Daily Arxiv

전 세계에서 발간되는 인공지능 관련 논문을 정리하는 페이지 입니다.
본 페이지는 Google Gemini를 활용해 요약 정리하며, 비영리로 운영 됩니다.
논문에 대한 저작권은 저자 및 해당 기관에 있으며, 공유 시 출처만 명기하면 됩니다.

What Has a Foundation Model Found? Using Inductive Bias to Probe for World Models

Squeeze the Soaked Sponge: Efficient Off-policy Reinforcement Finetuning for Large Language Model

The Dark Side of LLMs: Agent-based Attacks for Complete Computer Takeover

Artificial Generals Intelligence: Mastering Generals.io with Reinforcement Learning

HeLo: Heterogeneous Multi-Modal Fusion with Label Correlation for Emotion Distribution Learning

ixi-GEN: Efficient Industrial sLLMs through Domain Adaptive Continual Pretraining

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

Empowering Healthcare Practitioners with Language Models: Structuring Speech Transcripts in Two Real-World Clinical Applications

PWD: Prior-Guided and Wavelet-Enhanced Diffusion Model for Limited-Angle CT

VOTE: Vision-Language-Action Optimization with Trajectory Ensemble Voting

Adaptation of Multi-modal Representation Models for Multi-task Surgical Computer Vision

Multi-modal Representations for Fine-grained Multi-label Critical View of Safety Recognition

MCFormer: A Multi-Cost-Volume Network and Comprehensive Benchmark for Particle Image Velocimetry

Toward Efficient Speech Emotion Recognition via Spectral Learning and Attention

Optimas: Optimizing Compound AI Systems with Globally Aligned Local Rewards

Solving the Hubbard model with Neural Quantum States

S2FGL: Spatial Spectral Federated Graph Learning

Beyond Spatial Frequency: Pixel-wise Temporal Frequency-based Deepfake Video Detection

Are Vision Transformer Representations Semantically Meaningful? A Case Study in Medical Imaging

Description of the Training Process of Neural Networks via Ergodic Theorem : Ghost nodes

A Theory of Inference Compute Scaling: Reasoning through Directed Stochastic Skill Search

Damba-ST: Domain-Adaptive Mamba for Efficient Urban Spatio-Temporal Prediction

Studying and Improving Graph Neural Network-based Motif Estimation

Learning Algorithms in the Limit

Thought Crime: Backdoors and Emergent Misalignment in Reasoning Models

HadaNorm: Diffusion Transformer Quantization through Mean-Centered Transformations

MAEBE: Multi-Agent Emergent Behavior Framework

Evaluating LLM Agent Adherence to Hierarchical Safety Principles: A Lightweight Benchmark for Probing Foundational Controllability Components

What do self-supervised speech models know about Dutch? Analyzing advantages of language-specific pre-training

From Images to Signals: Are Large Vision Models Useful for Time Series Analysis?

One Trajectory, One Token: Grounded Video Tokenization via Panoptic Sub-object Trajectory

BountyBench: Dollar Impact of AI Agent Attackers and Defenders on Real-World Cybersecurity Systems

Anchoring AI Capabilities in Market Valuations: The Capability Realization Rate Model and Valuation Misalignment Risk

Fair Uncertainty Quantification for Depression Prediction

MF-LLM: Simulating Population Decision Dynamics via a Mean-Field Large Language Model Framework

A Cryptographic Perspective on Mitigation vs. Detection in Machine Learning

Constraint Programming Models For Serial Batch Scheduling With Minimum Batch Size

Toward Holistic Evaluation of Recommender Systems Powered by Generative Models

Rankers, Judges, and Assistants: Towards Understanding the Interplay of LLMs in Information Retrieval Evaluation

Localized Concept Erasure for Text-to-Image Diffusion Models Using Training-Free Gated Low-Rank Adaptation

Decoding AI Judgment: How LLMs Assess News Credibility and Bias

Ethical Concerns of Generative AI and Mitigation Strategies: A Systematic Mapping Study

Diffusion Augmented Retrieval: A Training-Free Approach to Interactive Text-to-Image Retrieval

Derivation of Output Correlation Inferences for Multi-Output (aka Multi-Task) Gaussian Process

Cosmos World Foundation Model Platform for Physical AI

Enhancing Transformers for Generalizable First-Order Logical Entailment

Multi-Scenario Reasoning: Unlocking Cognitive Autonomy in Humanoid Robots for Multimodal Understanding

DLaVA: Document Language and Vision Assistant for Answer Localization with Enhanced Interpretability and Trustworthiness

Tiny-Align: Bridging Automatic Speech Recognition and Large Language Model on the Edge

Understanding Chain-of-Thought in LLMs through Information Theory

A Multi-Granularity Supervised Contrastive Framework for Remaining Useful Life Prediction of Aero-engines

MarineFormer: A Spatio-Temporal Attention Model for USV Navigation in Dynamic Marine Environments

HARMONIC: Cognitive and Control Collaboration in Human-Robotic Teams

Investigating Context-Faithfulness in Large Language Models: The Roles of Memory Strength and Evidence Style

Masked Image Modeling: A Survey

Time Makes Space: Emergence of Place Fields in Networks Encoding Temporally Continuous Sensory Experiences

Curriculum Negative Mining For Temporal Networks

C3T: Cross-modal Transfer Through Time for Sensor-based Human Activity Recognition

Multi-Head RAG: Solving Multi-Aspect Problems with LLMs

Solving Probabilistic Verification Problems of Neural Networks using Branch and Bound

Offline Trajectory Optimization for Offline Reinforcement Learning

Structure Guided Large Language Model for SQL Generation

A Theory of Response Sampling in LLMs: Part Descriptive and Part Prescriptive

Don't Push the Button! Exploring Data Leakage Risks in Machine Learning and Transfer Learning

Unsupervised Automata Learning via Discrete Optimization

Don't Get Me Wrong: How to Apply Deep Visual Interpretations to Time Series

An Algorithm for Learning Smaller Representations of Models With Scarce Data

GTA1: GUI Test-time Scaling Agent

Fuzzy Classification Aggregation for a Continuum of Agents

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift

Establishing Best Practices for Building Rigorous Agentic Benchmarks

Thinking Beyond Tokens: From Brain-Inspired Intelligence to Cognitive Foundations for Artificial General Intelligence and its Societal Impact

AI's Euclid's Elements Moment: From Language Models to Computable Thought

Closer to Language than Steam: AI as the Cognitive Engine of a New Productivity Revolution

Access Controls Will Solve the Dual-Use Dilemma

Task Assignment and Exploration Optimization for Low Altitude UAV Rescue via Generative AI Enhanced Multi-agent Reinforcement Learning

Affordable AI Assistants with Knowledge Graph of Thoughts

Deontic Temporal Logic for Formal Verification of AI Ethics

Multi-Agent Pathfinding Under Team-Connected Communication Constraint via Adaptive Path Expansion and Dynamic Leading

Constrain Alignment with Sparse Autoencoders

Multi-modal Generative AI: Multi-modal LLMs, Diffusions and the Unification

SimSUM: Simulated Benchmark with Structured and Unstructured Medical Records

Solving a Stackelberg Game on Transportation Networks in a Dynamic Crime Scenario: A Mixed Approach on Multi-Layer Networks

Traceable Evidence Enhanced Visual Grounded Reasoning: Evaluation and Methodology

PyVision: Agentic Vision with Dynamic Tooling

Single-pass Adaptive Image Tokenization for Minimum Program Search

Multigranular Evaluation for Brain Visual Decoding

Multi-Granular Spatio-Temporal Token Merging for Training-Free Acceleration of Video LLMs

EXPO: Stable Reinforcement Learning with Expressive Policies

Performance and Practical Considerations of Large and Small Language Models in Clinical Decision Support in Rheumatology

Geometry Forcing: Marrying Video Diffusion and 3D Representation for Consistent World Modeling

Why is Your Language Model a Poor Implicit Reward Model?

Reinforcement Learning with Action Chunking

Scaling RL to Long Videos

MIRIX: Multi-Agent Memory System for LLM-Based Agents

Low Resource Reconstruction Attacks Through Benign Prompts

Probing Experts' Perspectives on AI-Assisted Public Speaking Training

Towards Continuous Home Cage Monitoring: An Evaluation of Tracking and Identification Strategies for Laboratory Mice

DTECT: Dynamic Topic Explorer & Context Tracker

Agentic Retrieval of Topics and Insights from Earnings Calls

S2FGL: Spatial Spectral Federated Graph Learning

Created by

Haebom

저자

Zihan Tan, Suyuan Huang, Guancheng Wan, Wenke Huang, He Li, Mang Ye

개요

본 논문은 연합 학습(FL)의 프라이버시 보존 기능과 그래프 신경망(GNN)의 강력한 그래프 모델링 기능을 결합한 연합 그래프 학습(FGL)에 대해 다룹니다. 기존 연구는 서브그래프 FL을 구조적 관점에서만 다루어 공간 및 스펙트럼 도메인에서의 그래프 신호 전파를 간과합니다. 공간적 관점에서 서브그래프 FL은 클라이언트 간 에지 연결 해제를 유발하여 레이블 신호의 중단 및 전역 GNN의 클래스 지식 저하를 초래합니다. 스펙트럼 관점에서 스펙트럼 이질성은 서브그래프 간 신호 주파수의 불일치를 야기하여 로컬 GNN이 로컬 신호 전파 방식에 과적합되게 합니다. 결과적으로 스펙트럼 클라이언트 드리프트가 발생하여 전역 일반화가 저하됩니다. 이러한 문제를 해결하기 위해 레이블 신호 중단을 완화하는 전역 지식 저장소와 스펙트럼 클라이언트 드리프트를 해결하는 주파수 정렬을 제안합니다. 공간 및 스펙트럼 전략의 조합으로 S2FGL 프레임워크를 구성합니다. 여러 데이터 세트에 대한 광범위한 실험을 통해 S2FGL의 우수성을 입증합니다. 코드는 https://github.com/Wonder7racer/S2FGL.git 에서 확인할 수 있습니다.

GitHub - Wonder7racer/S2FGL

Contribute to Wonder7racer/S2FGL development by creating an account on GitHub.

시사점, 한계점

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시사점:

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공간 및 스펙트럼 도메인에서의 그래프 신호 전파를 고려한 새로운 연합 그래프 학습 프레임워크 S2FGL을 제안합니다.

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레이블 신호 중단 및 스펙트럼 클라이언트 드리프트 문제를 효과적으로 해결하여 전역 일반화 성능을 향상시킵니다.

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다양한 데이터셋에서 S2FGL의 우수성을 실험적으로 검증합니다.

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공개된 코드를 통해 재현성을 높였습니다.

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한계점:

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제안된 방법의 계산 복잡도 및 확장성에 대한 추가적인 분석이 필요할 수 있습니다.

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다양한 그래프 구조 및 데이터 분포에 대한 로버스트성을 더욱 검증해야 합니다.

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특정 유형의 그래프에 대해서만 성능이 우수할 가능성이 있습니다. 더 넓은 범위의 그래프 구조에 대한 실험이 필요합니다.

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