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.

OvA-LP: A Simple and Efficient Framework for Federated Learning on Non-IID Data

8bit-GPT: Exploring Human-AI Interaction on Obsolete Macintosh Operating Systems

Pluralistic Behavior Suite: Stress-Testing Multi-Turn Adherence to Custom Behavioral Policies

Multi-agent Coordination via Flow Matching

Query Generation Pipeline with Enhanced Answerability Assessment for Financial Information Retrieval

BiPETE: A Bi-Positional Embedding Transformer Encoder for Risk Assessment of Alcohol and Substance Use Disorder with Electronic Health Records

Enhancing Public Speaking Skills in Engineering Students Through AI

Learning Fourier shapes to probe the geometric world of deep neural networks

Pattern-Aware Diffusion Synthesis of fMRI/dMRI with Tissue and Microstructural Refinement

Too Good to be Bad: On the Failure of LLMs to Role-Play Villains

DeepForgeSeal: Latent Space-Driven Semi-Fragile Watermarking for Deepfake Detection Using Multi-Agent Adversarial Reinforcement Learning

A benchmark multimodal oro-dental dataset for large vision-language models

Search Is Not Retrieval: Decoupling Semantic Matching from Contextual Assembly in RAG

BudgetMem: Learning Selective Memory Policies for Cost-Efficient Long-Context Processing in Language Models

MERaLiON-SER: Robust Speech Emotion Recognition Model for English and SEA Languages

A Dual Perspective on Decision-Focused Learning: Scalable Training via Dual-Guided Surrogates

You Need Reasoning to Learn Reasoning: The Limitations of Label-Free RL in Weak Base Models

Beta Distribution Learning for Reliable Roadway Crash Risk Assessment

Minimal and Mechanistic Conditions for Behavioral Self-Awareness in LLMs

Software Defined Vehicle Code Generation: A Few-Shot Prompting Approach

Prompt-Based Safety Guidance Is Ineffective for Unlearned Text-to-Image Diffusion Models

Isaac Lab: A GPU-Accelerated Simulation Framework for Multi-Modal Robot Learning

A Standardized Benchmark for Multilabel Antimicrobial Peptide Classification

Unified Multimodal Diffusion Forcing for Forceful Manipulation

An Active Learning Pipeline for Biomedical Image Instance Segmentation with Minimal Human Intervention

PuzzleMoE: Efficient Compression of Large Mixture-of-Experts Models via Sparse Expert Merging and Bit-packed inference

Data Efficiency and Transfer Robustness in Biomedical Image Segmentation: A Study of Redundancy and Forgetting with Cellpose

MDM: Manhattan Distance Mapping of DNN Weights for Parasitic-Resistance-Resilient Memristive Crossbars

Causal Structure and Representation Learning with Biomedical Applications

ScheduleStream: Temporal Planning with Samplers for GPU-Accelerated Multi-Arm Task and Motion Planning & Scheduling

CPO: Condition Preference Optimization for Controllable Image Generation

Knowledge-based anomaly detection for identifying network-induced shape artifacts

Trustworthiness Calibration Framework for Phishing Email Detection Using Large Language Models

IndicVisionBench: Benchmarking Cultural and Multilingual Understanding in VLMs

Temporal convolutional and fusional transformer model with Bi-LSTM encoder-decoder for multi-time-window remaining useful life prediction

Learning to reason about rare diseases through retrieval-augmented agents

Ada-FCN: Adaptive Frequency-Coupled Network for fMRI-Based Brain Disorder Classification

P-MIA: A Profiled-Based Membership Inference Attack on Cognitive Diagnosis Models

First is Not Really Better Than Last: Evaluating Layer Choice and Aggregation Strategies in Language Model Data Influence Estimation

SWAP: Towards Copyright Auditing of Soft Prompts via Sequential Watermarking

Jailbreaking in the Haystack

Prioritize Economy or Climate Action? Investigating ChatGPT Response Differences Based on Inferred Political Orientation

POLIS-Bench: Towards Multi-Dimensional Evaluation of LLMs for Bilingual Policy Tasks in Governmental Scenarios

Measuring what Matters: Construct Validity in Large Language Model Benchmarks

Separate the Wheat from the Chaff: Winnowing Down Divergent Views in Retrieval Augmented Generation

multiMentalRoBERTa: A Fine-tuned Multiclass Classifier for Mental Health Disorder

Simulating Misinformation Vulnerabilities With Agent Personas

EncouRAGe: Evaluating RAG Local, Fast, and Reliable

Reasoning Up the Instruction Ladder for Controllable Language Models

A Penny for Your Thoughts: Decoding Speech from Inexpensive Brain Signals

Adaptive Testing for LLM Evaluation: A Psychometric Alternative to Static Benchmarks

Stateful KV Cache Management for LLMs: Balancing Space, Time, Accuracy, and Positional Fidelity

AI-Powered Citation Auditing: A Zero-Assumption Protocol for Systematic Reference Verification in Academic Research

Efficient Deployment of CNN Models on Multiple In-Memory Computing Units

Reasoning Is All You Need for Urban Planning AI

Cleaning Maintenance Logs with LLM Agents for Improved Predictive Maintenance

Autonomous generation of different courses of action in mechanized combat operations

ORCHID: Orchestrated Retrieval-Augmented Classification with Human-in-the-Loop Intelligent Decision-Making for High-Risk Property

Real-Time Reasoning Agents in Evolving Environments

DMA: Online RAG Alignment with Human Feedback

Epistemic Reject Option Prediction

A hybrid solution approach for the Integrated Healthcare Timetabling Competition 2024

A Theoretical Framework for Environmental Similarity and Vessel Mobility as Coupled Predictors of Marine Invasive Species Pathways

CareMedEval dataset: Evaluating Critical Appraisal and Reasoning in the Biomedical Field

Node-Based Editing for Multimodal Generation of Text, Audio, Image, and Video

Control Barrier Function for Aligning Large Language Models

A Criminology of Machines

FATE: A Formal Benchmark Series for Frontier Algebra of Multiple Difficulty Levels

PoCo: Agentic Proof-of-Concept Exploit Generation for Smart Contracts

Causal Graph Neural Networks for Healthcare

LA-MARRVEL: A Knowledge-Grounded and Language-Aware LLM Reranker for AI-MARRVEL in Rare Disease Diagnosis

OceanAI: A Conversational Platform for Accurate, Transparent, Near-Real-Time Oceanographic Insights

Pay for The Second-Best Service: A Game-Theoretic Approach Against Dishonest LLM Providers

Artificial Intelligence in Elementary STEM Education: A Systematic Review of Current Applications and Future Challenges

Non-Convex Over-the-Air Heterogeneous Federated Learning: A Bias-Variance Trade-off

TraceTrans: Translation and Spatial Tracing for Surgical Prediction

TowerVision: Understanding and Improving Multilinguality in Vision-Language Models

Gestura: A LVLM-Powered System Bridging Motion and Semantics for Real-Time Free-Form Gesture Understanding

ADPO: Anchored Direct Preference Optimization

Rewarding the Journey, Not Just the Destination: A Composite Path and Answer Self-Scoring Reward Mechanism for Test-Time Reinforcement Learning

RealDPO: Real or Not Real, that is the Preference

Deep Edge Filter: Return of the Human-Crafted Layer in Deep Learning

Mathematics with large language models as provers and verifiers

Integrating Sequential and Relational Modeling for User Events: Datasets and Prediction Tasks

A Systematic Evaluation of Self-Supervised Learning for Label-Efficient Sleep Staging with Wearable EEG

Learning to Navigate Socially Through Proactive Risk Perception

Training Large Language Models To Reason In Parallel With Global Forking Tokens

ChessArena: A Chess Testbed for Evaluating Strategic Reasoning Capabilities of Large Language Models

HyperAdapt: Simple High-Rank Adaptation

Comparing Computational Pathology Foundation Models using Representational Similarity Analysis

Back to Ear: Perceptually Driven High Fidelity Music Reconstruction

Test-Time Warmup for Multimodal Large Language Models

Zero-Shot Referring Expression Comprehension via Vison-Language True/False Verification

Memorization in Large Language Models in Medicine: Prevalence, Characteristics, and Implications

Balancing Quality and Variation: Spam Filtering Distorts Data Label Distributions

A Multi-target Bayesian Transformer Framework for Predicting Cardiovascular Disease Biomarkers during Pandemics

Med-GLIP: Advancing Medical Language-Image Pre-training with Large-scale Grounded Dataset

NyayaRAG: Realistic Legal Judgment Prediction with RAG under the Indian Common Law System

XRoboToolkit: A Cross-Platform Framework for Robot Teleoperation

Vibe Coding as a Reconfiguration of Intent Mediation in Software Development: Definition, Implications, and Research Agenda

Who is Responsible When AI Fails? Mapping Causes, Entities, and Consequences of AI Privacy and Ethical Incidents

Created by

Haebom

저자

Hilda Hadan, Reza Hadi Mogavi, Leah Zhang-Kennedy, Lennart E. Nacke

개요

본 논문은 인공지능(AI) 기술의 급속한 발전으로 인해 발생하는 개인정보보호 및 윤리적 문제점을 다룬다. 202건의 실제 AI 관련 사고를 분석하여 AI 생애주기 전반에 걸친 사고 유형을 분류하는 분류 체계를 제시한다. 분석 결과, AI 개발자 및 사용자의 사고 보고 부족, 부적절한 조직적 의사결정 및 법적 준수 미흡, 법적 조치 및 시정 조치의 부족, 위험 완화 노력의 제한 등의 문제점을 발견하였다. 본 연구는 향후 AI 사고 보고를 위한 구조적 접근 방식을 제공하고, 현재 AI 거버넌스 프레임워크의 부적절성을 보여준다. 특히 아동 특화 보호 및 소셜 미디어 내 AI 정책의 필요성을 강조하며, 유해한 AI 생성 콘텐츠의 확산을 완화하기 위한 정책 마련을 촉구한다. 결론적으로, 본 연구는 정책 입안자와 실무자에게 윤리적인 AI 설계, AI 사고 탐지 및 위험 관리, AI 정책 개발을 위한 통찰력을 제공하여 유해한 AI 애플리케이션으로부터 사람들을 보호하고 AI 시스템의 혁신을 지원하는 데 기여한다.

시사점, 한계점

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시사점:

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실제 AI 사고를 바탕으로 한 AI 사고 분류 체계 제공

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AI 개발자 및 사용자의 사고 보고 부족, 부적절한 조직적 의사결정 및 법적 준수 미흡 등의 문제점 제시

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현재 AI 거버넌스 프레임워크의 부적절성을 보여주고 개선 방향 제시

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아동 특화 보호 및 소셜 미디어 내 AI 정책 필요성 강조

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정책 입안자와 실무자에게 윤리적인 AI 설계 및 위험 관리를 위한 통찰력 제공

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한계점:

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분석 대상 사고의 수(202건)가 전체 AI 사고를 대표하는지에 대한 일반화 가능성 검토 필요

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분류 체계의 객관성 및 신뢰성에 대한 추가 검증 필요

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제시된 정책 제언의 구체적인 실행 방안 및 효과성 평가에 대한 추가 연구 필요

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