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.

HoPE: Hyperbolic Rotary Positional Encoding for Stable Long-Range Dependency Modeling in Large Language Models

Comparative Analysis of Transformer Models in Disaster Tweet Classification for Public Safety

Emergent Social Dynamics of LLM Agents in the El Farol Bar Problem

The Good, the Bad and the Constructive: Automatically Measuring Peer Review's Utility for Authors

Energy Landscapes Enable Reliable Abstention in Retrieval-Augmented Large Language Models for Healthcare

DEXOP: A Device for Robotic Transfer of Dexterous Human Manipulation

Reinforcement Learning for Robust Ageing-Aware Control of Li-ion Battery Systems with Data-Driven Formal Verification

RepoDebug: Repository-Level Multi-Task and Multi-Language Debugging Evaluation of Large Language Models

Gravity Well Echo Chamber Modeling With An LLM-Based Confirmation Bias Model

Insights from Gradient Dynamics: Gradient Autoscaled Normalization

Efficient Virtuoso: A Latent Diffusion Transformer Model for Goal-Conditioned Trajectory Planning

MoSEs: Uncertainty-Aware AI-Generated Text Detection via Mixture of Stylistics Experts with Conditional Thresholds

DCPO: Dynamic Clipping Policy Optimization

DSDE: Dynamic Speculative Decoding with KLD Stability for Real-World Serving

Can AI be Auditable?

Robotic Fire Risk Detection based on Dynamic Knowledge Graph Reasoning: An LLM-Driven Approach with Graph Chain-of-Thought

Navigating the EU AI Act: Foreseeable Challenges in Qualifying Deep Learning-Based Automated Inspections of Class III Medical Devices

Complementary Learning System Empowers Online Continual Learning of Vehicle Motion Forecasting in Smart Cities

MultiPL-MoE: Multi-Programming-Lingual Extension of Large Language Models through Hybrid Mixture-of-Experts

QuadKAN: KAN-Enhanced Quadruped Motion Control via End-to-End Reinforcement Learning

MovieCORE: COgnitive REasoning in Movies

Automatic Prompt Optimization with Prompt Distillation

Membership Inference Attacks on LLM-based Recommender Systems

Leveraging Large Language Models for Accurate Sign Language Translation in Low-Resource Scenarios

Group Expectation Policy Optimization for Heterogeneous Reinforcement Learning

Convergence and Generalization of Anti-Regularization for Parametric Models

Jet-Nemotron: Efficient Language Model with Post Neural Architecture Search

CARFT: Boosting LLM Reasoning via Contrastive Learning with Annotated Chain-of-Thought-based Reinforced Fine-Tuning

Bridging Generalization and Personalization in Human Activity Recognition via On-Device Few-Shot Learning

FinAgentBench: A Benchmark Dataset for Agentic Retrieval in Financial Question Answering

Using Artificial Intuition in Distinct, Minimalist Classification of Scientific Abstracts for Management of Technology Portfolios

Semantic Discrepancy-aware Detector for Image Forgery Identification

Quantum-Efficient Reinforcement Learning Solutions for Last-Mile On-Demand Delivery

BadPromptFL: A Novel Backdoor Threat to Prompt-based Federated Learning in Multimodal Models

Uncertainty-Driven Reliability: Selective Prediction and Trustworthy Deployment in Modern Machine Learning

Real-Time Analysis of Unstructured Data with Machine Learning on Heterogeneous Architectures

VSI: Visual Subtitle Integration for Keyframe Selection to enhance Long Video Understanding

SGDFuse: SAM-Guided Diffusion for High-Fidelity Infrared and Visible Image Fusion

An Efficient Continuous-Time MILP for Integrated Aircraft Hangar Scheduling and Layout

DIRF: A Framework for Digital Identity Protection and Clone Governance in Agentic AI Systems

COLLAGE: Adaptive Fusion-based Retrieval for Augmented Policy Learning

Dynamically Adaptive Reasoning via LLM-Guided MCTS for Efficient and Context-Aware KGQA

Nested Graph Pseudo-Label Refinement for Noisy Label Domain Adaptation Learning

LanternNet: A Hub-and-Spoke System to Seek and Suppress Spotted Lanternfly Populations

RecPS: Privacy Risk Scoring for Recommender Systems

Supervised Fine Tuning on Curated Data is Reinforcement Learning (and can be improved)

Role-Playing LLM-Based Multi-Agent Support Framework for Detecting and Addressing Family Communication Bias

PLAME: Lightweight MSA Design Advances Protein Folding From Evolutionary Embeddings

Driver-Net: Multi-Camera Fusion for Assessing Driver Take-Over Readiness in Automated Vehicles

Leveraging Out-of-Distribution Unlabeled Images: Semi-Supervised Semantic Segmentation with an Open-Vocabulary Model

Visual Structures Helps Visual Reasoning: Addressing the Binding Problem in VLMs

Precise Bayesian Neural Networks

Transit for All: Mapping Equitable Bike2Subway Connection using Region Representation Learning

Scaling Intelligence: Designing Data Centers for Next-Gen Language Models

Image Segmentation with Large Language Models: A Survey with Perspectives for Intelligent Transportation Systems

SAIL: Faster-than-Demonstration Execution of Imitation Learning Policies

Persona-driven Simulation of Voting Behavior in the European Parliament with Large Language Models

Bipedal Balance Control with Whole-body Musculoskeletal Standing and Falling Simulations

Scaling Laws of Motion Forecasting and Planning - Technical Report

Efficient $Q$-Learning and Actor-Critic Methods for Robust Average Reward Reinforcement Learning

Who Gets Credit or Blame? Attributing Accountability in Modern AI Systems

Unsupervised Evolutionary Cell Type Matching via Entropy-Minimized Optimal Transport

Multi-output Classification using a Cross-talk Architecture for Compound Fault Diagnosis of Motors in Partially Labeled Condition

SoloSpeech: Enhancing Intelligibility and Quality in Target Speech Extraction through a Cascaded Generative Pipeline

Steering LLM Reasoning Through Bias-Only Adaptation

MetaSTH-Sleep: Towards Effective Few-Shot Sleep Stage Classification for Health Management with Spatial-Temporal Hypergraph Enhanced Meta-Learning

InterFeat: A Pipeline for Finding Interesting Scientific Features

HumaniBench: A Human-Centric Framework for Large Multimodal Models Evaluation

Advancing Scientific Text Classification: Fine-Tuned Models with Dataset Expansion and Hard-Voting

Test It Before You Trust It: Applying Software Testing for Trustworthy In-context Learning

Action Flow Matching for Continual Robot Learning

Addressing Concept Mislabeling in Concept Bottleneck Models Through Preference Optimization

Nemotron-H: A Family of Accurate and Efficient Hybrid Mamba-Transformer Models

Byzantine-Robust Federated Learning Using Generative Adversarial Networks

Beyond SHAP and Anchors: A large-scale experiment on how developers struggle to design meaningful end-user explanations

VIPER: Visual Perception and Explainable Reasoning for Sequential Decision-Making

DistJoin: A Decoupled Join Cardinality Estimator based on Adaptive Neural Predicate Modulation

Low-Confidence Gold: Refining Low-Confidence Samples for Efficient Instruction Tuning

Assistance or Disruption? Exploring and Evaluating the Design and Trade-offs of Proactive AI Programming Support

Soft Token Attacks Cannot Reliably Audit Unlearning in Large Language Models

CHIRLA: Comprehensive High-resolution Identification and Re-identification for Large-scale Analysis

Kolmogorov-Arnold Fourier Networks

Position: LLMs Can be Good Tutors in English Education

Predicting Steady-State Behavior in Complex Networks with Graph Neural Networks

Separate Motion from Appearance: Customizing Motion via Customizing Text-to-Video Diffusion Models

Motion-enhanced Cardiac Anatomy Segmentation via an Insertable Temporal Attention Module

Bias in Decision-Making for AI's Ethical Dilemmas: A Comparative Study of ChatGPT and Claude

OmniThink: Expanding Knowledge Boundaries in Machine Writing through Thinking

DispFormer: A Pretrained Transformer Incorporating Physical Constraints for Dispersion Curve Inversion

Integrating Evidence into the Design of XAI and AI-based Decision Support Systems: A Means-End Framework for End-users in Construction

Revealing the impact of synthetic native samples and multi-tasking strategies in Hindi-English code-mixed humour and sarcasm detection

Neural Port-Hamiltonian Differential Algebraic Equations for Compositional Learning of Electrical Networks

Sequential Controlled Langevin Diffusions

Privacy-Preserving Federated Learning via Homomorphic Adversarial Networks

CAREL: Instruction-guided reinforcement learning with cross-modal auxiliary objectives

Lessons from Studying Two-Hop Latent Reasoning

HierTOD: A Task-Oriented Dialogue System Driven by Hierarchical Goals

Flexible Coded Distributed Convolution Computing for Enhanced Straggler Resilience and Numerical Stability in Distributed CNNs

FACEGroup: Feasible and Actionable Counterfactual Explanations for Group Fairness

ETF: An Entity Tracing Framework for Hallucination Detection in Code Summaries

DIRF: A Framework for Digital Identity Protection and Clone Governance in Agentic AI Systems

Created by

Haebom

저자

Hammad Atta, Muhammad Zeeshan Baig, Yasir Mehmood, Nadeem Shahzad, Ken Huang, Muhammad Aziz Ul Haq, Muhammad Awais, Kamal Ahmed, Anthony Green

개요

본 논문은 생성형 인공지능(AI)의 발전으로 인해 발생하는 디지털 클로닝, 정교한 사칭, 신원 관련 데이터의 무단 상업화 등의 위협에 대응하기 위해, 디지털 신원 권리 프레임워크(DIRF)를 제안한다. DIRF는 행동, 생체 인식, 성격 기반의 디지털 유사성 속성을 보호하기 위해 설계된 9개 도메인과 63개의 통제 요소로 구성된 구조적 보안 및 거버넌스 모델이다. 법적, 기술적, 하이브리드 집행 메커니즘을 통합하여 디지털 신원에 대한 동의, 추적성 및 수익화를 보장한다. 본 논문은 DIRF의 아키텍처 기반, 집행 전략 및 주요 사용 사례를 제시하며, 플랫폼 구축자, 법률 기관 및 규제 기관에 AI 기반 시스템에서 신원 권리를 강화하는 데 필요한 필수 통제 요소에 대한 정보를 제공하고자 한다.

시사점, 한계점

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시사점:

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생성형 AI 시대의 디지털 신원 보호를 위한 종합적인 프레임워크(DIRF) 제시

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법적, 기술적, 하이브리드 집행 메커니즘 통합을 통한 효과적인 보호 전략 제안

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플랫폼 구축자, 법률 기관 및 규제 기관에 대한 실질적인 가이드라인 제공

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디지털 신원 권리 보호에 대한 논의 및 연구를 촉진

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한계점:

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DIRF의 실제 구현 및 효과에 대한 실증적 연구 부족

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급변하는 AI 기술 발전에 대한 지속적인 적응 및 업데이트 필요성

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다양한 이해관계자 간의 합의 및 협력 필요성

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글로벌 규제 환경의 다양성을 고려한 적용 방안 모색 필요

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