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Found 3 papers, 2 papers with code
Certifying Robustness of Graph Convolutional Networks for Node Perturbation with Polyhedra Abstract Interpretation
This poses a significant problem for GCNs intended to be used in critical applications, which need to provide certifiably robust services even in the presence of adversarial perturbations.
Prompting or Fine-tuning? A Comparative Study of Large Language Models for Taxonomy Construction
Our result reveals the following: (1) Even without explicit training on the dataset, the prompting approach outperforms fine-tuning-based approaches.
Towards Improving the Explainability of Text-based Information Retrieval with Knowledge Graphs
In this paper, we propose a general architecture to incorporate knowledge graphs for XIR in various steps of the retrieval process.
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