Search: “local-ai”

TouchAnything: Diffusion-Guided 3D Reconstruction from Sparse Robot Touches

arXiv:2604.08945v1 Announce Type: new Abstract: Accurate object geometry estimation is essential for many downstream tasks, including robotic manipulation and physical interaction. Although vision is

13 Apr 2026

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Adversarial Robustness of Time-Series Classification for Crystal Collimator Alignment

DGX agent

arXiv:2604.06289v1 Announce Type: cross Abstract: In this paper, we analyze and improve the adversarial robustness of a convolutional neural network (CNN) that assists crystal-collimator alignment at

local-aiarxiv-cs-lg

10 Apr 2026

Auditing Black-Box LLM APIs with a Rank-Based Uniformity Test

arXiv:2506.06975v5 Announce Type: replace-cross Abstract: As API access becomes a primary interface to large language models (LLMs), users often interact with black-box systems that offer little trans

Bridging Time and Space: Decoupled Spatio-Temporal Alignment for Video Grounding

arXiv:2604.08014v1 Announce Type: new Abstract: Spatio-Temporal Video Grounding requires jointly localizing target objects across both temporal and spatial dimensions based on natural language queries

CBM-Dual: A 65-nm Fully Connected Chaotic Boltzmann Machine Processor for Dual Function Simulated Annealing and Reservoir Computing

arXiv:2604.06808v1 Announce Type: cross Abstract: This paper presents CBM-Dual, the first silicon-proven digital chaotic dynamics processor (CDP) supporting both simulated annealing (SA) and reservoir

Chatbot-Based Assessment of Code Understanding in Automated Programming Assessment Systems

arXiv:2604.07304v1 Announce Type: cross Abstract: Large Language Models (LLMs) challenge conventional automated programming assessment because students can now produce functionally correct code withou

CHiQPM: Calibrated Hierarchical Interpretable Image Classification

arXiv:2511.20779v2 Announce Type: replace Abstract: Globally interpretable models are a promising approach for trustworthy AI in safety-critical domains. Alongside global explanations, detailed local

Clinical Cognition Alignment for Gastrointestinal Diagnosis with Multimodal LLMs

arXiv:2603.20698v2 Announce Type: replace-cross Abstract: Multimodal Large Language Models (MLLMs) have demonstrated remarkable potential in medical image analysis. However, their application in gastr

Concentrated siting of AI data centers drives regional power-system stress under rising global compute demand

arXiv:2604.06198v1 Announce Type: cross Abstract: The rapid rise of generative artificial intelligence (AI) is driving unprecedented growth in global computational demand, placing increasing pressure

ConfusionPrompt: Practical Private Inference for Online Large Language Models

arXiv:2401.00870v5 Announce Type: replace-cross Abstract: State-of-the-art large language models (LLMs) are typically deployed as online services, requiring users to transmit detailed prompts to cloud

Data Selection for Multi-turn Dialogue Instruction Tuning

arXiv:2604.07892v1 Announce Type: new Abstract: Instruction-tuned language models increasingly rely on large multi-turn dialogue corpora, but these datasets are often noisy and structurally inconsiste

Differentially Private Best-Arm Identification

arXiv:2406.06408v2 Announce Type: replace-cross Abstract: Best Arm Identification (BAI) problems are progressively used for data-sensitive applications, such as designing adaptive clinical trials, tun

EmoMAS: Emotion-Aware Multi-Agent System for High-Stakes Edge-Deployable Negotiation with Bayesian Orchestration

arXiv:2604.07003v1 Announce Type: new Abstract: Large language models (LLMs) has been widely used for automated negotiation, but their high computational cost and privacy risks limit deployment in pri

Explaining Neural Networks in Preference Learning: a Post-hoc Inductive Logic Programming Approach

arXiv:2604.06838v1 Announce Type: new Abstract: In this paper, we propose using Learning from Answer Sets to approximate black-box models, such as Neural Networks (NN), in the specific case of learnin

Fast reconstruction-based ROI triggering via anomaly detection in the CYGNO optical TPC

arXiv:2512.24290v2 Announce Type: replace-cross Abstract: Optical-readout Time Projection Chambers (TPCs) produce megapixel-scale images whose fine-grained topological information is essential for rar

FedDAP: Domain-Aware Prototype Learning for Federated Learning under Domain Shift

arXiv:2604.06795v1 Announce Type: cross Abstract: Federated Learning (FL) enables decentralized model training across multiple clients without exposing private data, making it ideal for privacy-sensit

FedDetox: Robust Federated SLM Alignment via On-Device Data Sanitization

arXiv:2604.06833v1 Announce Type: cross Abstract: As high quality public data becomes scarce, Federated Learning (FL) provides a vital pathway to leverage valuable private user data while preserving p

From Synthetic Data to Real Restorations: Diffusion Model for Patient-specific Dental Crown Completion

arXiv:2603.26588v2 Announce Type: replace-cross Abstract: We present ToothCraft, a diffusion-based model for the contextual generation of tooth crowns, trained on artificially created incomplete teeth

Governance and Regulation of Artificial Intelligence in Developing Countries: A Case Study of Nigeria

arXiv:2604.06018v2 Announce Type: replace-cross Abstract: This study examines the perception of legal professionals on the governance of AI in developing countries, using Nigeria as a case study. The

Hallucination Detection and Evaluation of Large Language Model

arXiv:2512.22416v2 Announce Type: replace Abstract: Hallucinations in Large Language Models (LLMs) pose a significant challenge, generating misleading or unverifiable content that undermines trust and

HQF-Net: A Hybrid Quantum-Classical Multi-Scale Fusion Network for Remote Sensing Image Segmentation

arXiv:2604.06715v1 Announce Type: cross Abstract: Remote sensing semantic segmentation requires models that can jointly capture fine spatial details and high-level semantic context across complex scen

Learning to Query History: Nonstationary Classification via Learned Retrieval

arXiv:2604.07027v1 Announce Type: new Abstract: Nonstationarity is ubiquitous in practical classification settings, leading deployed models to perform poorly even when they generalize well to holdout

Mind the Generative Details: Direct Localized Detail Preference Optimization for Video Diffusion Models

arXiv:2601.04068v3 Announce Type: replace Abstract: Aligning text-to-video diffusion models with human preferences is crucial for generating high-quality videos. Existing Direct Preference Otimization

MoBiE: Efficient Inference of Mixture of Binary Experts under Post-Training Quantization

arXiv:2604.06798v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) based large language models (LLMs) offer strong performance but suffer from high memory and computation costs. Weight binariz

MSGL-Transformer: A Multi-Scale Global-Local Transformer for Rodent Social Behavior Recognition

arXiv:2604.07578v1 Announce Type: new Abstract: Recognition of rodent behavior is important for understanding neural and behavioral mechanisms. Traditional manual scoring is time-consuming and prone t

NativeTernary: A Self-Delimiting Binary Encoding with Unary Run-Length Hierarchy Markers for Ternary Neural Network Weights, Structured Data, and General Computing Infrastructure

arXiv:2604.03336v2 Announce Type: replace Abstract: BitNet b1.58 (Ma et al., 2024) demonstrates that large language models can operate entirely on ternary weights {-1, 0, +1}, yet no native binary wir

PixelCAM: Pixel Class Activation Mapping for Histology Image Classification and ROI Localization

arXiv:2503.24135v3 Announce Type: replace Abstract: Weakly supervised object localization (WSOL) methods allow training models to classify images and localize ROIs. WSOL only requires low-cost image-c

Q-Zoom: Query-Aware Adaptive Perception for Efficient Multimodal Large Language Models

arXiv:2604.06912v1 Announce Type: cross Abstract: MLLMs require high-resolution visual inputs for fine-grained tasks like document understanding and dense scene perception. However, current global res

Quantifying Explanation Consistency: The C-Score Metric for CAM-Based Explainability in Medical Image Classification

arXiv:2604.08502v1 Announce Type: new Abstract: Class Activation Mapping (CAM) methods are widely used to generate visual explanations for deep learning classifiers in medical imaging. However, existi

Region-Graph Optimal Transport Routing for Mixture-of-Experts Whole-Slide Image Classification

arXiv:2604.07298v1 Announce Type: cross Abstract: Multiple Instance Learning (MIL) is the dominant framework for gigapixel whole-slide image (WSI) classification in computational pathology. However, c

SAT: Selective Aggregation Transformer for Image Super-Resolution

arXiv:2604.07994v1 Announce Type: new Abstract: Transformer-based approaches have revolutionized image super-resolution by modeling long-range dependencies. However, the quadratic computational comple

Scal3R: Scalable Test-Time Training for Large-Scale 3D Reconstruction

arXiv:2604.08542v1 Announce Type: new Abstract: This paper addresses the task of large-scale 3D scene reconstruction from long video sequences. Recent feed-forward reconstruction models have shown pro

SepSeq: A Training-Free Framework for Long Numerical Sequence Processing in LLMs

arXiv:2604.07737v1 Announce Type: new Abstract: While transformer-based Large Language Models (LLMs) theoretically support massive context windows, they suffer from severe performance degradation when

ShadowNPU: System and Algorithm Co-design for NPU-Centric On-Device LLM Inference

arXiv:2508.16703v4 Announce Type: replace-cross Abstract: On-device running Large Language Models (LLMs) is nowadays a critical enabler towards preserving user privacy. We observe that the attention o

Space Filling Curves is All You Need: Communication-Avoiding Matrix Multiplication Made Simple

arXiv:2601.16294v2 Announce Type: replace-cross Abstract: General Matrix Multiplication (GEMM) is the cornerstone of HPC workloads and Deep Learning. State-of-the-art vendor libraries tune tensor layo

SubFLOT: Submodel Extraction for Efficient and Personalized Federated Learning via Optimal Transport

arXiv:2604.06631v1 Announce Type: cross Abstract: Federated Learning (FL) enables collaborative model training while preserving data privacy, but its practical deployment is hampered by system and sta

SurFITR: A Dataset for Surveillance Image Forgery Detection and Localisation

arXiv:2604.07101v1 Announce Type: cross Abstract: We present the Surveillance Forgery Image Test Range (SurFITR), a dataset for surveillance-style image forgery detection and localisation, in response

Toward Personalized Darts Training: A Data-Driven Framework Based on Skeleton-Based Biomechanical Analysis and Motion Modeling

arXiv:2604.01130v3 Announce Type: replace Abstract: As sports training becomes more data-driven, traditional dart coaching based mainly on experience and visual observation is increasingly inadequate