Daily Arxiv

전 세계에서 발간되는 인공지능 관련 논문을 정리하는 페이지 입니다.
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GBPP: Grasp-Aware Base Placement Prediction for Robots via Two-Stage Learning

HiChunk: Evaluating and Enhancing Retrieval-Augmented Generation with Hierarchical Chunking

Evalet: Evaluating Large Language Models by Fragmenting Outputs into Functions

Your Compiler is Backdooring Your Model: Understanding and Exploiting Compilation Inconsistency Vulnerabilities in Deep Learning Compilers

Physics-informed neural network solves minimal surfaces in curved spacetime

A funny companion: Distinct neural responses to perceived AI- versus human-generated humor

National Running Club Database: Assessing Collegiate Club Athletes' Cross Country Race Results

Online Learning Based Efficient Resource Allocation for LoRaWAN Network

MetaLLMix : An XAI Aided LLM-Meta-learning Based Approach for Hyper-parameters Optimization

Implicit Neural Representations of Intramyocardial Motion and Strain

MVPBench: A Benchmark and Fine-Tuning Framework for Aligning Large Language Models with Diverse Human Values

MachineLearningLM: Scaling Many-shot In-context Learning via Continued Pretraining

AI Governance in Higher Education: A course design exploring regulatory, ethical and practical considerations

Benchmarking Gender and Political Bias in Large Language Models

BranchGRPO: Stable and Efficient GRPO with Structured Branching in Diffusion Models

TinyDef-DETR: A DETR-based Framework for Defect Detection in Transmission Lines from UAV Imagery

TSPC: A Two-Stage Phoneme-Centric Architecture for code-switching Vietnamese-English Speech Recognition

Spiking Neural Networks for Continuous Control via End-to-End Model-Based Learning

ICR: Iterative Clarification and Rewriting for Conversational Search

ToM-SSI: Evaluating Theory of Mind in Situated Social Interactions

Polysemantic Dropout: Conformal OOD Detection for Specialized LLMs

Keypoint-based Diffusion for Robotic Motion Planning on the NICOL Robot

PVPO: Pre-Estimated Value-Based Policy Optimization for Agentic Reasoning

A Survey of Threats Against Voice Authentication and Anti-Spoofing Systems

OpenWHO: A Document-Level Parallel Corpus for Health Translation in Low-Resource Languages

SIFThinker: Spatially-Aware Image Focus for Visual Reasoning

Sample-Aware Test-Time Adaptation for Medical Image-to-Image Translation

GPT-4.1 Sets the Standard in Automated Experiment Design Using Novel Python Libraries

FastDriveVLA: Efficient End-to-End Driving via Plug-and-Play Reconstruction-based Token Pruning

New Kid in the Classroom: Exploring Student Perceptions of AI Coding Assistants

Analysis of Fourier Neural Operators via Effective Field Theory

FCRF: Flexible Constructivism Reflection for Long-Horizon Robotic Task Planning with Large Language Models

PGT-I: Scaling Spatiotemporal GNNs with Memory-Efficient Distributed Training

Memorization Sinks: Isolating Memorization during LLM Training

Clue-RAG: Towards Accurate and Cost-Efficient Graph-based RAG via Multi-Partite Graph and Query-Driven Iterative Retrieval

OGF: An Online Gradient Flow Method for Optimizing the Statistical Steady-State Time Averages of Unsteady Turbulent Flows

AC-Refiner: Efficient Arithmetic Circuit Optimization Using Conditional Diffusion Models

Towards Bio-Inspired Robotic Trajectory Planning via Self-Supervised RNN

Evaluating the Robustness of Open-Source Vision-Language Models to Domain Shift in Object Captioning

Can Generalist Vision Language Models (VLMs) Rival Specialist Medical VLMs? Benchmarking and Strategic Insights

Efficient Context Selection for Long-Context QA: No Tuning, No Iteration, Just Adaptive-$k$

Worst-Case Symbolic Constraints Analysis and Generalisation with Large Language Models

MedEBench: Diagnosing Reliability in Text-Guided Medical Image Editing

Counterfactual Simulatability of LLM Explanations for Generation Tasks

PatentScore: Multi-dimensional Evaluation of LLM-Generated Patent Claims

HiLAB: A Hybrid Inverse-Design Framework

Tuning-Free LLM Can Build A Strong Recommender Under Sparse Connectivity And Knowledge Gap Via Extracting Intent

WaterFlow: Learning Fast & Robust Watermarks using Stable Diffusion

Is the Top Still Spinning? Evaluating Subjectivity in Narrative Understanding

Sketch-of-Thought: Efficient LLM Reasoning with Adaptive Cognitive-Inspired Sketching

Training-free Adjustable Polynomial Graph Filtering for Ultra-fast Multimodal Recommendation

Teaching Your Models to Understand Code via Focal Preference Alignment

Investigating the use of terrain-following coordinates in AI-driven precipitation forecasts

SuPreME: A Supervised Pre-training Framework for Multimodal ECG Representation Learning

Safe Learning Under Irreversible Dynamics via Asking for Help

Robust Adaptation of Large Multimodal Models for Retrieval Augmented Hateful Meme Detection

How Much Do LLMs Hallucinate across Languages? On Multilingual Estimation of LLM Hallucination in the Wild

TokenSkip: Controllable Chain-of-Thought Compression in LLMs

Break the Checkbox: Challenging Closed-Style Evaluations of Cultural Alignment in LLMs

Pitfalls of defacing whole-head MRI: re-identification risk with diffusion models and compromised research potential

AI/ML Based Detection and Categorization of Covert Communication in IPv6 Network

Learn from Global Correlations: Enhancing Evolutionary Algorithm via Spectral GNN

Enhancing Automated Loop Invariant Generation for Complex Programs with Large Language Models

Talking to DINO: Bridging Self-Supervised Vision Backbones with Language for Open-Vocabulary Segmentation

Convex Regularization and Convergence of Policy Gradient Flows under Safety Constraints

Adversarial Prompt Distillation for Vision-Language Models

TrojanRobot: Physical-world Backdoor Attacks Against VLM-based Robotic Manipulation

The Belief State Transformer

A Statistical Analysis of Deep Federated Learning for Intrinsically Low-dimensional Data

Responsible AI in NLP: GUS-Net Span-Level Bias Detection Dataset and Benchmark for Generalizations, Unfairness, and Stereotypes

T2V-Turbo-v2: Enhancing Video Generation Model Post-Training through Data, Reward, and Conditional Guidance Design

TRANSAGENT: An LLM-Based Multi-Agent System for Code Translation

Context-Aware Membership Inference Attacks against Pre-trained Large Language Models

RingMo-Aerial: An Aerial Remote Sensing Foundation Model With Affine Transformation Contrastive Learning

Solving Truly Massive Budgeted Monotonic POMDPs with Oracle-Guided Meta-Reinforcement Learning

Informed Correctors for Discrete Diffusion Models

EMOE: A Framework for Out-of-distribution Uncertainty Based Rejection via Model-Agnostic Expansive Matching of Experts

Empowering Time Series Analysis with Foundation Models: A Comprehensive Survey

Learning Environment-Aware Affordance for 3D Articulated Object Manipulation under Occlusions

Co-Alignment: Rethinking Alignment as Bidirectional Human-AI Cognitive Adaptation

When Safe Unimodal Inputs Collide: Optimizing Reasoning Chains for Cross-Modal Safety in Multimodal Large Language Models

Agentic Lybic: Multi-Agent Execution System with Tiered Reasoning and Orchestration

Executable Ontologies: Synthesizing Event Semantics with Dataflow Architecture

Explaining Tournament Solutions with Minimal Supports

Neuromorphic Computing with Multi-Frequency Oscillations: A Bio-Inspired Approach to Artificial Intelligence

TRiSM for Agentic AI: A Review of Trust, Risk, and Security Management in LLM-based Agentic Multi-Agent Systems

Small Language Models are the Future of Agentic AI

Contra4: Evaluating Contrastive Cross-Modal Reasoning in Audio, Video, Image, and 3D

Random Rule Forest (RRF): Interpretable Ensembles of LLM-Generated Questions for Predicting Startup Success

Comprehend, Divide, and Conquer: Feature Subspace Exploration via Multi-Agent Hierarchical Reinforcement Learning

Robust Decision-Making Via Free Energy Minimization

CredID: Credible Multi-Bit Watermark for Large Language Models Identification

Probing LLM Hallucination from Within: Perturbation-Driven Approach via Internal Knowledge

Overcoming classic challenges for artificial neural networks by providing incentives and practice

Federated Cross-Training Learners for Robust Generalization under Data Heterogeneity

Concurrent Linguistic Error Detection (CLED): a New Methodology for Error Detection in Large Language Models

Contrastive timbre representations for musical instrument and synthesizer retrieval

HARMONIC: A Content-Centric Cognitive Robotic Architecture

RadGame: An AI-Powered Platform for Radiology Education

JANUS: A Dual-Constraint Generative Framework for Stealthy Node Injection Attacks

Can Generalist Vision Language Models (VLMs) Rival Specialist Medical VLMs? Benchmarking and Strategic Insights

Created by

Haebom

저자

Yuan Zhong, Ruinan Jin, Qi Dou, Xiaoxiao Li

개요

본 연구는 의료 영상 진단 및 해석에 있어 전문 의료 Vision Language Model (VLM)과 일반 VLM의 상호 보완적인 강점을 강조합니다. 전문 의료 VLM은 특정 모달리티에 특화된 경우 유용하지만, 효율적으로 미세 조정된 일반 VLM은 특히 미지 또는 희귀한 OOD 의료 모달리티로 전이하는 경우 대부분의 과제에서 동등하거나 더 나은 성능을 달성할 수 있음을 보여줍니다. 따라서 전문적인 의료 사전 학습의 부족으로 제한되는 것이 아니라, 일반 VLM이 임상 AI 개발을 위한 확장 가능하고 비용 효율적인 경로를 제공할 수 있음을 시사합니다.

시사점, 한계점

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시사점:

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일반 VLM이 효율적인 미세 조정을 통해 전문 의료 VLM과 비교 가능하거나 우수한 성능을 보임.

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특히 미지 또는 희귀 의료 모달리티에서 일반 VLM의 우수성이 더욱 두드러짐.

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일반 VLM을 활용한 임상 AI 개발의 확장성 및 비용 효율성 증대 가능성 제시.

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전문 의료 VLM과 일반 VLM의 상호 보완적 활용 가능성 제시.

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한계점:

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본 연구에서 사용된 데이터셋 및 과제의 특성에 따른 일반화 가능성 제한.

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다양한 의료 모달리티 및 임상 시나리오에 대한 추가적인 연구 필요.

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일반 VLM의 미세 조정 전략 및 최적화에 대한 추가적인 연구 필요.

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