Search: “local-ai”

UniNote: A Unified Embedding Model for Multimodal Representation and Ranking

arXiv:2605.29287v1 Announce Type: cross Abstract: Item-to-Item (I2I) retrieval is a fundamental part of modern content platforms, supporting critical industrial workflows from recommendation engines t

29 May 2026

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Unsupervised Semantic Segmentation Facilitates Model Understanding

DGX agent

arXiv:2605.29691v1 Announce Type: new Abstract: Self-supervised learning (SSL) has produced a diverse landscape of vision transformers (ViTs) whose pretrained representations support a wide range of d

local-aiarxiv-cs-cv

29 May 2026

When Cloud Agents Meet Device Agents: Lessons from Hybrid Multi-Agent Systems

arXiv:2605.30102v1 Announce Type: cross Abstract: The design space of agentic AI inference spans two extremes: frontier large language models (LLMs), typically hosted in the cloud and offering strong

29 May 2026

A Generalized Tikhonov Layer for Interpretable-by-design Graph Neural Networks

arXiv:2605.28578v1 Announce Type: new Abstract: We propose the Tikhonov layer, a graph neural network layer that is interpretable by design: once trained, its learned parameters directly reveal which

A Paired Testing Protocol for Batch-Conditioned Refusal Robustness in LLM Serving

arXiv:2605.27763v1 Announce Type: new Abstract: Safety evaluations of language models often treat serving configuration as fixed background infrastructure, but batch condition is an untested treatment

A Spatially Informed Gaussian Process UCB Method for Decentralized Coverage Control

arXiv:2511.02398v2 Announce Type: replace Abstract: We present a novel decentralized algorithm for coverage control in unknown spatial environments modeled by Gaussian Processes (GPs). To trade-off be

Accelerating Robot Path Planning via Connectivity-Preserving Region Proposal Network

arXiv:2605.28362v1 Announce Type: new Abstract: Mobile robot path planning methods are often constrained by vast search spaces, resulting in latency in samplingbased algorithms. Learning-based approac

local-aiarxiv-cs-ro

An Evolutionary Approach for Designing Stable and Highly Expressible Low-Immunogenicity Therapeutic mRNA Sequences

arXiv:2605.27986v1 Announce Type: new Abstract: Messenger RNA (mRNA) sequences as therapeutics require optimized design to ensure efficient translation, structural stability, and minimal immunogenicit

Backdoor Attacks on Fault Detection and Localization in Cyber-Physical Systems

arXiv:2605.27674v1 Announce Type: cross Abstract: Cyber-Physical Systems (CPS) integrate sensing, communication, computation, and control to support critical infrastructure, including smart grids, ind

Beyond Lipschitz: Data-Driven Robustness via Discrete Modulus of Continuity

arXiv:2605.28729v1 Announce Type: cross Abstract: Robustness of neural networks is commonly quantified via local or global Lipschitz constants. However, Lipschitz continuity can be overly coarse or ov

CIVIC: End-to-End Sequence Compactness for Efficient Vision-Language Models

arXiv:2605.28115v1 Announce Type: new Abstract: Vision-Language Models (VLMs) face severe memory and latency bottlenecks due to high-resolution visual tokens. While current token reduction methods the

CLANE: Continual Learning of Actions on Neuromorphic Hardware from Event Cameras

arXiv:2605.28387v1 Announce Type: cross Abstract: Recognizing and continuously learning novel human actions without forgetting prior classes is a requirement for emerging AR/VR and robotics applicatio

ClinicalEncoder26AM: A Multlilingual Diagnosable ColBERT Model; Evidences from the MultiClinNER Shared Task

arXiv:2605.28521v1 Announce Type: new Abstract: ClinicalEncoder26AM is a multilingual Diagnosable ColBERT for clinical and biomedical texts, which aligns at multiple levels its token-level semantic wi

Decoupling Skeleton and Flesh: Efficient Multimodal Table Reasoning with Disentangled Alignment and Structure-aware Guidance

arXiv:2602.03491v2 Announce Type: replace-cross Abstract: Reasoning over table images remains challenging for Large Vision-Language Models (LVLMs) due to complex layouts and tightly coupled structure-

DeepC4: Deep Conditional Census-Constrained Clustering for Large-scale Multitask Spatial Disaggregation of Urban Morphology

arXiv:2507.22554v3 Announce Type: replace Abstract: To understand our global progress for sustainable development and disaster risk reduction in many developing economies, two recent major initiatives

Dual-branch Distilled Transformer for Efficient Asymmetric UAV Tracking

arXiv:2605.28018v1 Announce Type: new Abstract: Given the real-time demands of UAV tracking, many methods simplify the backbone to reduce computation, but this often weakens feature representation and

FD-RAG: Federated Dual-System Retrieval-Augmented Generation

arXiv:2605.27432v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) has emerged as a paradigm for grounding large language models in external knowledge, yet most existing RAG system

Geometry-First Generative Spatial Single-Cell Reconstruction

arXiv:2605.28200v1 Announce Type: new Abstract: Single-cell RNA sequencing (scRNA-seq) profiles large numbers of cells but loses spatial context, whereas spatial transcriptomics (ST) preserves partial

HarmoVid: Relightful Video Portrait Harmonization

arXiv:2605.28811v1 Announce Type: new Abstract: We present a method for harmonizing the lighting of a foreground video to match a target background scene, adjusting shadows, color tone, and illuminati

HARP: Measuring Harm Amplification in Multi-Agent LLM Systems

arXiv:2605.27489v1 Announce Type: cross Abstract: Multi-agent LLM systems decompose workflows across agents, tools, shared context, memory, and decision gates. This modularity improves interpretabilit

Identifying Explicit Parsimonious Piece-wise Polynomial Relationships in Industrial time-series: Application to manipulator robots

arXiv:2605.28320v1 Announce Type: cross Abstract: This paper addresses the problem of identifying parsimonious explicit piece-wise polynomial relationships that might involve a relatively large number

Integrating Inductive Biases in Transformers via Distillation for Financial Time Series Forecasting

arXiv:2603.16985v2 Announce Type: replace Abstract: Transformer-based models have been widely adopted for time-series forecasting due to their high representational capacity and architectural flexibil

Locality-Aware Redundancy Pruning for LLM Depth Compression

arXiv:2605.27786v1 Announce Type: cross Abstract: Large language models are known to contain representational redundancy across network depth, making depth pruning an effective approach for improving

Localizing Input Uncertainty Quantification for Large Language Models via Shapley Values

arXiv:2605.28170v1 Announce Type: new Abstract: As large language models (LLMs) are increasingly integrated into high-stakes decision-making, the ability to reliably quantify uncertainty has become a

Machine learning enables experimental access to photon-by-photon arrival times in scintillation detectors

arXiv:2605.27937v1 Announce Type: cross Abstract: Scintillation detectors with excellent timing resolution enable more precise localization of radiation sources in positron emission tomography, leadin

MM-PoisonRAG: Disrupting Multimodal RAG with Local and Global Poisoning Attacks

arXiv:2502.17832v4 Announce Type: replace-cross Abstract: Retrieval-augmented generation (RAG) has become a common practice in multimodal large language models (MLLM) to enhance factual grounding and

MMRad-22K: A Structured Multimodal Evidence Dataset for Chest X-ray Report Generation

arXiv:2602.12843v2 Announce Type: replace Abstract: Chest X-ray (CXR) reporting follows a region-based clinical workflow in which radiologists inspect anatomical regions and integrate localized findin

OmniVerifier-M1: Multimodal Meta-Verifier with Explicit Structured Recalibration

arXiv:2605.28805v1 Announce Type: cross Abstract: Visual outcomes are increasingly central to multimodal large language models, making reliable and fine-grained verification essential for scaling gene

OSP-Next: Efficient High-Quality Video Generation with Sparse Sequence Parallelism, HiF8 Quantization, and Reinforcement Learning

arXiv:2605.28691v1 Announce Type: new Abstract: Diffusion Transformers achieve strong video generation quality, but the quadratic cost of full attention limits efficiency. We introduce OSP-Next, an ef

Outer-Momentum Restarting in High-Dimensional Two-Phase Optimization

arXiv:2605.28585v1 Announce Type: new Abstract: Communication-efficient distributed optimizers such as DiLoCo reduce synchronization costs by letting workers perform many local updates before aggregat

PocketGS: On-Device Training of 3D Gaussian Splatting for High Perceptual Modeling

arXiv:2601.17354v5 Announce Type: replace Abstract: While 3D Gaussian Splatting (3DGS) enables real-time rendering, its training demands workstation-level compute and memory, making mobile deployment

Reading or Guessing? Visual Grounding Failures of Vision-Language Models for OCR in Ancient Greek Editions

arXiv:2605.27750v1 Announce Type: cross Abstract: Recent work has shown that Vision-Language Models (VLMs) used for optical character recognition (OCR) can generate plausible but visually unsupported

Reverse Probing: Supervised Token-level Uncertainty Quantification for Large Language Models in Clinical Text

arXiv:2605.28740v1 Announce Type: cross Abstract: As large language models are increasingly deployed for clinical text, ensuring they can reliably signal their own uncertainty becomes critical. Most e

Robust Contrastive Graph Clustering with Adaptive Local-Global Integration

arXiv:2605.28209v1 Announce Type: new Abstract: Graph clustering is essential in graph analysis for revealing structural patterns and node communities. Despite recent advances in self-supervised contr

ROVER: Routing Object-Centric Visual Evidence for Grounded Multi-Image Reasoning

arXiv:2605.27959v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) have increasingly localized and interleaved visual evidence for deliberative reasoning. Grounding-based appro

Sentence Curve Language Models

arXiv:2602.01807v3 Announce Type: replace Abstract: Language models (LMs) are a central component of modern AI systems, and diffusion language models (DLMs) have recently emerged as a competitive alte

SIGMA: Semantic-Difference Instruction-Grounding Mask Annotator for Text-Driven Image Manipulation Localization

arXiv:2605.27924v1 Announce Type: new Abstract: Text-driven image editing has advanced rapidly, but reliably localizing these manipulations requires image manipulation localization (IML) models traine

Soft Specialists: alpha-Renyi Ensembles for Uncertainty-Aware LLM Post-Training

arXiv:2605.27747v1 Announce Type: cross Abstract: Existing training approaches for large language models learn a single set of parameters, based on large volumes of data, which is typically heterogene

The Energy Blind Spot: NVIDIA's Flagship Edge AI Hardware Cannot Support Process-Level Energy Attribution

arXiv:2605.27599v1 Announce Type: cross Abstract: Agentic AI workloads - where a single user goal triggers multi-step orchestration, tool calls, retries, and failure recovery - are being targeted for

The Shape of Overthinking: Backtracking Bursts in Long Reasoning Traces

arXiv:2605.27965v1 Announce Type: new Abstract: Reasoning models often generate long traces in which useful self-correction and unproductive revision are hard to distinguish. We study this distinction

Trust Region Continual Learning as an Implicit Meta-Learner

arXiv:2602.02417v2 Announce Type: replace Abstract: Continual learning aims to acquire tasks sequentially without catastrophic forgetting, yet standard strategies face a core tradeoff: regularization-

When NPUs Are Not Always Faster: A Stage-Level Analysis of Mobile LLM Inference

arXiv:2605.27435v1 Announce Type: cross Abstract: Deploying large language models (LLMs) on mobile devices increasingly relies on heterogeneous execution, yet no prior study has systematically charact

Where Does Toxicity Live? Mechanistic Localization and Targeted Suppression in Language Models

arXiv:2605.27997v1 Announce Type: cross Abstract: Large language models frequently generate toxic, hateful, or harmful content, yet existing mitigation methods rely on costly retraining or output-leve

AIDG: A Formal Decomposition of Information Extraction and Containment Asymmetries in Multi-Turn LLM Dialogue

arXiv:2602.17443v2 Announce Type: replace Abstract: Multi-turn LLM evaluation is typically reported as a single win-rate scalar, conflating distinct capabilities. We introduce AIDG (Adversarial Inform

BatteryMFormer: Multi-level Learning for Battery Degradation Trajectory Forecasting

arXiv:2605.27044v1 Announce Type: new Abstract: Early battery degradation trajectory forecasting (BDTF), which predicts the full-life state-of-health trajectory from early operational data, is critica

Bounded Path Context: A Controlled Study of Visible Path History in LLM-Based Knowledge Graph Question Answering

arXiv:2605.26645v1 Announce Type: new Abstract: LLM-based knowledge-graph question answering (KGQA) delegates graph traversal to language models, turning each question into a sequence of local relatio

CART Random Forests as Sequential Allocation over Random Opportunity Sets: A Stochastic-Control Theory of Ensemble Risk

arXiv:2605.26675v1 Announce Type: cross Abstract: CART random forests are among the most widely used modern predictive methods, with well-documented empirical success. Yet, at the mechanistic level, t

Collaborative Navigation and Exploration with eta-Sparse Gaussian Processes

arXiv:2605.26304v1 Announce Type: new Abstract: Collaborative navigation of heterogeneous robots in unknown environments poses significant challenges due to sensing, communication, and computational l

local-aiarxiv-cs-ro