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.

Geo-Registration of Terrestrial LiDAR Point Clouds with Satellite Images without GNSS

Empowering Bridge Digital Twins by Bridging the Data Gap with a Unified Synthesis Framework

AI Agent Smart Contract Exploit Generation

ModelCitizens: Representing Community Voices in Online Safety

Sequential Attention-based Sampling for Histopathological Analysis

Classification of autoimmune diseases from Peripheral blood TCR repertoires by multimodal multi-instance learning

From Video to EEG: Adapting Joint Embedding Predictive Architecture to Uncover Visual Concepts in Brain Signal Analysis

Reinforcement Learning-based Feature Generation Algorithm for Scientific Data

RefineX: Learning to Refine Pre-training Data at Scale from Expert-Guided Programs

On Jailbreaking Quantized Language Models Through Fault Injection Attacks

PBa-LLM: Privacy- and Bias-aware NLP using Named-Entity Recognition (NER)

DriveMRP: Enhancing Vision-Language Models with Synthetic Motion Data for Motion Risk Prediction

Probing and Steering Evaluation Awareness of Language Models

Generating Heterogeneous Multi-dimensional Data : A Comparative Study

Autonomy by Design: Preserving Human Autonomy in AI Decision-Support

PBCAT: Patch-based composite adversarial training against physically realizable attacks on object detection

Federated Breast Cancer Detection Enhanced by Synthetic Ultrasound Image Augmentation

XY-Tokenizer: Mitigating the Semantic-Acoustic Conflict in Low-Bitrate Speech Codecs

DeepTalk: Towards Seamless and Smart Speech Interaction with Adaptive Modality-Specific MoE

SWE-SQL: Illuminating LLM Pathways to Solve User SQL Issues in Real-World Applications

LLM Agent for Hyper-Parameter Optimization

MedSyn: Enhancing Diagnostics with Human-AI Collaboration

Evaluating and Improving Robustness in Large Language Models: A Survey and Future Directions

ConTextTab: A Semantics-Aware Tabular In-Context Learner

QUITE: A Query Rewrite System Beyond Rules with LLM Agents

Saffron-1: Safety Inference Scaling

hdl2v: A Code Translation Dataset for Enhanced LLM Verilog Generation

Knockout LLM Assessment: Using Large Language Models for Evaluations through Iterative Pairwise Comparisons

Humanoid World Models: Open World Foundation Models for Humanoid Robotics

EMORL: Ensemble Multi-Objective Reinforcement Learning for Efficient and Flexible LLM Fine-Tuning

Adaptive Elicitation of Latent Information Using Natural Language

Substance over Style: Evaluating Proactive Conversational Coaching Agents

Real AI Agents with Fake Memories: Fatal Context Manipulation Attacks on Web3 Agents

Sparse Autoencoder as a Zero-Shot Classifier for Concept Erasing in Text-to-Image Diffusion Models

Safer or Luckier? LLMs as Safety Evaluators Are Not Robust to Artifacts

UniF$^2$ace: Fine-grained Face Understanding and Generation with Unified Multimodal Models

DynamicID: Zero-Shot Multi-ID Image Personalization with Flexible Facial Editability

GMLM: Bridging Graph Neural Networks and Language Models for Heterophilic Node Classification

Towards Enterprise-Ready Computer Using Generalist Agent

Oscillation-Reduced MXFP4 Training for Vision Transformers

Understanding Fixed Predictions via Confined Regions

Multi-Attribute Steering of Language Models via Targeted Intervention

Teaching LLMs According to Their Aptitude: Adaptive Reasoning for Mathematical Problem Solving

Theme-Explanation Structure for Table Summarization using Large Language Models: A Case Study on Korean Tabular Data

Scaling 4D Representations

AutoPrep: Natural Language Question-Aware Data Preparation with a Multi-Agent Framework

CHAI for LLMs: Improving Code-Mixed Translation in Large Language Models through Reinforcement Learning with AI Feedback

Vital Insight: Assisting Experts' Context-Driven Sensemaking of Multi-modal Personal Tracking Data Using Visualization and Human-In-The-Loop LLM

Hespi: A pipeline for automatically detecting information from hebarium specimen sheets

Diversifying Robot Locomotion Behaviors with Extrinsic Behavioral Curiosity

Pullback Flow Matching on Data Manifolds

The Impact of Generative AI on Collaborative Open-Source Software Development: Evidence from GitHub Copilot

Breaking PEFT Limitations: Leveraging Weak-to-Strong Knowledge Transfer for Backdoor Attacks in LLMs

Tokenization for Molecular Foundation Models

DilateQuant: Accurate and Efficient Diffusion Quantization via Weight Dilation

PersonaFlow: Designing LLM-Simulated Expert Perspectives for Enhanced Research Ideation

Disentangling Uncertainty for Safe Social Navigation using Deep Reinforcement Learning

CodeMirage: Hallucinations in Code Generated by Large Language Models

A Policy-Gradient Approach to Solving Imperfect-Information Games with Best-Iterate Convergence

Diffusion-Driven Semantic Communication for Generative Models with Bandwidth Constraints

Semantic Augmentation in Images using Language

Geometric Constraints in Deep Learning Frameworks: A Survey

Enhancing Plasticity for First Session Adaptation Continual Learning

Efficient Transfer Learning via Causal Bounds

FEVO: Financial Knowledge Expansion and Reasoning Evolution for Large Language Models

A Wireless Foundation Model for Multi-Task Prediction

GTA1: GUI Test-time Scaling Agent

Modeling (Deontic) Modal Operators With the s(CASP) Goal-directed Predicate Answer Set Programming System

Fuzzy Classification Aggregation for a Continuum of Agents

MedGellan: LLM-Generated Medical Guidance to Support Physicians

Animation Needs Attention: A Holistic Approach to Slides Animation Comprehension with Visual-Language Models

Establishing Best Practices for Building Rigorous Agentic Benchmarks

SHADE-Arena: Evaluating Sabotage and Monitoring in LLM Agents

TRiSM for Agentic AI: A Review of Trust, Risk, and Security Management in LLM-based Agentic Multi-Agent Systems

The end of radical concept nativism

AI-Driven Scholarly Peer Review via Persistent Workflow Prompting, Meta-Prompting, and Meta-Reasoning

Do Larger Language Models Imply Better Generalization? A Pretraining Scaling Law for Implicit Reasoning

SagaLLM: Context Management, Validation, and Transaction Guarantees for Multi-Agent LLM Planning

Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models

ROCKET-2: Steering Visuomotor Policy via Cross-View Goal Alignment

Hybrid Quantum-Classical Multi-Agent Pathfinding

FinSphere, a Real-Time Stock Analysis Agent Powered by Instruction-Tuned LLMs and Domain Tools

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

Can adversarial attacks by large language models be attributed?

Planning Anything with Rigor: General-Purpose Zero-Shot Planning with LLM-based Formalized Programming

OpenRLHF: An Easy-to-use, Scalable and High-performance RLHF Framework

Stepwise functional refoundation of relational concept analysis

A Survey on Event Prediction Methods from a Systems Perspective: Bringing Together Disparate Research Areas

An AI Approach for Learning the Spectrum of the Laplace-Beltrami Operator

Latent Acoustic Mapping for Direction of Arrival Estimation: A Self-Supervised Approach

DeepRetro: Retrosynthetic Pathway Discovery using Iterative LLM Reasoning

Comparative Analysis of CNN and Transformer Architectures with Heart Cycle Normalization for Automated Phonocardiogram Classification

A Novel Hybrid Deep Learning Technique for Speech Emotion Detection using Feature Engineering

Advances in Intelligent Hearing Aids: Deep Learning Approaches to Selective Noise Cancellation

Modeling Heterogeneity across Varying Spatial Extents: Discovering Linkages between Sea Ice Retreat and Ice Shelve Melt in the Antarctic

Surrogate Model for Heat Transfer Prediction in Impinging Jet Arrays using Dynamic Inlet/Outlet and Flow Rate Control

PLAME: Leveraging Pretrained Language Models to Generate Enhanced Protein Multiple Sequence Alignments

Design and Implementation of an OCR-Powered Pipeline for Table Extraction from Invoices

FlexOlmo: Open Language Models for Flexible Data Use

Generating Multi-Table Time Series EHR from Latent Space with Minimal Preprocessing

RAN Cortex: Memory-Augmented Intelligence for Context-Aware Decision-Making in AI-Native Networks

Created by

Haebom

저자

Sebastian Barros

개요

본 논문은 AI 기반 무선 접속 네트워크(RAN) 의사결정 시스템에 컨텍스트 재현 기능을 제공하는 메모리 증강 아키텍처인 RAN Cortex를 제안합니다. 기존의 xApps 및 rApps와 같은 지능형 모듈은 과거 이벤트나 결과에 대한 지속적인 메모리가 없어 반응적인 행동만을 보이는 한계를 지닙니다. RAN Cortex는 네트워크 상태를 고차원 임베딩으로 변환하는 컨텍스트 인코더, 과거 네트워크 에피소드의 벡터 기반 메모리 저장소, 의미적으로 유사한 상황을 검색하는 검색 엔진, 그리고 AI 에이전트에 실시간 또는 준 실시간으로 과거 컨텍스트를 제공하는 정책 인터페이스의 네 가지 요소로 구성된 모듈형 레이어를 도입합니다. O-RAN 인터페이스와 호환되는 시스템 아키텍처를 제시하고, Non-RT 및 Near-RT RIC 도메인 내에서의 실행 가능한 배포를 분석합니다. 경기장 교통 완화 및 드론 통로의 이동성 관리와 같은 예시를 통해 컨텍스트 메모리가 적응성, 연속성 및 전반적인 RAN 지능을 향상시키는 방법을 보여줍니다. 본 논문은 AI 기반 RAN 설계에서 메모리를 누락된 기본 요소로 제시하고 재훈련이나 중앙 집중식 추론 없이 "학습 에이전트"를 가능하게 하는 프레임워크를 제공합니다.

시사점, 한계점

•

시사점:

◦

AI 기반 RAN 의사결정 시스템의 성능 향상: 컨텍스트 메모리를 활용하여 네트워크 동적 특성에 대한 적응력 및 예측력 향상.

◦

지속적인 학습 및 최적화 가능성: 반복적인 패턴 학습을 통해 지속적인 성능 개선.

◦

에너지 효율 증대: 중앙 집중식 추론의 필요성 감소.

◦

O-RAN 표준과의 호환성: 기존 시스템과의 통합 용이.

•

한계점:

◦

메모리 저장소의 크기 및 관리: 대용량 메모리 관리에 대한 효율적인 전략 필요.

◦

검색 엔진의 성능: 효율적이고 정확한 유사 상황 검색 알고리즘 개발 필요.

◦

실제 환경 적용의 어려움: 다양한 네트워크 환경 및 트래픽 패턴에 대한 적용 및 성능 검증 필요.

◦

컨텍스트 인코딩의 효율성: 네트워크 상태를 효과적으로 표현하는 인코딩 방법 필요.

Made with Slashpage