilinear dependencies across mode

Efficient coding along the visual hierarchy

arXiv:2605.19155v1 Announce Type: new Abstract: Biological visual systems learn from limited experience, unlike deep learning models that rely on millions of training images. What learning principles

Efficient Conditioning Why Pseudo Observation Batch Bayesian Optimization Works When It Does not

arXiv:2605.18819v1 Announce Type: new Abstract: Constant Liar (CL), Kriging Believer (KB), and fantasy models are widely used for batch selection in parallel Bayesian Optimization, yet a unified theor

FieldFormer: Locality-Aware Transformers for Spatio-Temporal Modeling on Sparse Sensor Networks

arXiv:2510.03589v2 Announce Type: replace Abstract: Spatio-temporal sensor data in real-world systems is often sparse, noisy, and irregular, making latent field reconstruction fundamentally underconst

FormalASR: End-to-End Spoken Chinese to Formal Text

arXiv:2605.19266v1 Announce Type: cross Abstract: Automatic speech recognition (ASR) systems are typically optimized for verbatim transcription, which preserves disfluencies, filler words, and informa

Gaussian Approximation and Multiplier Bootstrap for Federated Linear Stochastic Approximation

arXiv:2605.19629v1 Announce Type: cross Abstract: In this paper, we establish Berry-Esseen-type bounds for federated linear stochastic approximation (LSA). Our results provide the first federated Gaus

Going PLACES: Participatory Localized Red Teaming for Text-to-Image Safety in the Global South

arXiv:2605.19190v1 Announce Type: cross Abstract: Despite the global deployment of text-to-image (T2I) models, their safety frameworks are largely calibrated to a Western-centric default, creating sig

GRALIS: A Unified Canonical Framework for Linear Attribution Methods via Riesz Representation

arXiv:2605.05480v2 Announce Type: replace-cross Abstract: The main XAI attribution methods for deep neural networks -- GradCAM, SHAP, LIME, Integrated Gradients -- operate on separate theoretical foun

GRASP: Deterministic argument ranking in interaction graphs

arXiv:2605.19141v1 Announce Type: cross Abstract: Large language models are increasingly deployed as automated judges to evaluate the strength of arguments. As this role expands, their legitimacy depe

GRLoc: Geometric Representation Regression for Visual Localization

arXiv:2511.13864v2 Announce Type: replace Abstract: Absolute Pose Regression (APR) has emerged as a compelling paradigm for visual localization. However, APR models typically operate as black boxes, d

Hierarchical Schedule Optimization for Fast and Robust Diffusion Model Sampling

arXiv:2511.11688v3 Announce Type: replace-cross Abstract: Diffusion probabilistic models have set a new standard for generative fidelity but are hindered by a slow iterative sampling process. A powerf

iDiff: Interpretable Difference-aware Framework for Pairwise Image Quality Assessment

arXiv:2605.19522v1 Announce Type: new Abstract: Pairwise image quality assessment (IQA) in professional photography requires a model not only to identify the preferred image between two candidates, bu

INSIGHTS: Demonstration-Based Summaries of Time Series Predictors

arXiv:2605.18849v1 Announce Type: cross Abstract: Explainability methods have progressed rapidly, but global explanations for time-series models remain underdeveloped, with most approaches focusing on

KIO-planner: Attention-Guided Single-Stage Motion Planning with Dual Mapping for UAV Navigation

arXiv:2605.19703v1 Announce Type: new Abstract: Autonomous UAV flight in confined, wall-dense environments requires low-latency and reliable motion planning under strict safety constraints. Traditiona

local-aiarxiv-cs-ro

Landscape-Awareness for Geometric View Diffusion Model

arXiv:2605.19865v1 Announce Type: new Abstract: Accurate camera viewpoint estimation under sparse-view conditions remains challenging, particularly in two-view scenarios. Recent approaches leverage di

Learning to Hand Off: Provably Convergent Workflow Learning under Interface Constraints

arXiv:2605.19140v1 Announce Type: new Abstract: We study workflow learning in a setting where specialized agents hand off control through a shared artifact, each agent observes only a local function o

Mechanisms of Object Localization in Vision-Language Models

arXiv:2605.19792v1 Announce Type: new Abstract: Visually-grounded language models (VLMs) are highly effective in linking visual and textual information, yet they often struggle with basic classificati

Multi-Pedestrian Safety Warning at Urban Intersections Use Case of Digital Twin

arXiv:2605.18823v1 Announce Type: new Abstract: Digital twins (DTs) for urban transportation systems have gained increasing attention; however, their systematic evaluation in safety-critical scenarios

NORi: An ML-Augmented Ocean Boundary Layer Parameterization

arXiv:2512.04452v2 Announce Type: replace-cross Abstract: NORi is a machine learning (ML) parameterization of ocean boundary layer turbulence that is physics-based and augmented with neural networks.

OEP: Poisoning Self-Evolving LLM Agents via Locally Correct but Non-Transferable Experiences

arXiv:2605.18930v1 Announce Type: cross Abstract: Memory-augmented large language model (LLM) agents use iterative reflection and self-evolution to solve complex tasks, but these mechanisms introduce

On-Device Continual Learning with Dual-Stage Buffer and Dynamic Loss for Point-of-Care Pneumonia Diagnosis

arXiv:2605.19201v1 Announce Type: cross Abstract: Deep learning models detect pneumonia from chest X-rays with high accuracy, but the performance declines under domain shifts caused by differences in

Perceptual misalignment of texture representations in convolutional neural networks

arXiv:2604.01341v2 Announce Type: replace Abstract: Mathematical modeling of visual textures traces back to Julesz's intuition that texture perception in humans is based on local correlations between

Posterior Contraction of Levy Adaptive B-spline Regression in Besov Spaces

arXiv:2605.19610v1 Announce Type: cross Abstract: We investigate the asymptotic properties of the Levy Adaptive B-spline (LABS) regression model, a Bayesian nonparametric method that incorporates B-sp

PRISM-SLAM: Probabilistic Ray-Grounded Inference for Scale-aware Metric SLAM

arXiv:2605.19257v1 Announce Type: new Abstract: Monocular SLAM historically suffers from scale ambiguity and tracking failure in dynamic environments. While recent vision foundation models (VFMs) prov

local-aiarxiv-cs-ro

Query-Conditioned Graph Retrieval for Contextualized LLM Reasoning in Personalized Wearable Data

arXiv:2605.18763v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly applied to analyzing wearable sensing data, which are long-term, multimodal, and highly personalized. A

Real-Time Parallel Counterfactual Regret Minimization

arXiv:2605.19928v1 Announce Type: cross Abstract: Counterfactual Regret Minimization (CFR) is the dominant algorithmic family for solving large imperfect-information games, underpinning breakthroughs

Rethinking Visual Attribution for Chest X-ray Reasoning in Large Vision Language Models

arXiv:2605.20158v1 Announce Type: cross Abstract: Large Vision Language Models (LVLMs) show promise in medical applications, but their inability to faithfully ground responses in visual evidence raise

Slot-MLLM: Object-Centric Visual Tokenization for Multimodal LLM

arXiv:2505.17726v3 Announce Type: replace-cross Abstract: Recently, multimodal large language models (MLLMs) have emerged as a key approach in achieving artificial general intelligence. In particular,

StableGrad: Backward Scale Control without Batch Normalization

arXiv:2605.19856v1 Announce Type: cross Abstract: Training very deep neural networks requires controlling the propagation of magnitudes across depth. Without such control, activations and gradients ma

STRIDE: Learnable Stepwise Language Feedback for LLM Reasoning

arXiv:2605.18851v1 Announce Type: new Abstract: Recent advances in Reinforcement Learning (RL) have underscored its potential for incentivizing reasoning capabilities of Large Language Models (LLMs).

Tango3D: Towards Alignment for Global and Local 2D-3D Correspondence

arXiv:2605.19727v1 Announce Type: new Abstract: Existing 3D foundation models typically align point clouds to frozen vision-language spaces like CLIP, which achieve strong cross-modal retrieval by com

Thinking in Scales: Accelerating Gigapixel Pathology Image Analysis via Adaptive Continuous Reasoning

arXiv:2605.19491v1 Announce Type: new Abstract: Traditional whole slide image (WSI) analysis methods typically rely on the multiple instance learning (MIL) paradigm, which extracts patch-level feature

Understanding and Exploiting Weight Update Sparsity for Communication-Efficient Distributed RL

arXiv:2602.03839v2 Announce Type: replace Abstract: Bandwidth-constrained distributed reinforcement learning (RL) post-training of large language models is bottlenecked by two channels: weight synchro

Using Aristotle API for AI-Assisted Theorem Proving in Lean 4: A Formalisation Case Study of the Grasshopper Problem

arXiv:2605.20120v1 Announce Type: new Abstract: AI-assisted theorem proving can now generate substantial Lean developments for olympiad-level mathematics, but the evidential status of such development

Your Neighbors Know: Leveraging Local Neighborhoods for Backdoor Detection in Decentralized Learning

arXiv:2605.19969v1 Announce Type: new Abstract: Decentralized learning (DL) is an emerging machine learning paradigm where nodes collaboratively train models without a central server. However, the col

AdaptiveLoad: Towards Efficient Video Diffusion Transformer Training

arXiv:2605.17923v1 Announce Type: cross Abstract: In video generation models, particularly world models, training large-scale video diffusion Transformers (such as DiT and MMDiT) poses significant com

ADMEDTAGGER: an annotation framework for distillation of expert knowledge for the Polish medical language

arXiv:2601.09722v2 Announce Type: replace-cross Abstract: In this work, we present an annotation framework that demonstrates how a multilingual LLM pretrained on a large corpus can be used as a teache

ALIGN: A Vision-Language Framework for High-Accuracy Accident Location Inference through Geo-Spatial Neural Reasoning

arXiv:2511.06316v3 Announce Type: replace Abstract: In low- and middle-income countries, public safety and urban planning initiatives frequently face a critical shortage of accurate, location-specific

ANNEAL: Adapting LLM Agents via Governed Symbolic Patch Learning

arXiv:2605.16309v1 Announce Type: new Abstract: LLM-based agents can recover from individual execution errors, yet they repeatedly fail on the same fault when the underlying process knowledge--operato

AtlasVid: Efficient Ultra-High-Resolution Long Video Generation via Decoupled Global-Local Modeling

arXiv:2605.16649v1 Announce Type: new Abstract: Recent diffusion-based video generators have achieved remarkable visual fidelity and prompt controllability, yet scaling them to ultra-high-resolution (

Attend Locally, Remember Linearly: Linear Attention as Cross-Frame Memory for Autoregressive Video Diffusion

arXiv:2605.16579v1 Announce Type: new Abstract: Autoregressive (AR) video diffusion is a powerful paradigm for streaming and interactive video generation. However, its reliance on softmax self-attenti

Aurora: Unified Video Editing with a Tool-Using Agent

arXiv:2605.18748v1 Announce Type: new Abstract: Recent video editing models have converged on a unified conditioning design: a single diffusion transformer jointly consumes text, source video, and ref

Axial-Relation Guided Fusion State Space Model for Optical-Elevation Sensing Image Segmentation

arXiv:2605.16768v1 Announce Type: new Abstract: Semantic segmentation of multi-source remote sensing images is a fundamental task for Earth observation applications. Existing methods often struggle wi

Beyond Inference-Time Search: Reinforcement Learning Synthesizes Reusable Solvers

arXiv:2605.18374v1 Announce Type: cross Abstract: Large language models (LLMs) typically approach combinatorial optimization as an inference-time procedure, solving each instance separately through sa

Beyond the Cartesian Illusion: Testing Two-Stage Multi-Modal Theory of Mind under Perceptual Bottlenecks

arXiv:2605.18194v1 Announce Type: new Abstract: While Multi-Modal Large Language Models (MLLMs) demonstrate impressive capabilities in general reasoning, their embodied spatial intelligence remains ha