Daily Arxiv

전 세계에서 발간되는 인공지능 관련 논문을 정리하는 페이지 입니다.
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From Text to Network: Constructing a Knowledge Graph of Taiwan-Based China Studies Using Generative AI

Leveraging Graph Retrieval-Augmented Generation to Support Learners' Understanding of Knowledge Concepts in MOOCs

The First MPDD Challenge: Multimodal Personality-aware Depression Detection

Pre-Act: Multi-Step Planning and Reasoning Improves Acting in LLM Agents

Demystifying AI Agents: The Final Generation of Intelligence

"There Is No Such Thing as a Dumb Question," But There Are Good Ones

Offline Reinforcement Learning for Microgrid Voltage Regulation

A Multimodal Multi-Agent Framework for Radiology Report Generation

Explainability Through Human-Centric Design for XAI in Lung Cancer Detection

General Dynamic Goal Recognition

Feature Relevancy, Necessity and Usefulness: Complexity and Algorithms

Study and improvement of search algorithms in two-players perfect information games

Towards Autonomous UAV Visual Object Search in City Space: Benchmark and Agentic Methodology

Hakim: Farsi Text Embedding Model

Fast Text-to-Audio Generation with Adversarial Post-Training

Fusing Bidirectional Chains of Thought and Reward Mechanisms A Method for Enhancing Question-Answering Capabilities of Large Language Models for Chinese Intangible Cultural Heritage

Intelligent Product 3.0: Decentralised AI Agents and Web3 Intelligence Standards

Neural Brain: A Neuroscience-inspired Framework for Embodied Agents

Decoding Futures Price Dynamics: A Regularized Sparse Autoencoder for Interpretable Multi-Horizon Forecasting and Factor Discovery

Steerable Chatbots: Personalizing LLMs with Preference-Based Activation Steering

SafeNav: Safe Path Navigation using Landmark Based Localization in a GPS-denied Environment

Don't be lazy: CompleteP enables compute-efficient deep transformers

Llama-Nemotron: Efficient Reasoning Models

Rethinking Time Encoding via Learnable Transformation Functions

CrashFixer: A crash resolution agent for the Linux kernel

Harden and Catch for Just-in-Time Assured LLM-Based Software Testing: Open Research Challenges

Multi-Agent Reinforcement Learning Simulation for Environmental Policy Synthesis

Energy Matching: Unifying Flow Matching and Energy-Based Models for Generative Modeling

Beyond Single-Turn: A Survey on Multi-Turn Interactions with Large Language Models

Evaluating Clinical Competencies of Large Language Models with a General Practice Benchmark

Reinforcement Learning Outperforms Supervised Fine-Tuning: A Case Study on Audio Question Answering

The Problem of the Priors, or Posteriors?

Simulating and Analysing Human Survey Responses with Large Language Models: A Case Study in Energy Stated Preference

Learning Autonomy: Off-Road Navigation Enhanced by Human Input

InductionBench: LLMs Fail in the Simplest Complexity Class

Activation Steering in Neural Theorem Provers

PropNet: a White-Box and Human-Like Network for Sentence Representation

Principled Data Selection for Alignment: The Hidden Risks of Difficult Examples

FAS: Fast ANN-SNN Conversion for Spiking Large Language Models

Learning Traffic Anomalies from Generative Models on Real-Time Observations

High-temperature superconductivity in Li$_2$AuH$_6$ mediated by strong electron-phonon coupling under ambient pressure

A Bio-Inspired Research Paradigm of Collision Perception Neurons Enabling Neuro-Robotic Integration: The LGMD Case

ThreatModeling-LLM: Automating Threat Modeling using Large Language Models for Banking System

Is Linear Feedback on Smoothed Dynamics Sufficient for Stabilizing Contact-Rich Plans?

What Features in Prompts Jailbreak LLMs? Investigating the Mechanisms Behind Attacks

FAMMA: A Benchmark for Financial Domain Multilingual Multimodal Question Answering

Deep Signature: Characterization of Large-Scale Molecular Dynamics

State-of-the-Art Periorbital Distance Prediction and Disease Classification Using Periorbital Features

A Deep Learning Approach for Pixel-level Material Classification via Hyperspectral Imaging

Fragment-Masked Diffusion for Molecular Optimization

Public Constitutional AI

Cognitive Insights and Stable Coalition Matching for Fostering Multi-Agent Cooperation

DACAD: Domain Adaptation Contrastive Learning for Anomaly Detection in Multivariate Time Series

Construction and Application of Materials Knowledge Graph in Multidisciplinary Materials Science via Large Language Model

Detecting Multimedia Generated by Large AI Models: A Survey

Efficient approximation of Earth Mover's Distance Based on Nearest Neighbor Search

EiHi Net: Out-of-Distribution Generalization Paradigm

Agent RL Scaling Law: Agent RL with Spontaneous Code Execution for Mathematical Problem Solving

RefPentester: A Knowledge-Informed Self-Reflective Penetration Testing Framework Based on Large Language Models

CAT Merging: A Training-Free Approach for Resolving Conflicts in Model Merging

SafeMate: A Modular RAG-Based Agent for Context-Aware Emergency Guidance

UI-R1: Enhancing Efficient Action Prediction of GUI Agents by Reinforcement Learning

AdaWorld: Learning Adaptable World Models with Latent Actions

Reinforcement Learning-based Heuristics to Guide Domain-Independent Dynamic Programming

An Analytical Emotion Framework of Rumour Threads on Social Media

Deontic Temporal Logic for Formal Verification of AI Ethics

PSPO*: An Effective Process-supervised Policy Optimization for Reasoning Alignment

Think Smart, Act SMARL! Analyzing Probabilistic Logic Shields for Multi-Agent Reinforcement Learning

Exploiting Uncertainty for Querying Inconsistent Description Logics Knowledge Bases

Learning to Be Cautious

Customizing a Large Language Model for VHDL Design of High-Performance Microprocessors

How Hungry is AI? Benchmarking Energy, Water, and Carbon Footprint of LLM Inference

WorldView-Bench: A Benchmark for Evaluating Global Cultural Perspectives in Large Language Models

Variational Visual Question Answering

Ethics and Persuasion in Reinforcement Learning from Human Feedback: A Procedural Rhetorical Approach

BLIP3-o: A Family of Fully Open Unified Multimodal Models-Architecture, Training and Dataset

Meta-learning Slice-to-Volume Reconstruction in Fetal Brain MRI using Implicit Neural Representations

Learning Long-Context Diffusion Policies via Past-Token Prediction

WavReward: Spoken Dialogue Models With Generalist Reward Evaluators

Flash-VL 2B: Optimizing Vision-Language Model Performance for Ultra-Low Latency and High Throughput

Preserving Plasticity in Continual Learning with Adaptive Linearity Injection

Deploying Foundation Model-Enabled Air and Ground Robots in the Field: Challenges and Opportunities

A 2D Semantic-Aware Position Encoding for Vision Transformers

Quantum state-agnostic work extraction (almost) without dissipation

Evaluating GPT- and Reasoning-based Large Language Models on Physics Olympiad Problems: Surpassing Human Performance and Implications for Educational Assessment

CXMArena: Unified Dataset to benchmark performance in realistic CXM Scenarios

Endo-CLIP: Progressive Self-Supervised Pre-training on Raw Colonoscopy Records

Multilingual Machine Translation with Quantum Encoder Decoder Attention-based Convolutional Variational Circuits

Quantum-Enhanced Parameter-Efficient Learning for Typhoon Trajectory Forecasting

UMotion: Uncertainty-driven Human Motion Estimation from Inertial and Ultra-wideband Units

FedSaaS: Class-Consistency Federated Semantic Segmentation via Global Prototype Supervision and Local Adversarial Harmonization

The Voice Timbre Attribute Detection 2025 Challenge Evaluation Plan

Examining Deployment and Refinement of the VIOLA-AI Intracranial Hemorrhage Model Using an Interactive NeoMedSys Platform

TensorRL-QAS: Reinforcement learning with tensor networks for scalable quantum architecture search

GreenFactory: Ensembling Zero-Cost Proxies to Estimate Performance of Neural Networks

Insights into DeepSeek-V3: Scaling Challenges and Reflections on Hardware for AI Architectures

Evaluating the Robustness of Adversarial Defenses in Malware Detection Systems

BioVFM-21M: Benchmarking and Scaling Self-Supervised Vision Foundation Models for Biomedical Image Analysis

Neural Video Compression using 2D Gaussian Splatting

Toward Fair Federated Learning under Demographic Disparities and Data Imbalance

Examining Deployment and Refinement of the VIOLA-AI Intracranial Hemorrhage Model Using an Interactive NeoMedSys Platform

Created by

Haebom

저자

Qinghui Liu, Jon Nesvold, Hanna Raaum, Elakkyen Murugesu, Martin R{\o}vang, Bradley J Maclntosh, Atle Bj{\o}rnerud, Karoline Skogen

개요

본 논문은 의료 영상 AI 모델의 효율적인 배포 및 개선을 위한 방사선과 소프트웨어 플랫폼 NeoMedSys를 소개하고, 실제 임상 환경에서의 3개월간의 평가 결과를 제시합니다. NeoMedSys는 AI 모델 배포, 테스트, 최적화 도구와 웹 기반 의료 영상 뷰어, 주석 시스템, 병원 전체 방사선 정보 시스템을 통합합니다. 노르웨이 최대 응급실 두 곳에서 외상성 뇌손상 또는 뇌졸중이 의심되는 환자의 임상 사례를 사용하여 두개강 출혈(ICH) 검출을 위한 자체 개발 AI 모델인 VIOLA-AI의 성능 향상에 초점을 맞추었습니다. NeoMedSys를 통해 VIOLA-AI 모델의 반복적인 개선이 이루어졌으며, 민감도는 79.2%에서 90.3%로, 특이도는 80.7%에서 89.3%로 향상되었고, AUC는 0.873에서 0.949로 증가했습니다. 실시간 방사선 전문의 피드백을 통한 모델 개선의 가치를 강조합니다.

시사점, 한계점

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시사점:

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NeoMedSys 플랫폼은 실제 임상 환경에서 AI 모델의 효율적인 배포 및 지속적인 성능 향상을 가능하게 합니다.

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실시간 피드백 기반의 반복적인 모델 개선을 통해 AI 모델의 정확도를 상당히 향상시킬 수 있음을 보여줍니다.

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VIOLA-AI 모델의 성능 향상을 통해 두개강 출혈 검출의 정확성을 높일 수 있는 가능성을 제시합니다.

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한계점:

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연구 대상이 노르웨이 최대 응급실 두 곳으로 제한되어 일반화 가능성에 대한 추가 연구가 필요합니다.

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3개월이라는 비교적 짧은 기간의 평가 기간으로 장기적인 효과 및 안정성에 대한 추가적인 연구가 필요합니다.

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특정 AI 모델(VIOLA-AI)과 특정 질환(ICH)에 대한 연구 결과이므로 다른 AI 모델 및 질환에 대한 일반화에는 주의가 필요합니다.

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