Daily Arxiv

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Self-Questioning Language Models

Beyond risk: A proto-framework for assessing the societal impact of AI systems

Supervised Dynamic Dimension Reduction with Deep Neural Network

EmoSteer-TTS: Fine-Grained and Training-Free Emotion-Controllable Text-to-Speech via Activation Steering

LLMs Have a Heart of Stone: Demystifying the Soft Thinking Ability of Large Reasoning Models

Industrial LLM-based Code Optimization under Regulation: A Mixture-of-Agents Approach

Reliable Evaluation Protocol for Low-Precision Retrieval

Landsat30-AU: A Vision-Language Dataset for Australian Landsat Imagery

Tool-integrated Reinforcement Learning for Repo Deep Search

CauKer: classification time series foundation models can be pretrained on synthetic data only

Context-Adaptive Multi-Prompt Embedding with Large Language Models for Vision-Language Alignment

DMSC: Dynamic Multi-Scale Coordination Framework for Time Series Forecasting

HyCodePolicy: Hybrid Language Controllers for Multimodal Monitoring and Decision in Embodied Agents

Entity Representation Learning Through Onsite-Offsite Graph for Pinterest Ads

Evaluating User Experience in Conversational Recommender Systems: A Systematic Review Across Classical and LLM-Powered Approaches

Spatial-Frequency Aware for Object Detection in RAW Image

Learning Pivoting Manipulation with Force and Vision Feedback Using Optimization-based Demonstrations

NCCR: to Evaluate the Robustness of Neural Networks and Adversarial Examples

ChartM$^3$: Benchmarking Chart Editing with Multimodal Instructions

From Entanglement to Alignment: Representation Space Decomposition for Unsupervised Time Series Domain Adaptation

EcoTransformer: Attention without Multiplication

Bob's Confetti: Phonetic Memorization Attacks in Music and Video Generation

SDBench: A Comprehensive Benchmark Suite for Speaker Diarization

True Multimodal In-Context Learning Needs Attention to the Visual Context

Gauge Flow Models

Zero-Shot Neural Architecture Search with Weighted Response Correlation

The Dark Side of LLMs: Agent-based Attacks for Complete Computer Takeover

CAVGAN: Unifying Jailbreak and Defense of LLMs via Generative Adversarial Attacks on their Internal Representations

VOTE: Vision-Language-Action Optimization with Trajectory Ensemble Voting

A Comparative Study of Specialized LLMs as Dense Retrievers

Sign Spotting Disambiguation using Large Language Models

UnMix-NeRF: Spectral Unmixing Meets Neural Radiance Fields

Thought Anchors: Which LLM Reasoning Steps Matter?

UITron-Speech: Towards Automated GUI Agents Based on Speech Instructions

15,500 Seconds: Lean UAV Classification Using EfficientNet and Lightweight Fine-Tuning

AtmosMJ: Revisiting Gating Mechanism for AI Weather Forecasting Beyond the Year Scale

On the Fundamental Impossibility of Hallucination Control in Large Language Models

Multi-Modal Multi-Task Federated Foundation Models for Next-Generation Extended Reality Systems: Towards Privacy-Preserving Distributed Intelligence in AR/VR/MR

Text-Only Reasoning Unleashes Zero-Shot Multimodal Evaluators

CAIN: Hijacking LLM-Humans Conversations via Malicious System Prompts

Explain Less, Understand More: Jargon Detection via Personalized Parameter-Efficient Fine-tuning

What Lives? A meta-analysis of diverse opinions on the definition of life

A Generative Neural Annealer for Black-Box Combinatorial Optimization

GRILL: Gradient Signal Restoration in Ill-Conditioned Layers to Enhance Adversarial Attacks on Autoencoders

CostFilter-AD: Enhancing Anomaly Detection through Matching Cost Filtering

Mj\"olnir: A Deep Learning Parametrization Framework for Global Lightning Flash Density

RGB-Event based Pedestrian Attribute Recognition: A Benchmark Dataset and An Asymmetric RWKV Fusion Framework

ProtoECGNet: Case-Based Interpretable Deep Learning for Multi-Label ECG Classification with Contrastive Learning

Beyond Wide-Angle Images: Structure-to-Detail Video Portrait Correction via Unsupervised Spatiotemporal Adaptation

CITRAS: Covariate-Informed Transformer for Time Series Forecasting

Rubric Is All You Need: Enhancing LLM-based Code Evaluation With Question-Specific Rubrics

Empirical Analysis of Sim-and-Real Cotraining of Diffusion Policies for Planar Pushing from Pixels

SimpleRL-Zoo: Investigating and Taming Zero Reinforcement Learning for Open Base Models in the Wild

NuPlanQA: A Large-Scale Dataset and Benchmark for Multi-View Driving Scene Understanding in Multi-Modal Large Language Models

The Impact of Item-Writing Flaws on Difficulty and Discrimination in Item Response Theory

Through the Magnifying Glass: Adaptive Perception Magnification for Hallucination-Free VLM Decoding

Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning

Pull-Based Query Scheduling for Goal-Oriented Semantic Communication

Accelerating Focal Search in Multi-Agent Path Finding with Tighter Lower Bounds

RAILGUN: A Unified Convolutional Policy for Multi-Agent Path Finding Across Different Environments and Tasks

UltraSTF: Ultra-Compact Model for Large-Scale Spatio-Temporal Forecasting

PTQ1.61: Push the Real Limit of Extremely Low-Bit Post-Training Quantization Methods for Large Language Models

Foundation Model of Electronic Medical Records for Adaptive Risk Estimation

Tool Unlearning for Tool-Augmented LLMs

Vision without Images: End-to-End Computer Vision from Single Compressive Measurements

How Do Generative Models Draw a Software Engineer? A Case Study on Stable Diffusion Bias

3DTTNet: Multimodal Fusion-Based 3D Traversable Terrain Modeling for Off-Road Environments

DOGR: Towards Versatile Visual Document Grounding and Referring

Real-World Offline Reinforcement Learning from Vision Language Model Feedback

Causality-Driven Audits of Model Robustness

AUTALIC: A Dataset for Anti-AUTistic Ableist Language In Context

Beyond Adapter Retrieval: Latent Geometry-Preserving Composition via Sparse Task Projection

pyhgf: A neural network library for predictive coding

Human Bias in the Face of AI: Examining Human Judgment Against Text Labeled as AI Generated

AVG-LLaVA: An Efficient Large Multimodal Model with Adaptive Visual Granularity

Parse Trees Guided LLM Prompt Compression

One Model, Any Conjunctive Query: Graph Neural Networks for Answering Queries over Incomplete Knowledge Graphs

A Value Based Parallel Update MCTS Method for Multi-Agent Cooperative Decision Making of Connected and Automated Vehicles

Fairness Definitions in Language Models Explained

CityLight: A Neighborhood-inclusive Universal Model for Coordinated City-scale Traffic Signal Control

Time Evidence Fusion Network: Multi-source View in Long-Term Time Series Forecasting

Long-Term Visual Object Tracking with Event Cameras: An Associative Memory Augmented Tracker and A Benchmark Dataset

Hulk: A Universal Knowledge Translator for Human-Centric Tasks

From Cluster Assumption to Graph Convolution: Graph-based Semi-Supervised Learning Revisited

Environmental Sound Classification on An Embedded Hardware Platform

Data Dependency Inference for Industrial Code Generation Based on UML Sequence Diagrams

InqEduAgent: Adaptive AI Learning Partners with Gaussian Process Augmentation

SE-Agent: Self-Evolution Trajectory Optimization in Multi-Step Reasoning with LLM-Based Agents

RL-PLUS: Countering Capability Boundary Collapse of LLMs in Reinforcement Learning with Hybrid-policy Optimization

Higher Gauge Flow Models

Think How to Think: Mitigating Overthinking with Autonomous Difficulty Cognition in Large Reasoning Models

IS-Bench: Evaluating Interactive Safety of VLM-Driven Embodied Agents in Daily Household Tasks

SLR: Automated Synthesis for Scalable Logical Reasoning

The SWE-Bench Illusion: When State-of-the-Art LLMs Remember Instead of Reason

APOLLO: Automated LLM and Lean Collaboration for Advanced Formal Reasoning

Adversarial Cooperative Rationalization: The Risk of Spurious Correlations in Even Clean Datasets

Learning to Inference Adaptively for Multimodal Large Language Models

Efficient rule induction by ignoring pointless rules

Why the Agent Made that Decision: Contrastive Explanation Learning for Reinforcement Learning

Evaluating Detection Thresholds: The Impact of False Positives and Negatives on Super-Resolution Ultrasound Localization Microscopy

SemiSegECG: A Multi-Dataset Benchmark for Semi-Supervised Semantic Segmentation in ECG Delineation

작성자

Haebom

저자

Minje Park, Jeonghwa Lim, Taehyung Yu, Sunghoon Joo

개요

본 논문은 심전도(ECG) 파형의 의미있는 특징을 분할하는 심전도 분할(ECG delineation)에 초점을 맞추고 있습니다. 공개적으로 이용 가능한 주석이 달린 데이터셋의 부족으로 인해 심층 학습을 이용한 발전이 제한적이었기에, 풍부한 비표시 ECG 데이터를 활용하는 준지도 학습이 유망한 해결책으로 제시됩니다. 이 연구에서는 ECG 분할에서의 준지도 의미론적 분할(SemiSeg)을 위한 최초의 체계적인 벤치마크인 SemiSegECG를 제시합니다. 기존에 활용되지 않던 소스를 포함한 여러 공개 데이터셋을 큐레이팅하고 통합하여 강력하고 다양한 평가를 지원합니다. 컴퓨터 비전에서 5가지 대표적인 SemiSeg 알고리즘을 채택하여 합성곱 신경망과 트랜스포머라는 두 가지 다른 아키텍처에 구현하고, 도메인 내 및 도메인 간 두 가지 설정에서 평가했습니다. 또한 ECG 특정 훈련 구성 및 증강 전략을 제안하고 표준화된 평가 프레임워크를 도입했습니다. 결과는 트랜스포머가 준지도 ECG 분할에서 합성곱 신경망보다 성능이 우수함을 보여줍니다. SemiSegECG는 준지도 ECG 분할 방법을 발전시키고 이 분야의 추가 연구를 촉진하는 기반이 될 것으로 예상됩니다.

시사점, 한계점

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시사점:

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SemiSegECG라는 준지도 의미론적 분할을 위한 최초의 체계적인 ECG 분할 벤치마크를 제공합니다.

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다양한 공개 데이터셋을 통합하여 강건하고 다양한 평가를 가능하게 합니다.

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트랜스포머 아키텍처가 준지도 ECG 분할에서 합성곱 신경망보다 우수한 성능을 보임을 밝힙니다.

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ECG 특정 훈련 구성 및 증강 전략을 제시하여 성능 향상에 기여합니다.

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준지도 ECG 분할 방법 연구 및 발전에 기여할 기반을 마련합니다.

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한계점:

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사용된 데이터셋의 특성 및 규모에 따라 일반화 성능이 달라질 수 있습니다.

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제시된 5가지 SemiSeg 알고리즘 외 다른 알고리즘의 성능 비교가 필요할 수 있습니다.

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실제 임상 환경에서의 성능 검증이 추가적으로 필요합니다.

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도메인 간 성능 차이에 대한 추가적인 분석이 필요할 수 있습니다.

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