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.

Aggregating Concepts of Accuracy and Fairness in Prediction Algorithms

Self-cross Feature based Spiking Neural Networks for Efficient Few-shot Learning

Graph neural networks and MSO

Generative Pre-trained Autoregressive Diffusion Transformer

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models

Towards user-centered interactive medical image segmentation in VR with an assistive AI agent

Towards Scalable IoT Deployment for Visual Anomaly Detection via Efficient Compression

X-Sim: Cross-Embodiment Learning via Real-to-Sim-to-Real

UniVLA: Learning to Act Anywhere with Task-centric Latent Actions

Assessing Tenstorrent's RISC-V MatMul Acceleration Capabilities

Examining the Source of Defects from a Mechanical Perspective for 3D Anomaly Detection

Understanding In-context Learning of Addition via Activation Subspaces

Risk-sensitive Reinforcement Learning Based on Convex Scoring Functions

Intelligently Augmented Contrastive Tensor Factorization: Empowering Multi-dimensional Time Series Classification in Low-Data Environments

Modeling Human Behavior in a Strategic Network Game with Complex Group Dynamics

GPU Performance Portability needs Autotuning

RM-R1: Reward Modeling as Reasoning

Fast and Robust: Task Sampling with Posterior and Diversity Synergies for Adaptive Decision-Makers in Randomized Environments

Data-Driven Calibration of Prediction Sets in Large Vision-Language Models Based on Inductive Conformal Prediction

WildFireCan-MMD: A Multimodal Dataset for Classification of User-Generated Content During Wildfires in Canada

CLASH: Evaluating Language Models on Judging High-Stakes Dilemmas from Multiple Perspectives

Optimizing Power Grid Topologies with Reinforcement Learning: A Survey of Methods and Challenges

Flexible Graph Similarity Computation With A Proactive Optimization Strategy

CryoSAMU: Enhancing 3D Cryo-EM Density Maps of Protein Structures at Intermediate Resolution with Structure-Aware Multimodal U-Nets

PromptMobile: Efficient Promptus for Low Bandwidth Mobile Video Streaming

Implicit Bias-Like Patterns in Reasoning Models

EMMOE: A Comprehensive Benchmark for Embodied Mobile Manipulation in Open Environments

Temporal Triplane Transformers as Occupancy World Models

The Lazy Student's Dream: ChatGPT Passing an Engineering Course on Its Own

Atlas: A Framework for ML Lifecycle Provenance & Transparency

Centrally Coordinated Multi-Agent Reinforcement Learning for Power Grid Topology Control

Illegal Waste Detection in Remote Sensing Images: A Case Study

ARR: Question Answering with Large Language Models via Analyzing, Retrieving, and Reasoning

ImprovNet -- Generating Controllable Musical Improvisations with Iterative Corruption Refinement

Lightspeed Geometric Dataset Distance via Sliced Optimal Transport

Benchmarking Generative AI for Scoring Medical Student Interviews in Objective Structured Clinical Examinations (OSCEs)

Representation Convergence: Mutual Distillation is Secretly a Form of Regularization

Goal-Conditioned Supervised Learning for Multi-Objective Recommendation

Not All Adapters Matter: Selective Adapter Freezing for Memory-Efficient Fine-Tuning of Language Models

Simple and Provable Scaling Laws for the Test-Time Compute of Large Language Models

KBAlign: Efficient Self Adaptation on Specific Knowledge Bases

Natural Language Reinforcement Learning

Translating Electrocardiograms to Cardiac Magnetic Resonance Imaging Useful for Cardiac Assessment and Disease Screening: A Multi-Center Study AI for ECG to CMR Translation Study

TSINR: Capturing Temporal Continuity via Implicit Neural Representations for Time Series Anomaly Detection

Towards Graph Foundation Models: Training on Knowledge Graphs Enables Transferability to General Graphs

Temporal-Difference Variational Continual Learning

FAMMA: A Benchmark for Financial Domain Multilingual Multimodal Question Answering

Time Awareness in Large Language Models: Benchmarking Fact Recall Across Time

Self-supervised Learning for Acoustic Few-Shot Classification

Double Successive Over-Relaxation Q-Learning with an Extension to Deep Reinforcement Learning

SAKR: Enhancing Retrieval-Augmented Generation via Streaming Algorithm and K-Means Clustering

Compensate Quantization Errors+: Quantized Models Are Inquisitive Learners

Beyond Next Token Prediction: Patch-Level Training for Large Language Models

PersLLM: A Personified Training Approach for Large Language Models

PyramidKV: Dynamic KV Cache Compression based on Pyramidal Information Funneling

Demystifying AI Platform Design for Distributed Inference of Next-Generation LLM models

RoBERTa-BiLSTM: A Context-Aware Hybrid Model for Sentiment Analysis

Tokenization Matters! Degrading Large Language Models through Challenging Their Tokenization

Aligning Transformers with Continuous Feedback via Energy Rank Alignment

Large Language Models for Cyber Security: A Systematic Literature Review

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

CreativeSynth: Cross-Art-Attention for Artistic Image Synthesis with Multimodal Diffusion

LLM A*: Human in the Loop Large Language Models Enabled A* Search for Robotics

Neurodivergent Influenceability as a Contingent Solution to the AI Alignment Problem

AssertionForge: Enhancing Formal Verification Assertion Generation with Structured Representation of Specifications and RTL

Demonstrating specification gaming in reasoning models

SensorChat: Answering Qualitative and Quantitative Questions during Long-Term Multimodal Sensor Interactions

MapExplorer: New Content Generation from Low-Dimensional Visualizations

Addressing and Visualizing Misalignments in Human Task-Solving Trajectories

AriGraph: Learning Knowledge Graph World Models with Episodic Memory for LLM Agents

Learning Progress Driven Multi-Agent Curriculum

Neural Thermodynamic Laws for Large Language Model Training

MathCoder-VL: Bridging Vision and Code for Enhanced Multimodal Mathematical Reasoning

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data

Real-Time Out-of-Distribution Failure Prevention via Multi-Modal Reasoning

LibIQ: Toward Real-Time Spectrum Classification in O-RAN dApps

Knowledge capture, adaptation and composition (KCAC): A framework for cross-task curriculum learning in robotic manipulation

Multi-Token Prediction Needs Registers

PnPXAI: A Universal XAI Framework Providing Automatic Explanations Across Diverse Modalities and Models

UniEval: Unified Holistic Evaluation for Unified Multimodal Understanding and Generation

Fine-tuning Diffusion Policies with Backpropagation Through Diffusion Timesteps

Superposition Yields Robust Neural Scaling

SEAL: Searching Expandable Architectures for Incremental Learning

Vision language models have difficulty recognizing virtual objects

Are Large Language Models Robust in Understanding Code Against Semantics-Preserving Mutations?

IN-RIL: Interleaved Reinforcement and Imitation Learning for Policy Fine-Tuning

PIF: Anomaly detection via preference embedding

Learned Lightweight Smartphone ISP with Unpaired Data

Visual Fidelity Index for Generative Semantic Communications with Critical Information Embedding

Rethinking Repetition Problems of LLMs in Code Generation

Inconsistency Handling in DatalogMTL

Uncovering Magnetic Phases with Synthetic Data and Physics-Informed Training

Schreier-Coset Graph Propagation

Multi-Agent Path Finding For Large Agents Is Intractable

Are Sparse Autoencoders Useful for Java Function Bug Detection?

ILIF: Temporal Inhibitory Leaky Integrate-and-Fire Neuron for Overactivation in Spiking Neural Networks

FactsR: A Safer Method for Producing High Quality Healthcare Documentation

SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity

Uniform Loss vs. Specialized Optimization: A Comparative Analysis in Multi-Task Learning

Emergence of Structure in Ensembles of Random Neural Networks

Translating Electrocardiograms to Cardiac Magnetic Resonance Imaging Useful for Cardiac Assessment and Disease Screening: A Multi-Center Study AI for ECG to CMR Translation Study

Created by

Haebom

저자

Zhengyao Ding, Ziyu Li, Yujian Hu, Youyao Xu, Chengchen Zhao, Yiheng Mao, Haitao Li, Zhikang Li, Qian Li, Jing Wang, Yue Chen, Mengjia Chen, Longbo Wang, Xuesen Chu, Weichao Pan, Ziyi Liu, Fei Wu, Hongkun Zhang, Ting Chen, Zhengxing Huang

개요

본 논문은 심혈관 질환(CVD) 진단을 위한 저렴하고 접근성 높은 도구의 필요성에 주목하여, 심전도(ECG) 신호를 심장 자기 공명 영상(CMR) 수준의 기능적 매개변수와 합성 이미지로 변환하는 심층 학습 프레임워크인 CardioNets를 제안합니다. CardioNets는 교차 모드 대조 학습과 생성적 사전 학습을 통합하여 ECG와 CMR 유래 심장 표현형을 정렬하고, 마스크 자기 회귀 모델을 통해 고해상도 CMR 이미지를 합성합니다. UK Biobank와 MIMIC-IV-ECG 등 다섯 개 코호트의 159,819개 샘플로 훈련되고 독립적인 임상 데이터셋으로 외부 검증된 CardioNets는 질병 선별 및 표현형 추정 작업에서 강력한 성능을 달성했습니다. UK Biobank에서 심장 표현형 회귀 R2를 24.8% 향상시켰고, 심근증 AUC를 최대 39.3% 향상시켰으며, MIMIC에서는 폐 고혈압 검출 AUC를 5.6% 향상시켰습니다. 생성된 CMR 이미지는 기존 접근 방식보다 36.6% 높은 SSIM과 8.7% 높은 PSNR을 보였습니다. 독자 연구에서 ECG 전용 CardioNets는 ECG와 실제 CMR을 모두 사용하는 의사보다 13.9% 높은 정확도를 달성했습니다. 이러한 결과는 CardioNets가 특히 자원이 제한된 환경에서 대규모 CVD 선별을 위한 유망한 저비용 대안을 제공함을 시사합니다. 향후 연구는 ECG 기반 합성 영상의 임상 배포 및 규제 검증에 중점을 둘 것입니다.

시사점, 한계점

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시사점:

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저렴하고 널리 사용 가능한 ECG를 이용하여 CMR 수준의 심장 기능 평가가 가능하다는 것을 보여줌.

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대규모 CVD 선별 검사 및 자원 제약 환경에서의 심장 질환 진단 향상에 기여할 수 있음.

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기존 방법보다 향상된 정확도와 효율성을 제공하는 합성 CMR 이미지 생성.

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의사의 진단 정확도를 능가하는 성능을 보임.

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한계점:

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임상 배포 및 규제 검증이 필요함.

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모델의 일반화 성능에 대한 추가 연구가 필요함.

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다양한 인종 및 연령대에 대한 성능 평가가 추가적으로 필요함.

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ECG 신호의 품질에 대한 의존도가 높을 수 있음.

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