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Ds-agent: Automated data science by empowering large language models with case-based reasoning
In this work, we investigate the potential of large language models (LLMs) based agents to
automate data science tasks, with the goal of comprehending task requirements, then …
automate data science tasks, with the goal of comprehending task requirements, then …
Multi-track message passing: tackling oversmoothing and oversquashing in graph learning via preventing heterophily mixing
The advancement toward deeper graph neural networks is currently obscured by two
inherent issues in message passing,* oversmoothing* and* oversquashing*. We identify the …
inherent issues in message passing,* oversmoothing* and* oversquashing*. We identify the …
Positive and unlabeled learning with controlled probability boundary fence
Positive and Unlabeled (PU) learning refers to a special case of binary classification, and
technically, it aims to induce a binary classifier from a few labeled positive training instances …
technically, it aims to induce a binary classifier from a few labeled positive training instances …
GPFedRec: Graph-guided personalization for federated recommendation
The federated recommendation system is an emerging AI service architecture that provides
recommendation services in a privacy-preserving manner. Using user-relation graphs to …
recommendation services in a privacy-preserving manner. Using user-relation graphs to …
Accurate PROTAC targeted degradation prediction with DegradeMaster
Motivation: Proteolysis-targeting chimeras (PROTACs) are heterobifunctional molecules that
can degrade" undruggable" protein of interest (POI) by recruiting E3 ligases and hijacking …
can degrade" undruggable" protein of interest (POI) by recruiting E3 ligases and hijacking …
Semi-supervised Node Importance Estimation with Informative Distribution Modeling for Uncertainty Regularization
Y Chen, T Wang, Y Fang, Y **ao - THE WEB CONFERENCE 2025 - openreview.net
Graph node importance estimation, a classical problem in network analysis, underpins
various web applications. To improve estimation accuracy, previous methods either exploit …
various web applications. To improve estimation accuracy, previous methods either exploit …