Daily Arxiv

전 세계에서 발간되는 인공지능 관련 논문을 정리하는 페이지 입니다.
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PRIX: Learning to Plan from Raw Pixels for End-to-End Autonomous Driving

Swin-TUNA : A Novel PEFT Approach for Accurate Food Image Segmentation

EarthLink: A Self-Evolving AI Agent for Climate Science

Reality Proxy: Fluid Interactions with Real-World Objects in MR via Abstract Representations

Leveraging multi-source and heterogeneous signals for fatigue detection

Segmentation-free Goodness of Pronunciation

Adaptive Relative Pose Estimation Framework with Dual Noise Tuning for Safe Approaching Maneuvers

Compositional Coordination for Multi-Robot Teams with Large Language Models

Diffusion Beats Autoregressive in Data-Constrained Settings

The New LLM Bottleneck: A Systems Perspective on Latent Attention and Mixture-of-Experts

EndoControlMag: Robust Endoscopic Vascular Motion Magnification with Periodic Reference Resetting and Hierarchical Tissue-aware Dual-Mask Control

Long-Short Distance Graph Neural Networks and Improved Curriculum Learning for Emotion Recognition in Conversation

Omni-Thinker: Scaling Cross-Domain Generalization in LLMs via Multi-Task RL with Hybrid Rewards

GCC-Spam: Spam Detection via GAN, Contrastive Learning, and Character Similarity Networks

SDSC:A Structure-Aware Metric for Semantic Signal Representation Learning

Multilingual LLMs Are Not Multilingual Thinkers: Evidence from Hindi Analogy Evaluation

Frequency-Dynamic Attention Modulation for Dense Prediction

A Survey of Deep Learning for Geometry Problem Solving

EEG Foundation Models: A Critical Review of Current Progress and Future Directions

Inversion-DPO: Precise and Efficient Post-Training for Diffusion Models

A PBN-RL-XAI Framework for Discovering a "Hit-and-Run" Therapeutic Strategy in Melanoma

Task Priors: Enhancing Model Evaluation by Considering the Entire Space of Downstream Tasks

OrQstrator: An AI-Powered Framework for Advanced Quantum Circuit Optimization

A comprehensive study of LLM-based argument classification: from LLAMA through GPT-4o to Deepseek-R1

Mechanistic Indicators of Understanding in Large Language Models

Scaling RL to Long Videos

Fast Bilateral Teleoperation and Imitation Learning Using Sensorless Force Control via Accurate Dynamics Model

Masked Autoencoders that Feel the Heart: Unveiling Simplicity Bias for ECG Analyses

SyncMapV2: Robust and Adaptive Unsupervised Segmentation

LLM Web Dynamics: Tracing Model Collapse in a Network of LLMs

Why Do Class-Dependent Evaluation Effects Occur with Time Series Feature Attributions? A Synthetic Data Investigation

Diffuse and Disperse: Image Generation with Representation Regularization

LLM-D12: A Dual-Dimensional Scale of Instrumental and Relational Dependencies on Large Language Models

MambaNeXt-YOLO: A Hybrid State Space Model for Real-time Object Detection

PALADIN : Robust Neural Fingerprinting for Text-to-Image Diffusion Models

Outcome-Based Online Reinforcement Learning: Algorithms and Fundamental Limits

Machine Learning Solutions Integrated in an IoT Healthcare Platform for Heart Failure Risk Stratification

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

Vision Transformers in Precision Agriculture: A Comprehensive Survey

PerceptionLM: Open-Access Data and Models for Detailed Visual Understanding

Position: An Empirically Grounded Identifiability Theory Will Accelerate Self-Supervised Learning Research

LagKV: Lag-Relative Information of the KV Cache Tells Which Tokens Are Important

Trigger without Trace: Towards Stealthy Backdoor Attack on Text-to-Image Diffusion Models

Sparse Logit Sampling: Accelerating Knowledge Distillation in LLMs

Aligning Vision to Language: Annotation-Free Multimodal Knowledge Graph Construction for Enhanced LLMs Reasoning

Att-Adapter: A Robust and Precise Domain-Specific Multi-Attributes T2I Diffusion Adapter via Conditional Variational Autoencoder

When Large Vision-Language Model Meets Large Remote Sensing Imagery: Coarse-to-Fine Text-Guided Token Pruning

Robust Multi-View Learning via Representation Fusion of Sample-Level Attention and Alignment of Simulated Perturbation

Tackling Hallucination from Conditional Models for Medical Image Reconstruction with DynamicDPS

Quantum Machine Learning in Precision Medicine and Drug Discovery -- A Game Changer for Tailored Treatments?

A general language model for peptide identification

ExpliCa: Evaluating Explicit Causal Reasoning in Large Language Models

EVEv2: Improved Baselines for Encoder-Free Vision-Language Models

LLM Alignment as Retriever Optimization: An Information Retrieval Perspective

Pulse-PPG: An Open-Source Field-Trained PPG Foundation Model for Wearable Applications Across Lab and Field Settings

Online Housing Market

Integrated Learning and Optimization for Congestion Management and Profit Maximization in Real-Time Electricity Market

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

Scalable Parameter Design for Superconducting Quantum Circuits with Graph Neural Networks

A Survey of Event Causality Identification: Taxonomy, Challenges, Assessment, and Prospects

Neural Corrective Machine Unranking

Towards a Universal 3D Medical Multi-modality Generalization via Learning Personalized Invariant Representation

Differentiable Motion Manifold Primitives for Reactive Motion Generation under Kinodynamic Constraints

Zeroth-Order Fine-Tuning of LLMs in Random Subspaces

RUMI: Rummaging Using Mutual Information

Neural Machine Unranking

VolDoGer: LLM-assisted Datasets for Domain Generalization in Vision-Language Tasks

Unsupervised Concept Drift Detection from Deep Learning Representations in Real-time

A Multi-Faceted Evaluation Framework for Assessing Synthetic Data Generated by Large Language Models

DualXDA: Towards Sparse, Efficient and Explainable Data Attribution in Large AI Models

Quantifying the Uniqueness and Divisiveness of Presidential Discourse

DocTER: Evaluating Document-based Knowledge Editing

Learning Concepts Definable in First-Order Logic with Counting

Recognizing and Eliciting Weakly Single Crossing Profiles on Trees

Compliance Brain Assistant: Conversational Agentic AI for Assisting Compliance Tasks in Enterprise Environments

Learning Temporal Abstractions via Variational Homomorphisms in Option-Induced Abstract MDPs

When Autonomy Goes Rogue: Preparing for Risks of Multi-Agent Collusion in Social Systems

An Integrated Framework of Prompt Engineering and Multidimensional Knowledge Graphs for Legal Dispute Analysis

DisMS-TS: Eliminating Redundant Multi-Scale Features for Time Series Classification

Corrupted by Reasoning: Reasoning Language Models Become Free-Riders in Public Goods Games

Beamforming and Resource Allocation for Delay Minimization in RIS-Assisted OFDM Systems

Neurodivergent Influenceability as a Contingent Solution to the AI Alignment Problem

EducationQ: Evaluating LLMs' Teaching Capabilities Through Multi-Agent Dialogue Framework

SuperARC: An Agnostic Test for Narrow, General, and Super Intelligence Based On the Principles of Recursive Compression and Algorithmic Probability

IPCGRL: Language-Instructed Reinforcement Learning for Procedural Level Generation

OR-LLM-Agent: Automating Modeling and Solving of Operations Research Optimization Problems with Reasoning LLM

Chemical reasoning in LLMs unlocks strategy-aware synthesis planning and reaction mechanism elucidation

BEARCUBS: A benchmark for computer-using web agents

From Hypothesis to Publication: A Comprehensive Survey of AI-Driven Research Support Systems

HPS: Hard Preference Sampling for Human Preference Alignment

A Differentiated Reward Method for Reinforcement Learning based Multi-Vehicle Cooperative Decision-Making Algorithms

Retrieving Classes of Causal Orders with Inconsistent Knowledge Bases

On the Structure of Game Provenance and its Applications

I-CEE: Tailoring Explanations of Image Classification Models to User Expertise

SIDA: Synthetic Image Driven Zero-shot Domain Adaptation

3D Software Synthesis Guided by Constraint-Expressive Intermediate Representation

Moving Out: Physically-grounded Human-AI Collaboration

SynC: Synthetic Image Caption Dataset Refinement with One-to-many Mapping for Zero-shot Image Captioning

Approximate SMT Counting Beyond Discrete Domains

DRWKV: Focusing on Object Edges for Low-Light Image Enhancement

ACMP: Allen-Cahn Message Passing with Attractive and Repulsive Forces for Graph Neural Networks

Created by

Haebom

저자

Yuelin Wang, Kai Yi, Xinliang Liu, Yu Guang Wang, Shi Jin

개요

본 논문은 그래프 구조 데이터에 대한 기본적인 특징 추출 단위인 신경 메시지 전달을 매력적이고 반발적인 힘과 상전이 모델링에서 발생하는 Allen-Cahn 힘을 가진 상호 작용 입자 시스템으로 모델링합니다. 시스템의 역학은 입자를 분리하면서 폭발하지 않는 반응-확산 과정입니다. 이는 그래프 신경망을 위한 Allen-Cahn 메시지 전달(ACMP)을 유도하며, 입자 시스템 해에 대한 수치적 반복이 메시지 전달 전파를 구성합니다. 신경 ODE 솔버를 사용하여 간단하게 구현할 수 있는 ACMP는 이론적으로 증명된 엄격하게 양의 하한값을 갖는 Dirichlet 에너지를 통해 네트워크 깊이를 최대 100계층까지 높일 수 있습니다. 따라서 과다 평활화라는 일반적인 GNN 문제를 해결하는 GNN의 심층 모델을 제공합니다. ACMP를 사용하는 GNN은 동종 및 이종 데이터 세트 모두에서 실제 노드 분류 작업에 대해 최첨단 성능을 달성합니다. 코드는 https://github.com/ykiiiiii/ACMP 에서 확인할 수 있습니다.

GitHub - ykiiiiii/ACMP: ACMP: Allen-Cahn Message Passing with Attractive and Repulsive Forces for Graph Neural Networks(ICLR 2023)

ACMP: Allen-Cahn Message Passing with Attractive and Repulsive Forces for Graph Neural Networks(ICLR 2023) - ykiiiiii/ACMP

시사점, 한계점

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시사점:

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Allen-Cahn 메시지 전달(ACMP)을 통해 GNN의 깊이를 획기적으로 증가시켜 과다 평활화 문제를 해결할 수 있음을 보여줌.

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간단한 구현과 이론적 근거를 바탕으로 실제 노드 분류 작업에서 최첨단 성능을 달성함.

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Dirichlet 에너지의 엄격하게 양의 하한값을 이론적으로 증명.

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한계점:

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제시된 방법의 계산 비용 및 확장성에 대한 추가적인 분석 필요.

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다양한 그래프 구조 및 작업에 대한 일반화 성능에 대한 추가적인 실험 필요.

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특정 유형의 그래프 데이터에 편향될 가능성 존재.

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