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Chapter History

First Online: 17 September 2023

Limitations and Ethical Statement

: <scp>GraD</scp> relies on informative input node features to learn effective shared LMs (or MLPs) that can generalize to unseen nodes, which is the case in textual graphs. Thus, one limitation is that it is not certain how <scp>GraD</scp> generalizes to other graphs, e.g., to featureless graphs. Moreover as a knowledge distillation approach, <scp>GraD</scp> trades accuracy for computation efficiency and it cannot adapt to dynamic graphs with edge changes the same way as GNN could. To overcome biases encoded in the training graph, e.g., standard stereotypes in recommender graphs, <scp>GraD</scp> needs to be retrained over the new unbiased graph.

Conference Information

Conference Acronym: ECML PKDD

Conference Name: Joint European Conference on Machine Learning and Knowledge Discovery in Databases

Conference City: Turin

Conference Country: Italy

Conference Year: 2023

Conference Start Date: 18 September 2023

Conference End Date: 22 September 2023

Conference Number: 23

Conference ID: ecml2023

Conference URL: https://2023.ecmlpkdd.org/

Peer Review Information (provided by the conference organizers)

Type: Double-blind

Conference Management System: CMT

Number of Submissions Sent for Review: 829

Number of Full Papers Accepted: 196

Number of Short Papers Accepted: 0

Acceptance Rate of Full Papers: 24% - The value is computed by the equation "Number of Full Papers Accepted / Number of Submissions Sent for Review * 100" and then rounded to a whole number.

Average Number of Reviews per Paper: 3.63

Average Number of Papers per Reviewer: 4.5

External Reviewers Involved: Yes

Additional Info on Review Process: Applied Data Science Track: 239 submissions, 58 accepted papers; Demo Track: 31 submissions, 16 accepted papers.