Search: “local-ai”

E^2DT: Efficient and Effective Decision Transformer with Experience-Aware Sampling for Robotic Manipulation

arXiv:2605.00159v1 Announce Type: new Abstract: In reinforcement learning (RL) for robotic manipulation, the Decision Transformer (DT) has emerged as an effective framework for addressing long-horizon

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EGREFINE: An Execution-Grounded Optimization Framework for Text-to-SQL Schema Refinement

DGX agent

arXiv:2605.00628v1 Announce Type: cross Abstract: Text-to-SQL enables non-expert users to query databases in natural language, yet real-world schemas often suffer from ambiguous, abbreviated, or incon

local-aiarxiv-cs-cl

4 May 2026

Federated Distillation for Whole Slide Image via Gaussian-Mixture Feature Alignment and Curriculum Integration

arXiv:2605.00578v1 Announce Type: new Abstract: Federated learning (FL) offers a promising framework for collaborative digital pathology by enabling model training across institutions. However, real-w

FedKPer: Tackling Generalization and Personalization in Medical Federated Learning via Knowledge Personalization

arXiv:2605.00698v1 Announce Type: cross Abstract: Federated learning (FL) holds great potential for medical applications. However, statistical heterogeneity across healthcare institutions poses a majo

From Birdsong to Rumbles: Classifying Elephant Calls with Out-of-Species Embeddings

arXiv:2605.00225v1 Announce Type: cross Abstract: We show that pretrained acoustic embeddings classify elephant vocalisations at a level approaching that of end-to-end supervised neural networks, with

Gated Differential Linear Attention: A Linear-Time Decoder for High-Fidelity Medical Segmentation

arXiv:2603.02727v4 Announce Type: replace Abstract: Medical image segmentation requires models that preserve fine anatomical boundaries while remaining practical for clinical deployment. Transformers

Hyperspherical Forward-Forward with Prototypical Representations

arXiv:2605.00082v1 Announce Type: new Abstract: The Forward-Forward (FF) algorithm presents a compelling, bio-inspired alternative to backpropagation. However, while efficient in training, it has a co

Learning the Helmholtz equation operator with DeepONet for non-parametric 2D geometries

arXiv:2605.00760v1 Announce Type: new Abstract: This paper deals with solving the 2D Helmholtz equation on non-parametric domains, leveraging a physics-informed neural operator network based on the De

Lucid-XR: An Extended-Reality Data Engine for Robotic Manipulation

arXiv:2605.00244v1 Announce Type: cross Abstract: We introduce Lucid-XR, a generative data engine for creating diverse and realistic-looking multi-modal data to train real-world robotic systems. At th

MSACT: Multistage Spatial Alignment for Stable Low-Latency Fine Manipulation

arXiv:2605.00475v1 Announce Type: cross Abstract: Real-world fine manipulation, particularly in bimanual manipulation, typically requires low-latency control and stable visual localization, while coll

NLPOpt-Net: A Learning Method for Nonlinear Optimization with Feasibility Guarantees

arXiv:2605.00260v1 Announce Type: new Abstract: Nonlinear Parametric Optimization Network (NLPOpt-Net) is an unsupervised learning architecture to solve constrained nonlinear programs (NLP). Given the

NonZero: Interaction-Guided Exploration for Multi-Agent Monte Carlo Tree Search

arXiv:2605.00751v1 Announce Type: new Abstract: Monte Carlo Tree Search (MCTS) scales poorly in cooperative multi-agent domains because expansion must consider an exponentially large set of joint acti

Polaris: Coupled Orbital Polar Embeddings for Hierarchical Concept Learning

arXiv:2605.00265v1 Announce Type: new Abstract: Real-world knowledge is often organized as hierarchies such as product taxonomies, medical ontologies, and label trees, yet learning hierarchical repres

Prefer-DAS: Learning from Local Preferences and Sparse Prompts for Domain Adaptive Segmentation of Electron Microscopy

arXiv:2602.19423v3 Announce Type: replace Abstract: Domain adaptive segmentation (DAS) is a promising paradigm for delineating intracellular structures from various large-scale electron microscopy (EM

RadLite: Multi-Task LoRA Fine-Tuning of Small Language Models for CPU-Deployable Radiology AI

arXiv:2605.00421v1 Announce Type: new Abstract: Large language models (LLMs) show promise in radiology but their deployment is limited by computational requirements that preclude use in resource-const

local-aiarxiv-cs-cl

Tempus: A Temporally Scalable Resource-Invariant GEMM Streaming Framework for Versal AI Edge

arXiv:2605.00536v1 Announce Type: cross Abstract: Scaling laws for Large Language Models (LLMs) establish that model quality improves with computational scale, yet edge deployment imposes strict const

Thinking in Text and Images: Interleaved Vision--Language Reasoning Traces for Long-Horizon Robot Manipulation

arXiv:2605.00438v1 Announce Type: cross Abstract: Long-horizon robotic manipulation requires plans that are both logically coherent and geometrically grounded. Existing Vision-Language-Action policies

TimesNet-Gen: Deep Learning-based Site Specific Strong Motion Generation

arXiv:2512.04694v3 Announce Type: replace Abstract: Effective earthquake risk reduction relies on accurate site-specific evaluations, which require models capable of representing the influence of loca

TokenWeave: Efficient Compute-Communication Overlap for Distributed LLM Inference

arXiv:2505.11329v5 Announce Type: replace-cross Abstract: Distributed inference of large language models (LLMs) using tensor parallelism can introduce communication overheads of 20% even over GPUs con

VkSplat: High-Performance 3DGS Training in Vulkan Compute

arXiv:2605.00219v1 Announce Type: new Abstract: We present VkSplat, a high-performance, cross-vendor 3D Gaussian Splatting (3DGS) training pipeline implemented fully in Vulkan compute, addressing perf

A Collective Variational Principle Unifying Bayesian Inference, Game Theory, and Thermodynamics

arXiv:2604.27942v1 Announce Type: new Abstract: Collective intelligence emerges across biological, physical, and artificial systems without central coordination, yet a unifying principle governing suc

Attractor FCM

arXiv:2604.27947v1 Announce Type: cross Abstract: In this paper an attractor FCM is created, tested, and analyzed. This FCM is neither a hebbian based nor agentic, nor a hybrid; it rather is a gradien

Can Tabular Foundation Models Guide Exploration in Robot Policy Learning?

arXiv:2604.27667v1 Announce Type: cross Abstract: Policy optimization in high-dimensional continuous control for robotics remains a challenging problem. Predominant methods are inherently local and of

CasLayout: Cascaded 3D Layout Diffusion for Indoor Scene Synthesis with Implicit Relation Modeling

arXiv:2604.27361v1 Announce Type: new Abstract: Synthesizing realistic 3D indoor scenes remains challenging due to data scarcity and the difficulty of simultaneously enforcing global architectural con

Detecting is Easy, Adapting is Hard: Local Expert Growth for Visual Model-Based Reinforcement Learning under Distribution Shift

arXiv:2604.27411v1 Announce Type: new Abstract: Visual model-based reinforcement learning (MBRL) agents can perform well on the training distribution, but often break down once the test environment sh

Echo-{alpha}: Large Agentic Multimodal Reasoning Model for Ultrasound Interpretation

arXiv:2604.28011v1 Announce Type: new Abstract: Ultrasound interpretation requires both precise lesion localization and holistic clinical reasoning, yet existing methods typically excel at only one of

Effective Prompt Pool Learning for Continual Category Discovery

arXiv:2407.19001v3 Announce Type: replace Abstract: This paper studies effective prompt pool learning for Continual Category Discovery (CCD), a challenging open-world setting where a model must discov

ELiC: Efficient LiDAR Geometry Compression via Cross-Bit-depth Feature Propagation and Bag-of-Encoders

arXiv:2511.14070v3 Announce Type: replace-cross Abstract: Hierarchical LiDAR geometry compression encodes voxel occupancies from low to high bit-depths, yet prior methods treat each depth independentl

Enhancing Linux Privilege Escalation Attack Capabilities of Local LLM Agents

arXiv:2604.27143v1 Announce Type: cross Abstract: Recent research has demonstrated the potential of Large Language Models (LLMs) for autonomous penetration testing, particularly when using cloud-based

Global Sampling-Based Trajectory Optimization for Contact-Rich Manipulation via KernelSOS

arXiv:2604.27175v1 Announce Type: new Abstract: Contact-rich manipulation is challenging due to its high dimensionality, the requirement for long time horizons, and the presence of hybrid contact dyna

Gradient-Based Optimization on Godel Logic as Discrete Local Search

arXiv:2503.01817v2 Announce Type: replace Abstract: A fundamental challenge in neurosymbolic systems is applying continuous gradient-based optimization to discrete logical domains. While fuzzy relaxat

Hinge Regression Tree: A Newton Method for Oblique Regression Tree Splitting

arXiv:2602.05371v3 Announce Type: replace Abstract: Oblique decision trees combine the transparency of trees with the power of multivariate decision boundaries, but learning high-quality oblique split

MoCapAnything V2: End-to-End Motion Capture for Arbitrary Skeletons

arXiv:2604.28130v1 Announce Type: new Abstract: Recent methods for arbitrary-skeleton motion capture from monocular video follow a factorized pipeline, where a Video-to-Pose network predicts joint pos

Multi-Level Narrative Evaluation Outperforms Lexical Features for Mental Health

arXiv:2604.27846v1 Announce Type: new Abstract: How people narrate their experiences offers a window into how the mind organizes them. Computational approaches to therapeutic writing have evolved from

local-aiarxiv-cs-cl

OmniDrive-R1: Reinforcement-driven Interleaved Multi-modal Chain-of-Thought for Trustworthy Vision-Language Autonomous Driving

arXiv:2512.14044v3 Announce Type: replace-cross Abstract: The deployment of Vision-Language Models (VLMs) in safety-critical domains like autonomous driving (AD) is critically hindered by reliability

Policy-Governed LLM Routing with Intent Matching for Instrument Laboratories

arXiv:2604.26955v1 Announce Type: cross Abstract: AI tutoring systems in engineering labs face a tension between providing sufficient assistance and preserving learning opportunities. Existing systems

Privacy-Preserving Federated Learning via Differential Privacy and Homomorphic Encryption for Cardiovascular Disease Risk Modeling

arXiv:2604.27598v1 Announce Type: new Abstract: Protecting sensitive health data while enabling collaborative analysis is a central challenge in healthcare. Traditional machine learning (ML) requires

RAY-TOLD: Ray-Based Latent Dynamics for Dense Dynamic Obstacle Avoidance with TDMPC

arXiv:2604.27450v1 Announce Type: cross Abstract: Dense, dynamic crowds pose a persistent challenge for autonomous mobile robots. Purely reactive planning methods, such as Model Predictive Path Integr

Secret Stealing Attacks on Local LLM Fine-Tuning through Supply-Chain Model Code Backdoors

arXiv:2604.27426v1 Announce Type: cross Abstract: Local fine-tuning datasets routinely contain sensitive secrets such as API keys, personal identifiers, and financial records. Although ''local offline

TeD-Loc: Text Distillation for Weakly Supervised Object Localization

arXiv:2501.12632v2 Announce Type: replace Abstract: Weakly supervised object localization (WSOL) models are trained using only image-level class labels. They can predict both the object class and spat

Training-Free Tunnel Defect Inspection and Engineering Interpretation via Visual Recalibration and Entity Reconstruction

arXiv:2604.27928v1 Announce Type: cross Abstract: Tunnel inspection requires outputs that can support defect localization, measurement, severity grading, and engineering documentation. Existing traini

VerteNet -- A Multi-Context Hybrid CNN Transformer for Accurate Vertebral Landmark Localization in Lateral Spine DXA Images

arXiv:2502.02097v3 Announce Type: replace Abstract: This aims to develop and validate a deep learning model that can accurately locate vertebral landmarks in lateral spine Dual energy X-ray Absorptiom

When 2D Tasks Meet 1D Serialization: On Serialization Friction in Structured Tasks

arXiv:2604.27272v1 Announce Type: cross Abstract: Large language models (LLMs) conventionally process structured inputs as 1D token sequences. While natural for prose, such linearization may introduce

Action Hints: Semantic Typicality and Context Uniqueness for Generalizable Skeleton-based Video Anomaly Detection

arXiv:2509.11058v2 Announce Type: replace Abstract: Zero-Shot Video Anomaly Detection (ZS-VAD) requires temporally localizing anomalies without target domain training data, which is a crucial task due

Adaptive Layerwise Perturbation: Unifying Off-Policy Corrections for LLM RL

arXiv:2603.19470v2 Announce Type: replace-cross Abstract: Off-policy problems such as policy staleness and training--inference mismatch have become a major bottleneck for training stability and furthe

CoFL: Continuous Flow Fields for Language-Conditioned Navigation

arXiv:2603.02854v2 Announce Type: replace-cross Abstract: Existing language-conditioned navigation systems typically rely on modular pipelines or trajectory generators, but the latter use each scene--

Distill-Belief: Closed-Loop Inverse Source Localization and Characterization in Physical Fields

arXiv:2604.26095v1 Announce Type: new Abstract: {Closed-loop inverse source localization and characterization (ISLC) requires a mobile agent to select measurements that localize sources and infer late

Distributional Stability of Tangent-Linearized Gaussian Inference on Smooth Manifolds

arXiv:2602.19179v2 Announce Type: replace Abstract: Gaussian inference on smooth manifolds is central to robotics, but exact marginalization and conditioning are generally non-Gaussian and geometry-de