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.

A Survey of Slow Thinking-based Reasoning LLMs using Reinforced Learning and Inference-time Scaling Law

Agentic Neurodivergence as a Contingent Solution to the AI Alignment Problem

Theoretical Foundations for Semantic Cognition in Artificial Intelligence

Approximate Lifted Model Construction

MultiMind: Enhancing Werewolf Agents with Multimodal Reasoning and Theory of Mind

Advancing Embodied Agent Security: From Safety Benchmarks to Input Moderation

Do We Truly Need So Many Samples? Multi-LLM Repeated Sampling Efficiently Scales Test-Time Compute

Recursive Inference Scaling: A Winning Path to Scalable Inference in Language and Multimodal Systems

Generating Symbolic World Models via Test-time Scaling of Large Language Models

Imagining and building wise machines: The centrality of AI metacognition

Public Perceptions of Fairness Metrics Across Borders

Combating Confirmation Bias: A Unified Pseudo-Labeling Framework for Entity Alignment

Flow-GRPO: Training Flow Matching Models via Online RL

StreamBridge: Turning Your Offline Video Large Language Model into a Proactive Streaming Assistant

ComPO: Preference Alignment via Comparison Oracles

TransProQA: an LLM-based literary Translation evaluation metric with Professional Question Answering

TokLIP: Marry Visual Tokens to CLIP for Multimodal Comprehension and Generation

Reasoning Models Don't Always Say What They Think

Crosslingual Reasoning through Test-Time Scaling

CART-ELC: Oblique Decision Tree Induction via Exhaustive Search

Threshold Modulation for Online Test-Time Adaptation of Spiking Neural Networks

Time of the Flight of the Gaussians: Optimizing Depth Indirectly in Dynamic Radiance Fields

High-fidelity Grain Growth Modeling: Leveraging Deep Learning for Fast Computations

Feature-Augmented Deep Networks for Multiscale Building Segmentation in High-Resolution UAV and Satellite Imagery

Mapping User Trust in Vision Language Models: Research Landscape, Challenges, and Prospects

Scalable Chain of Thoughts via Elastic Reasoning

Benchmarking Ophthalmology Foundation Models for Clinically Significant Age Macular Degeneration Detection

PlaceIt3D: Language-Guided Object Placement in Real 3D Scenes

Software Development Life Cycle Perspective: A Survey of Benchmarks for CodeLLMs and Agents

T-T: Table Transformer for Tagging-based Aspect Sentiment Triplet Extraction

Enhancing Cooperative Multi-Agent Reinforcement Learning with State Modelling and Adversarial Exploration

Put CASH on Bandits: A Max K-Armed Problem for Automated Machine Learning

Incentive-Aware Machine Learning; Robustness, Fairness, Improvement & Causality

LAPSO: A Unified Optimization View for Learning-Augmented Power System Operations

Concept-Based Unsupervised Domain Adaptation

Revealing Weaknesses in Text Watermarking Through Self-Information Rewrite Attacks

Biomed-DPT: Dual Modality Prompt Tuning for Biomedical Vision-Language Models

Stochastic Variational Propagation: Local, Scalable and Efficient Alternative to Backpropagation

Dukawalla: Voice Interfaces for Small Businesses in Africa

Understanding In-context Learning of Addition via Activation Subspaces

Guiding Evolutionary AutoEncoder Training with Activation-Based Pruning Operators

Beyond Low-rank Decomposition: A Shortcut Approach for Efficient On-Device Learning

FG-CLIP: Fine-Grained Visual and Textual Alignment

Teochew-Wild: The First In-the-wild Teochew Dataset with Orthographic Annotations

Direct Image Classification from Fourier Ptychographic Microscopy Measurements without Reconstruction

Image-Text Relation Prediction for Multilingual Tweets

Generating Reliable Synthetic Clinical Trial Data: The Role of Hyperparameter Optimization and Domain Constraints

An Agent-Based Modeling Approach to Free-Text Keyboard Dynamics for Continuous Authentication

StabStitch++: Unsupervised Online Video Stitching with Spatiotemporal Bidirectional Warps

Rethinking Invariance in In-context Learning

Decomposition of Probabilities of Causation with Two Mediators

ChainMarks: Securing DNN Watermark with Cryptographic Chain

AI and Vision based Autonomous Navigation of Nano-Drones in Partially-Known Environments

Moments of Causal Effects

ADD: Physics-Based Motion Imitation with Adversarial Differential Discriminators

Graffe: Graph Representation Learning via Diffusion Probabilistic Models

Chain-of-Thought Tokens are Computer Program Variables

T2VTextBench: A Human Evaluation Benchmark for Textual Control in Video Generation Models

Structural Alignment in Link Prediction

Fair Uncertainty Quantification for Depression Prediction

Physics-Assisted and Topology-Informed Deep Learning for Weather Prediction

An Open-Source Dual-Loss Embedding Model for Semantic Retrieval in Higher Education

SpatialPrompting: Keyframe-driven Zero-Shot Spatial Reasoning with Off-the-Shelf Multimodal Large Language Models

Precise gradient descent training dynamics for finite-width multi-layer neural networks

Clustering with Communication: A Variational Framework for Single Cell Representation Learning

Cross-Branch Orthogonality for Improved Generalization in Face Deepfake Detection

QBR: A Question-Bank-Based Approach to Fine-Grained Legal Knowledge Retrieval for the General Public

ConCISE: Confidence-guided Compression in Step-by-step Efficient Reasoning

GroverGPT-2: Simulating Grover's Algorithm via Chain-of-Thought Reasoning and Quantum-Native Tokenization

Learning from Loss Landscape: Generalizable Mixed-Precision Quantization via Adaptive Sharpness-Aware Gradient Aligning

Federated Learning for Cyber Physical Systems: A Comprehensive Survey

Auto-regressive transformation for image alignment

D-CODA: Diffusion for Coordinated Dual-Arm Data Augmentation

PR2: Peephole Raw Pointer Rewriting with LLMs for Translating C to Safer Rust

Benchmarking LLM Faithfulness in RAG with Evolving Leaderboards

Putting the Value Back in RL: Better Test-Time Scaling by Unifying LLM Reasoners With Verifiers

Quantum-Inspired Optimization Process for Data Imputation

Piecewise Constant Spectral Graph Neural Network

ORBIT-2: Scaling Exascale Vision Foundation Models for Weather and Climate Downscaling

Confabulation dynamics in a reservoir computer: Filling in the gaps with untrained attractors

Replay to Remember (R2R): An Efficient Uncertainty-driven Unsupervised Continual Learning Framework Using Generative Replay

Flower Across Time and Media: Sentiment Analysis of Tang Song Poetry and Visual Correspondence

A Proposal for Evaluating the Operational Risk for ChatBots based on Large Language Models

Exploring Zero-Shot App Review Classification with ChatGPT: Challenges and Potential

When Bad Data Leads to Good Models

QBD-RankedDataGen: Generating Custom Ranked Datasets for Improving Query-By-Document Search Using LLM-Reranking with Reduced Human Effort

Geometric Fault-Tolerant Neural Network Tracking Control of Unknown Systems on Matrix Lie Groups

Advanced Deep Learning Approaches for Automated Recognition of Cuneiform Symbols

Proceedings The 13th International Workshop on Theorem proving components for Educational software

REVEAL: Multi-turn Evaluation of Image-Input Harms for Vision LLM

Personalized Risks and Regulatory Strategies of Large Language Models in Digital Advertising

Advancing 3D Medical Image Segmentation: Unleashing the Potential of Planarian Neural Networks in Artificial Intelligence

Advancing Conversational Diagnostic AI with Multimodal Reasoning

Multimodal Benchmarking and Recommendation of Text-to-Image Generation Models

Rethinking Multimodal Sentiment Analysis: A High-Accuracy, Simplified Fusion Architecture

Language translation, and change of accent for speech-to-speech task using diffusion model

Adaptive Token Boundaries: Integrating Human Chunking Mechanisms into Multimodal LLMs

From Dialect Gaps to Identity Maps: Tackling Variability in Speaker Verification

How Social is It? A Benchmark for LLMs' Capabilities in Multi-user Multi-turn Social Agent Tasks

Toward Holistic Evaluation of Recommender Systems Powered by Generative Models

Elastic Federated Learning over Open Radio Access Network (O-RAN) for Concurrent Execution of Multiple Distributed Learning Tasks

Created by

Haebom

저자

Payam Abdisarabshali, Nicholas Accurso, Filippo Malandra, Weifeng Su, Seyyedali Hosseinalipour

개요

본 논문은 사물 인터넷(IoT) 네트워크에서 연합 학습(FL)의 효율적인 구현을 위한 새로운 분산 기계 학습 아키텍처인 탄성 연합 학습(EFL)을 제안합니다. 5G 및 그 이상의 무선 네트워크에서 FL을 구현하는 과정에서 발생하는 무선 네트워크 상태의 역동성과 여러 FL 서비스의 공존으로 인한 자원 과소/과다 할당 및 관점 기반 부하 분산 문제를 해결하기 위해, EFL은 O-RAN 시스템의 잠재력을 활용하고 탄력적인 자원 프로비저닝 방법론을 도입합니다. 또한, 시스템 및 FL 관련 역동성 및 매개변수를 예측하는 비실시간 시스템 기술자, O-RAN 슬라이싱 및 이동성 관리를 처리하는 준실시간 FL 컨트롤러, 다양한 FL 서비스의 최종 클라이언트에 대한 실시간 자원 할당을 수행하는 FL MAC 스케줄러를 포함한 세 가지 전용 네트워크 제어 기능을 도입하는 다중 시간 척도 FL 관리 시스템을 구성합니다. 마지막으로, EFL의 프로토타입을 통해 FL 서비스 성능 향상 가능성을 보여줍니다.

시사점, 한계점

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시사점:

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5G 및 그 이상의 무선 네트워크 환경에서 연합 학습의 효율성을 높이는 새로운 아키텍처(EFL) 제시

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O-RAN 시스템의 탄력적인 자원 프로비저닝 및 다중 시간 척도 관리 시스템을 통한 FL 서비스 성능 향상 가능성 제시

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비실시간 시스템 기술자, 준실시간 FL 컨트롤러, FL MAC 스케줄러 등의 전용 네트워크 제어 기능을 통해 FL 서비스 관리의 효율성 증대

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실제 프로토타입을 통해 EFL의 성능 향상 가능성을 실증

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한계점:

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제안된 EFL 아키텍처의 실제 구현 및 배포에 대한 상세한 내용 부족

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다양한 IoT 환경 및 FL 서비스에 대한 확장성 및 일반화 가능성에 대한 추가적인 연구 필요

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프로토타입을 통한 성능 평가 결과의 제한된 범위 및 일반화 가능성에 대한 검토 필요

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실제 네트워크 환경에서의 성능 평가 및 안정성에 대한 추가적인 연구 필요

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