4 papers
HyperAggregation: Aggregating over Graph Edges with Hypernetworks
Nicolas Lell, Ansgar Scherp
HyperAggregation is a hypernetwork-based aggregation function for Graph Neural Networks. It uses a hypernetwork to dynamically generate weights in the size of the current neighborh…
Text Role Classification in Scientific Charts Using Multimodal Transformers
Hye Jin Kim, Nicolas Lell, Ansgar Scherp
Text role classification involves classifying the semantic role of textual elements within scientific charts. For this task, we propose to finetune two pretrained multimodal docume…
GenCodeSearchNet: A Benchmark Test Suite for Evaluating Generalization in Programming Language Understanding
Andor Diera, Abdelhalim Dahou, Lukas Galke +3
Language models can serve as a valuable tool for software developers to increase productivity. Large generative models can be used for code generation and code completion, while sm…
Open-World Lifelong Graph Learning
Marcel Hoffmann, Lukas Galke, Ansgar Scherp
We study the problem of lifelong graph learning in an open-world scenario, where a model needs to deal with new tasks and potentially unknown classes. We utilize Out-of-Distributio…