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Unmasking Hidden Biases in Network Link Predictions

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Enhancing Equivariant Graph Neural Networks with Magnitude-Modulated Adapters for Chemical Simulations

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Breaking Down Complex Problems: S-DAG’s Approach to Multi-Subject AI Reasoning

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LORETTA: Unveiling a Stealthy Poisoning Attack on Dynamic Graph Neural Networks

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Decoding Contracts: How AI Transforms Legal Document Analysis into Visual Graphs

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Ada-FCN: A New AI Model for Enhanced Brain Disorder Diagnosis Using fMRI

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Navigating Spatio-Temporal Forecasting: When Graph Neural Networks and Foundation Models Shine

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Bridging Structure and Sequence: DGTN’s Novel Approach to Protein Stability Prediction

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DeNoise: A Robust Approach to Unsupervised Graph Anomaly Detection in Noisy Data

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Enhancing Recommendation Accuracy by Decoupling and Denoising Collaborative Signals

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Advancing Relational Deep Learning with Integrated Temporal and Structural Context

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SLIP: Integrating Structural Relationships for Enhanced Vision-Language Understanding

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GraphCliff: A New Approach to Unraveling Molecular Activity Cliffs with Graph Neural Networks

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AI-Powered Framework for Comprehensive Web Accessibility Audits

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Artificial Intelligence Reshaping Financial Services: A New Era for Risk, Fraud, and Investment

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Adaptive AI Model Enhances Multi-Horizon Weather Forecasting Precision

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Optimizing LLM Collaboration: A Graph-Based Approach to Test-Time Scaling

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GraphKeeper: Advancing Graph Models with Domain-Incremental Learning

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Unlocking Network Influence: A Causal Autoencoder for Cross-Network Node Ranking

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GLM: Enhancing LLM Reasoning on Graphs with Multi-Agent Collaboration and Optimized Serving

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Leveraging Structural Data for Better Theorem Proving in Lean

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