activity
20212026
most citedGCExplainer: Human-in-the-Loop Concept-based Explanations for Graph Neural Networks

14 citations · 36 across the 15 of their papers we have counts for

collaborators
Showing 2024Show all

2 papers · 1 filter

cs.CL2024

On the Way to LLM Personalization: Learning to Remember User Conversations

Lucie Charlotte Magister, Katherine Metcalf, Yizhe Zhang +1

Large Language Models (LLMs) have quickly become an invaluable assistant for a variety of tasks. However, their effectiveness is constrained by their ability to tailor responses to…

cs.LG2024★ 1 cited

Explaining Hypergraph Neural Networks: From Local Explanations to Global Concepts

Shiye Su, Iulia Duta, Lucie Charlotte Magister +1

Hypergraph neural networks are a class of powerful models that leverage the message passing paradigm to learn over hypergraphs, a generalization of graphs well-suited to describing…