Search: “local-ai”

From Short Histories to Long Futures: Horizon-Aware Graph Neural Networks for Long Horizon Forecasting

arXiv:2605.29952v1 Announce Type: new Abstract: Accurate long-range prediction of geophysical systems is difficult due to strongly nonlinear dynamics, the high computational cost of full-physics simul

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Local Ai

HTAM: Hierarchical Transition-Attended Memory for Operator Optimization

DGX agent

arXiv:2605.29734v1 Announce Type: new Abstract: High-performance GPU kernels are essential for efficient LLM deployment, yet optimizing them remains expertise-intensive. Recent LLM-based code generati

local-aiarxiv-cs-cl

29 May 2026

KAN-AD: Time Series Anomaly Detection with Kolmogorov-Arnold Networks

arXiv:2411.00278v4 Announce Type: replace Abstract: Time series anomaly detection (TSAD) underpins real-time monitoring in cloud services and web systems, allowing rapid identification of anomalies to

Learning to Solve PDEs on Neural Shape Representations

arXiv:2512.21311v2 Announce Type: replace Abstract: Solving partial differential equations (PDEs) on shapes underpins many shape analysis and engineering tasks; yet, prevailing PDE solvers operate on

Locally Coherent, Globally Incoherent: Bounding Compositional Incoherence in Multi-Component LLM Agents

arXiv:2605.30335v1 Announce Type: new Abstract: Multi-component LLM agents assemble probabilistic claims from components that each see only part of a joint problem; the composition can violate basic p

MediHive: A Decentralized Agent Collective for Medical Reasoning

arXiv:2603.27150v2 Announce Type: replace Abstract: Large language models (LLMs) have revolutionized medical reasoning tasks, yet single-agent systems often falter on complex, interdisciplinary proble

Meta-Cognitive Memory Policy Optimization for Long-Horizon LLM Agents

arXiv:2605.30159v1 Announce Type: new Abstract: Memory-augmented LLM agents tackle complex long-horizon tasks by recursively summarizing interaction trajectories into compact memory. However, existing

MoLe-{Lambda}: Learning the Coupled-Cluster Response State for Energies, Gradients, and Properties

arXiv:2605.29622v1 Announce Type: new Abstract: Coupled-cluster (CC) theory is often considered the gold standard of quantum chemistry, but its high computational cost limits routine access to accurat

Multi-Scale Local Speculative Decoding for Image Generation

arXiv:2601.05149v2 Announce Type: replace Abstract: Autoregressive (AR) models have achieved remarkable success in image synthesis, yet their sequential nature imposes significant latency constraints.

Prompt-Level Reward Specifications for Open-Ended Post-Training

arXiv:2605.29275v1 Announce Type: new Abstract: Open-ended post-training benefits from rewards that make prompt-specific success conditions explicit, rather than relying only on post-hoc scalar scores

PROTOCOL: Late Interaction Retrieval for Protein Homolog Search

arXiv:2605.29158v1 Announce Type: new Abstract: Protein homology search underlies function annotation, structure prediction, and evolutionary analysis, but remains challenging in the 'twilight zone,'

Q-ANCHOR: Federated Quantum Learning with ZNE-guided Correction

arXiv:2605.30075v1 Announce Type: new Abstract: Quantum Federated Learning (QFL) offers a promising framework to train quantum models across distributed clients while keeping data strictly local. Due

RadioFormer3D: Weakly Supervised 3D Radio Map Estimation in Low-Altitude Airspace via Generative Modeling

arXiv:2605.29538v1 Announce Type: new Abstract: With the emergence of wireless applications in three-dimensional environments, such as the low-altitude airspace and 3D heterogeneous networks, radio ma

Reasoning with Sampling: Cutting at Decision Points

arXiv:2605.30327v1 Announce Type: cross Abstract: Frontier reasoning models are produced by posttraining base language models with reinforcement learning. Recent work has challenged this by showing th

S3Mem: Structured Spatiotemporal Scene-Event Memory for Long-Horizon Interactive Question Answering

arXiv:2605.28831v1 Announce Type: cross Abstract: Long-horizon interactive agents often accumulate large trajectory histories yet still fail to answer questions about earlier events reliably. We argue

Steering at the Source: Style Modulation Heads for Robust Persona Control

arXiv:2603.13249v2 Announce Type: replace-cross Abstract: Activation steering offers a computationally efficient mechanism for controlling Large Language Models (LLMs) without fine-tuning. While effec

Towards Localized and Disentangled Knowledge Editing for Multimodal Large Language Models

arXiv:2605.29826v1 Announce Type: cross Abstract: Existing methods in Multimodal Knowledge Editing (MKE) have advanced the ability to correct outdated or inaccurate knowledge in Multimodal Large Langu

Towards Understanding the Shape of Representations in Protein Language Models

arXiv:2509.24895v2 Announce Type: replace Abstract: While protein language models (PLMs) are one of the most promising avenues of research for future de novo protein design, the way in which they tran

UI-KOBE: Knowledge-Oriented Behavior Exploration for Lightweight Graph-Guided GUI Agents

arXiv:2605.29534v1 Announce Type: new Abstract: Recent advances in mobile GUI agents have shown strong potential for automating mobile tasks, but most effective systems still depend on large vision-la

Unifying Temporal and Structural Credit Assignment in LLM-Based Multi-Agent Prompt Optimization

arXiv:2605.30227v1 Announce Type: cross Abstract: While Multi-Agent Systems (MAS) empower Large Language Models to tackle complex reasoning tasks through collaborative interaction, optimizing their dy

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

Unsupervised Semantic Segmentation Facilitates Model Understanding

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

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

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