9 papers
Aitchison Embeddings for Learning Compositional Graph Representations
Nikolaos Nakis, Chrysoula Kosma, Panagiotis Promponas +2
Representation learning is central to graph machine learning, powering tasks such as link prediction and node classification. However, most graph embeddings are hard to interpret,…
GreekMMLU: A Native-Sourced Multitask Benchmark for Evaluating Language Models in Greek
Yang Zhang, Mersin Konomi, Christos Xypolopoulos +6
Large Language Models (LLMs) are commonly trained on multilingual corpora that include Greek, yet reliable evaluation benchmarks for Greek-particularly those based on authentic, na…
On the Lipschitz Continuity of Set Aggregation Functions and Neural Networks for Sets
Giannis Nikolentzos, Konstantinos Skianis
The Lipschitz constant of a neural network is connected to several important properties of the network such as its robustness and generalization. It is thus useful in many settings…
Archetypal Graph Generative Models: Explainable and Identifiable Communities via Anchor-Dominant Convex Hulls
Nikolaos Nakis, Chrysoula Kosma, Panagiotis Promponas +2
Representation learning has been essential for graph machine learning tasks such as link prediction, community detection, and network visualization. Despite recent advances in achi…
Graph Linearization Methods for Reasoning on Graphs with Large Language Models
Christos Xypolopoulos, Guokan Shang, Xiao Fei +6
Large language models have evolved to process multiple modalities beyond text, such as images and audio, which motivates us to explore how to effectively leverage them for graph re…
Metrics to Detect Small-Scale and Large-Scale Citation Orchestration
Iakovos Evdaimon, John P. A. Ioannidis, Giannis Nikolentzos +3
Citation counts and related metrics have pervasive uses and misuses in academia and research appraisal, serving as scholarly influence and recognition measures. Hence, comprehendin…