Daily Arxiv

전 세계에서 발간되는 인공지능 관련 논문을 정리하는 페이지 입니다.
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논문에 대한 저작권은 저자 및 해당 기관에 있으며, 공유 시 출처만 명기하면 됩니다.

Relational Causal Discovery with Latent Confounders

GPT, But Backwards: Exactly Inverting Language Model Outputs

Blending Supervised and Reinforcement Fine-Tuning with Prefix Sampling

Deep Recommender Models Inference: Automatic Asymmetric Data Flow Optimization

Comparing Optimization Algorithms Through the Lens of Search Behavior Analysis

AsyncFlow: An Asynchronous Streaming RL Framework for Efficient LLM Post-Training

Autoregressive Image Generation with Linear Complexity: A Spatial-Aware Decay Perspective

GradMetaNet: An Equivariant Architecture for Learning on Gradients

Customized Exploration of Landscape Features Driving Multi-Objective Combinatorial Optimization Performance

Depth Anything at Any Condition

Tile and Slide : A New Framework for Scaling NeRF from Local to Global 3D Earth Observation

Prompt Guidance and Human Proximal Perception for HOT Prediction with Regional Joint Loss

Enhanced Influence-aware Group Recommendation for Online Media Propagation

Survivability of Backdoor Attacks on Unconstrained Face Recognition Systems

Data Agent: A Holistic Architecture for Orchestrating Data+AI Ecosystems

Autonomous AI Surveillance: Multimodal Deep Learning for Cognitive and Behavioral Monitoring

Exploring Classical Piano Performance Generation with Expressive Music Variational AutoEncoder

Real-Time Emergency Vehicle Siren Detection with Efficient CNNs on Embedded Hardware

Self-Guided Process Reward Optimization with Masked Step Advantage for Process Reinforcement Learning

Crafting Hanzi as Narrative Bridges: An AI Co-Creation Workshop for Elderly Migrants

AI and Remote Sensing for Resilient and Sustainable Built Environments: A Review of Current Methods, Open Data and Future Directions

Chargax: A JAX Accelerated EV Charging Simulator

Following the Clues: Experiments on Person Re-ID using Cross-Modal Intelligence

Integrating Traditional and Deep Learning Methods to Detect Tree Crowns in Satellite Images

Crop Pest Classification Using Deep Learning Techniques: A Review

BioMARS: A Multi-Agent Robotic System for Autonomous Biological Experiments

Epistemic Scarcity: The Economics of Unresolvable Unknowns

Evaluating the Effectiveness of Direct Preference Optimization for Personalizing German Automatic Text Simplifications for Persons with Intellectual Disabilities

Zero-Incentive Dynamics: a look at reward sparsity through the lens of unrewarded subgoals

NOCTIS: Novel Object Cyclic Threshold based Instance Segmentation

Quantum-Assisted Automatic Path-Planning for Robotic Quality Inspection in Industry 4.0

Tensor Program Optimization for the RISC-V Vector Extension Using Probabilistic Programs

EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices

Hardware-software co-exploration with racetrack memory based in-memory computing for CNN inference in embedded systems

DocShaDiffusion: Diffusion Model in Latent Space for Document Image Shadow Removal

Penalizing Transparency? How AI Disclosure and Author Demographics Shape Human and AI Judgments About Writing

Evaluating LLM Agent Collusion in Double Auctions

Age Sensitive Hippocampal Functional Connectivity: New Insights from 3D CNNs and Saliency Mapping

Medical-Knowledge Driven Multiple Instance Learning for Classifying Severe Abdominal Anomalies on Prenatal Ultrasound

Distributional Soft Actor-Critic with Diffusion Policy

RALLY: Role-Adaptive LLM-Driven Yoked Navigation for Agentic UAV Swarms

Skywork-Reward-V2: Scaling Preference Data Curation via Human-AI Synergy

User-guided Generative Source Separation

LEDOM: An Open and Fundamental Reverse Language Model

Reasoner for Real-World Event Detection: Scaling Reinforcement Learning via Adaptive Perplexity-Aware Sampling Strategy

ICLShield: Exploring and Mitigating In-Context Learning Backdoor Attacks

Neural Hamiltonian Operator

VLAD: A VLM-Augmented Autonomous Driving Framework with Hierarchical Planning and Interpretable Decision Process

Rethinking All Evidence: Enhancing Trustworthy Retrieval-Augmented Generation via Conflict-Driven Summarization

AI Meets Maritime Training: Precision Analytics for Enhanced Safety and Performance

PULSE: Practical Evaluation Scenarios for Large Multimodal Model Unlearning

LLM-based Realistic Safety-Critical Driving Video Generation

GAIus: Combining Genai with Legal Clauses Retrieval for Knowledge-based Assistant

Beyond First-Order: Training LLMs with Stochastic Conjugate Subgradients and AdamW

Capacity Planning and Scheduling for Jobs with Uncertainty in Resource Usage and Duration

Search-Based Robot Motion Planning With Distance-Based Adaptive Motion Primitives

Are Large Brainwave Foundation Models Capable Yet? Insights from Fine-tuning

Geometry-aware 4D Video Generation for Robot Manipulation

AI-guided digital intervention with physiological monitoring reduces intrusive memories after experimental trauma

Empirical Analysis Of Heuristic and Approximation Algorithms for the The Mutual-Visibility Problem

Evaluation of a Foundational Model and Stochastic Models for Forecasting Sporadic or Spiky Production Outages of High-Performance Machine Learning Services

FAIR-MATCH: A Multi-Objective Framework for Bias Mitigation in Reciprocal Dating Recommendations

Quantifying Student Success with Generative AI: A Monte Carlo Simulation Informed by Systematic Review

Epitome: Pioneering an Experimental Platform for AI-Social Science Integration

Automated Vehicles Should be Connected with Natural Language

A Data Science Approach to Calcutta High Court Judgments: An Efficient LLM and RAG-powered Framework for Summarization and Similar Cases Retrieval

Prompt Mechanisms in Medical Imaging: A Comprehensive Survey

XxaCT-NN: Structure Agnostic Multimodal Learning for Materials Science

Conversational LLMs Simplify Secure Clinical Data Access, Understanding, and Analysis

Long-Sequence Memory with Temporal Kernels and Dense Hopfield Functionals

Can AI be Consentful?

Text Detoxification: Data Efficiency, Semantic Preservation and Model Generalization

Sensing Cardiac Health Across Scenarios and Devices: A Multi-Modal Foundation Model Pretrained on Heterogeneous Data from 1.7 Million Individuals

Data Classification with Dynamically Growing and Shrinking Neural Networks

Can Argus Judge Them All? Comparing VLMs Across Domains

Fast AI Model Splitting over Edge Networks

Fast Clifford Neural Layers

On-Policy Optimization of ANFIS Policies Using Proximal Policy Optimization

Learning to Segment for Vehicle Routing Problems

Systemic Constraints of Undecidability

Research on Low-Latency Inference and Training Efficiency Optimization for Graph Neural Network and Large Language Model-Based Recommendation Systems

Data-driven Insights for Informed Decision-Making: Applying LSTM Networks for Robust Electricity Forecasting in Libya

An Uncertainty-Aware Dynamic Decision Framework for Progressive Multi-Omics Integration in Classification Tasks

PathCoT: Chain-of-Thought Prompting for Zero-shot Pathology Visual Reasoning

HPC-AI Coupling Methodology for Scientific Applications

Hello Afrika: Speech Commands in Kinyarwanda

A Systematic Review of Security Vulnerabilities in Smart Home Devices and Mitigation Techniques

Refining Gelfond Rationality Principle Towards More Comprehensive Foundational Principles for Answer Set Semantics

Joint Matching and Pricing for Crowd-shipping with In-store Customers

Agent Ideate: A Framework for Product Idea Generation from Patents Using Agentic AI

T3DM: Test-Time Training-Guided Distribution Shift Modelling for Temporal Knowledge Graph Reasoning

Agent-as-Tool: A Study on the Hierarchical Decision Making with Reinforcement Learning

Using multi-agent architecture to mitigate the risk of LLM hallucinations

Pensieve Grader: An AI-Powered, Ready-to-Use Platform for Effortless Handwritten STEM Grading

A Fuzzy Approach to the Specification, Verification and Validation of Risk-Based Ethical Decision Making Models

AI Agents and Agentic AI-Navigating a Plethora of Concepts for Future Manufacturing

Beyond Black-Box AI: Interpretable Hybrid Systems for Dementia Care

Rethinking the Illusion of Thinking

Autonomy by Design: Preserving Human Autonomy in AI Decision-Support

Adapt Your Body: Mitigating Proprioception Shifts in Imitation Learning

OM4OV: Leveraging Ontology Matching for Ontology Versioning

Created by

Haebom

저자

Zhangcheng Qiang, Kerry Taylor, Weiqing Wang

개요

본 논문은 Semantic Web의 동적 특성으로 인해, 특히 널리 사용되는 온톨로지의 경우 시간에 따라 변하는 정보를 포착하기 위한 버전 관리가 필요하다는 점을 지적합니다. 기존의 온톨로지 버전 관리(OV) 접근 방식이 온톨로지의 크기 증가와 수작업으로 인한 오류 누적으로 인해 한계를 드러내는 문제를 해결하기 위해, 기존의 온톨로지 매칭(OM) 기술과 시스템을 활용한 새로운 OV 접근 방식을 제안합니다. OM 관점에서 OV 작업을 위한 새로운 작업 공식화 및 측정 방법을 제시하고, OM의 이전 정렬을 기반으로 전체 OV 성능을 향상시키는 교차 참조(CR) 메커니즘이라는 파이프라인 최적화 방법을 제안합니다. Ontology Alignment Evaluation Initiative (OAEI) 데이터셋을 기반으로 한 OV 테스트 환경에서 OM4OV 파이프라인과 교차 참조 메커니즘을 실험적으로 검증하고, OV 작업에 사용되는 OM에 대한 통찰력, 특히 OV 시스템에서 감지된 일부 명백한 잘못된 매핑이 실제로 거짓이 아닌 경우에 대한 논의를 포함합니다.

시사점, 한계점

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시사점:

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기존 온톨로지 버전 관리의 한계점을 극복할 수 있는 새로운 접근 방식 제시

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온톨로지 매칭 기술을 온톨로지 버전 관리에 효과적으로 활용하는 방법 제시

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교차 참조 메커니즘을 통한 파이프라인 최적화로 성능 향상

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OV 작업에 대한 OM의 새로운 관점 제시 및 잘못된 매핑에 대한 재해석

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한계점:

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제안된 방법의 실제 적용 가능성 및 확장성에 대한 추가 연구 필요

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OAEI 데이터셋을 기반으로 한 실험 결과의 일반화 가능성에 대한 검토 필요

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다양한 유형의 온톨로지에 대한 적용성 및 성능 평가 필요

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