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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.

SeC: Advancing Complex Video Object Segmentation via Progressive Concept Construction

GUI-G$^2$: Gaussian Reward Modeling for GUI Grounding

Romance, Relief, and Regret: Teen Narratives of Chatbot Overreliance

Supernova: Achieving More with Less in Transformer Architectures

GR-3 Technical Report

EndoControlMag: Robust Endoscopic Vascular Motion Magnification with Periodic Reference Resetting and Hierarchical Tissue-aware Dual-Mask Contro

AI-Enhanced Precision in Sport Taekwondo: Increasing Fairness, Speed, and Trust in Competition (FST.ai)

Promptomatix: An Automatic Prompt Optimization Framework for Large Language Models

NeuroHD-RA: Neural-distilled Hyperdimensional Model with Rhythm Alignment

IPPRO: Importance-based Pruning with PRojective Offset for Magnitude-indifferent Structural Pruning

Lessons from the TREC Plain Language Adaptation of Biomedical Abstracts (PLABA) track

Seed-X: Building Strong Multilingual Translation LLM with 7B Parameters

Physical models realizing the transformer architecture of large language models

GitChameleon 2.0: Evaluating AI Code Generation Against Python Library Version Incompatibilities

Multimodal Coordinated Online Behavior: Trade-offs and Strategies

A Survey of Deep Learning for Geometry Problem Solving

Prompt4Trust: A Reinforcement Learning Prompt Augmentation Framework for Clinically-Aligned Confidence Calibration in Multimodal Large Language Models

Pre-Training LLMs on a budget: A comparison of three optimizers

OPC: One-Point-Contraction Unlearning Toward Deep Feature Forgetting

Adaptive Gaussian Mixture Models-based Anomaly Detection for under-constrained Cable-Driven Parallel Robots

Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Agent KB: Leveraging Cross-Domain Experience for Agentic Problem Solving

Omni-Router: Sharing Routing Decisions in Sparse Mixture-of-Experts for Speech Recognition

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling

The Joys of Categorical Conformal Prediction

Towards Accurate and Efficient 3D Object Detection for Autonomous Driving: A Mixture of Experts Computing System on Edge

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

FedWSQ: Efficient Federated Learning with Weight Standardization and Distribution-Aware Non-Uniform Quantization

Neural Approaches for Multi-Objective Routing on Multigraphs

Diffusion-Based Electrocardiography Noise Quantification via Anomaly Detection

CogStream: Context-guided Streaming Video Question Answering

Can LLMs Generate Reliable Test Case Generators? A Study on Competition-Level Programming Problems

Towards provable probabilistic safety for scalable embodied AI systems

SenWiCh: Sense-Annotation of Low-Resource Languages for WiC using Hybrid Methods

Human Empathy as Encoder: AI-Assisted Depression Assessment in Special Education

Multimodal Forecasting of Sparse Intraoperative Hypotension Events Powered by Language Model

Autocomp: LLM-Driven Code Optimization for Tensor Accelerators

ViP$^2$-CLIP: Visual-Perception Prompting with Unified Alignment for Zero-Shot Anomaly Detection

ReMi: A Random Recurrent Neural Network Approach to Music Production

Aitomia: Your Intelligent Assistant for AI-Driven Atomistic and Quantum Chemical Simulations

A Goal-Oriented Reinforcement Learning-Based Path Planning Algorithm for Modular Self-Reconfigurable Satellites

A Method for the Architecture of a Medical Vertical Large Language Model Based on Deepseek R1

Balancing Robustness and Efficiency in Embedded DNNs Through Activation Function Selection

Antithetic Sampling for Top-k Shapley Identification

GeoFlow-SLAM: A Robust Tightly-Coupled RGBD-Inertial and Legged Odometry Fusion SLAM for Dynamic Legged Robotics

SciFi-Benchmark: Leveraging Science Fiction To Improve Robot Behavior

ETCH: Generalizing Body Fitting to Clothed Humans via Equivariant Tightness

Global Convergence and Rich Feature Learning in $L$-Layer Infinite-Width Neural Networks under $\mu$P Parametrization

Curating Demonstrations using Online Experience

OMNISEC: LLM-Driven Provenance-based Intrusion Detection via Retrieval-Augmented Behavior Prompting

PRISM: High-Resolution & Precise Counterfactual Medical Image Generation using Language-guided Stable Diffusion

Reasoning Does Not Necessarily Improve Role-Playing Ability

BioMaze: Benchmarking and Enhancing Large Language Models for Biological Pathway Reasoning

Revealing Bias Formation in Deep Neural Networks Through the Geometric Mechanisms of Human Visual Decoupling

Conformal Predictions for Human Action Recognition with Vision-Language Models

Cross-Encoder Rediscovers a Semantic Variant of BM25

DisCoPatch: Taming Adversarially-driven Batch Statistics for Improved Out-of-Distribution Detection

RadAlign: Advancing Radiology Report Generation with Vision-Language Concept Alignment

R-Bot: An LLM-based Query Rewrite System

Towards a Universal 3D Medical Multi-modality Generalization via Learning Personalized Invariant Representation

Atomic Calibration of LLMs in Long-Form Generations

LibEER: A Comprehensive Benchmark and Algorithm Library for EEG-based Emotion Recognition

Aligning AI with Public Values: Deliberation and Decision-Making for Governing Multimodal LLMs in Political Video Analysis

VitaGlyph: Vitalizing Artistic Typography with Flexible Dual-branch Diffusion Models

From homeostasis to resource sharing: Biologically and economically aligned multi-objective multi-agent AI safety benchmarks

V-RoAst: Visual Road Assessment. Can VLM be a Road Safety Assessor Using the iRAP Standard?

FLAIN: Mitigating Backdoor Attacks in Federated Learning via Flipping Weight Updates of Low-Activation Input Neurons

FBSDiff: Plug-and-Play Frequency Band Substitution of Diffusion Features for Highly Controllable Text-Driven Image Translation

Analysis of the 2024 BraTS Meningioma Radiotherapy Planning Automated Segmentation Challenge

Unisolver: PDE-Conditional Transformers Are Universal PDE Solvers

LangBiTe: A Platform for Testing Bias in Large Language Models

Practical Insights into Knowledge Distillation for Pre-Trained Models

Risks of AI Scientists: Prioritizing Safeguarding Over Autonomy

Energy-Efficient and Real-Time Sensing for Federated Continual Learning via Sample-Driven Control

Gemini 2.5 Pro Capable of Winning Gold at IMO 2025

Hierarchical Budget Policy Optimization for Adaptive Reasoning

BioGraphFusion: Graph Knowledge Embedding for Biological Completion and Reasoning

Routine: A Structural Planning Framework for LLM Agent System in Enterprise

CUDA-L1: Improving CUDA Optimization via Contrastive Reinforcement Learning

Assessing Adaptive World Models in Machines with Novel Games

A Multi-granularity Concept Sparse Activation and Hierarchical Knowledge Graph Fusion Framework for Rare Disease Diagnosis

An Integrated Framework of Prompt Engineering and Multidimensional Knowledge Graphs for Legal Dispute Analysis

Hierarchical Reasoning Model

The Unified Cognitive Consciousness Theory for Language Models: Anchoring Semantics, Thresholds of Activation, and Emergent Reasoning

DCG-SQL: Enhancing In-Context Learning for Text-to-SQL with Deep Contextual Schema Link Graph

InternAgent: When Agent Becomes the Scientist -- Building Closed-Loop System from Hypothesis to Verification

R2D2: Remembering, Replaying and Dynamic Decision Making with a Reflective Agentic Memory

Efficient Strategy Learning by Decoupling Searching and Pathfinding for Object Navigation

Alto: Orchestrating Distributed Compound AI Systems with Nested Ancestry

Toward A Causal Framework for Modeling Perception

ThinkAct: Vision-Language-Action Reasoning via Reinforced Visual Latent Planning

MegaScience: Pushing the Frontiers of Post-Training Datasets for Science Reasoning

Rethinking LLM-Based RTL Code Optimization Via Timing Logic Metamorphosis

Beyond Binary Rewards: Training LMs to Reason About Their Uncertainty

Decoding Translation-Related Functional Sequences in 5'UTRs Using Interpretable Deep Learning Models

Steering Out-of-Distribution Generalization with Concept Ablation Fine-Tuning

Never Come Up Empty: Adaptive HyDE Retrieval for Improving LLM Developer Support

AI-enhanced conversational agents for personalized asthma support Factors for engagement, value and efficacy

RAVine: Reality-Aligned Evaluation for Agentic Search

Experience is the Best Teacher: Grounding VLMs for Robotics through Self-Generated Memory

EndoControlMag: Robust Endoscopic Vascular Motion Magnification with Periodic Reference Resetting and Hierarchical Tissue-aware Dual-Mask Contro

Created by

Haebom

저자

An Wanga, Rulin Zhou, Mengya Xu, Yiru Ye, Longfei Gou, Yiting Chang, Hao Chen, Chwee Ming Lim, Jiankun Wang, Hongliang Ren

개요

EndoControlMag은 내시경 수술 중 미세한 혈관 운동을 시각화하기 위한 훈련이 필요 없는 라그랑주 기반 프레임워크입니다. 복잡하고 역동적인 수술 환경에서의 정확한 수술과 의사결정에 필수적인 혈관 운동의 미세한 변화를 시각화하는 데 중점을 두고 있습니다. 주요 모듈로는 오류 누적을 방지하고 시간적 일관성을 유지하기 위해 동적으로 참조 프레임을 업데이트하는 주기적 참조 재설정(PRR) 기법과, 폐색 및 시야 변화에도 정확한 위치 파악을 유지하기 위해 사전 훈련된 시각 추적 모델을 사용하는 계층적 조직 인식 확대(HTM) 프레임워크가 있습니다. HTM은 운동 기반 소프트닝 또는 거리 기반 지수 감쇠 중 하나의 적응적 소프트닝 전략을 적용하여 다양한 수술 시나리오에 적응합니다. EndoVMM24 데이터셋을 사용하여 다양한 수술 유형과 어려운 시나리오에서 성능을 평가했으며, 기존 방법보다 확대 정확도와 시각적 품질이 우수함을 보였습니다. 코드, 데이터셋 및 비디오 결과는 https://szupc.github.io/EndoControlMag/ 에서 확인할 수 있습니다.

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szupc.github.io

시사점, 한계점

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시사점:

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훈련이 필요 없는 라그랑주 기반 프레임워크를 통해 내시경 수술 중 미세한 혈관 운동 시각화의 정확성과 효율성을 높였습니다.

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PRR과 HTM 모듈을 통해 오류 누적을 방지하고 다양한 수술 환경에 적응 가능한 로버스트한 성능을 보여줍니다.

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기존 방법보다 우수한 확대 정확도와 시각적 품질을 제공합니다.

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공개된 코드, 데이터셋, 비디오 결과를 통해 재현성과 접근성을 높였습니다.

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한계점:

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EndoVMM24 데이터셋의 범위가 제한적일 수 있으며, 다양한 수술 유형 및 환경에 대한 일반화 성능에 대한 추가 연구가 필요할 수 있습니다.

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실제 수술 환경에서의 실시간 처리 속도 및 안정성에 대한 추가적인 평가가 필요합니다.

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HTM의 두 가지 소프트닝 전략 중 어떤 전략이 특정 상황에 더 적합한지에 대한 추가적인 분석이 필요할 수 있습니다.

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