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.

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

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

Created by

Haebom

저자

Raphael Weuts (KU Leuven, Belgium), Johannes Bleher (University of Hohenheim, Germany), Hannah Bleher (University of Bonn, Germany), Rozanne Tuesday Flores (Bukidnon State University, Philippines), Guo Xuanyang (Southwest University of Political Science and Law, China), Pawe{\l} Pujszo (College of Europe, Natolin, Poland), Zsolt Almasi (Pazmany Peter Catholic University, Hungary)

개요

본 논문은 인공지능(AI) 시스템이 중요한 분야에 침투함에 따라 윤리적, 법적, 거버넌스적 문제를 해결할 수 있는 전문가의 필요성이 시급해짐을 강조한다. 현재의 AI 윤리 교육은 분야별로 고립되어 실제와 연결되지 않은 단편적인 상태임을 지적하며, 기술적 기반과 윤리, 법, 정책을 통합하는 모듈식의 학제 간 교육과정을 제안한다. AI의 반복적인 운영상 실패(편향, 목표 오류, 일반화 오류, 오용, 거버넌스 실패)를 강조하고, 이를 AI 거버넌스 교육 전략과 연결한다. EU, 중국 및 국제적 틀에서의 관점을 바탕으로 통합 윤리, 이해관계자 참여 및 경험적 학습을 강조하는 학기별 교육 계획을 제시하며, 학생들이 위험을 진단하고 규정을 준수하며 다양한 이해관계자와 소통하여 책임감 있는 AI 거버넌스를 위한 적응력 있고 윤리적으로 기반을 갖춘 전문가를 양성하는 것을 목표로 한다.

시사점, 한계점

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시사점:

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AI 거버넌스 전문가 양성을 위한 학제 간 통합 교육과정의 필요성 제시.

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AI 운영 실패 사례를 바탕으로 한 실질적인 교육 전략 제안.

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EU, 중국 등 다양한 국제적 규제 프레임워크를 고려한 교육 계획 수립.

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통합 윤리, 이해관계자 참여, 경험적 학습을 강조한 실용적인 교육 모델 제시.

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한계점:

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제시된 교육과정의 실제 효과 및 적용 가능성에 대한 실증적 연구 부족.

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특정 국가 및 지역의 규제 환경에 치우친 교육 계획일 가능성.

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다양한 AI 분야의 특수성을 충분히 반영하지 못했을 가능성.

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교육과정 평가 및 지속적인 개선 방안에 대한 구체적인 논의 부족.

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