{"url":"/dataset/ipc-grounded","name":"IPC-grounded","full_name":null,"description_markdown":"","description_withheld":null,"homepage":"","introduced_date":null,"introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[],"tasks":[{"name":"Graph Classification","url":"/task/graph-classification","datasets_with_task":"/datasets/task/graph-classification"}],"languages":[],"variants":["IPC-grounded"],"data_loaders":[],"num_papers_in_archive":2,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/graph-classification-on-ipc-grounded","task":"Graph Classification","dataset_variant":"IPC-grounded","rows":2,"metrics":["Accuracy"],"first_row_in_archive_order":{"model":"GG-NN","paper":"/paper/gated-graph-sequence-neural-networks","metrics":{"Accuracy":"77.9%"},"code_links":[{"title":"dmlc/dgl","url":"https://github.com/dmlc/dgl/tree/master/examples/pytorch/ggnn"},{"title":"Microsoft/gated-graph-neural-network-samples","url":"https://github.com/Microsoft/gated-graph-neural-network-samples"},{"title":"chingyaoc/ggnn.pytorch","url":"https://github.com/chingyaoc/ggnn.pytorch"},{"title":"JamesChuanggg/ggnn.pytorch","url":"https://github.com/JamesChuanggg/ggnn.pytorch"},{"title":"yujiali/ggnn","url":"https://github.com/yujiali/ggnn"},{"title":"messi-q/gnnscvuldetector","url":"https://github.com/messi-q/gnnscvuldetector"},{"title":"Microsoft/graph-partition-neural-network-samples","url":"https://github.com/Microsoft/graph-partition-neural-network-samples"},{"title":"bdqnghi/bi-tbcnn","url":"https://github.com/bdqnghi/bi-tbcnn"},{"title":"entslscheia/GGNN_Reasoning","url":"https://github.com/entslscheia/GGNN_Reasoning"},{"title":"alexOarga/haiku-geometric","url":"https://github.com/alexOarga/haiku-geometric/blob/main/haiku_geometric/nn/conv/gated_graph_conv.py"},{"title":"aszot/ggnn","url":"https://github.com/aszot/ggnn"},{"title":"vntchain/gnnscvuldetector","url":"https://github.com/vntchain/gnnscvuldetector"},{"title":"fau-is/grm","url":"https://github.com/fau-is/grm"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/ipc-a-benchmark-data-set-for-learning-with","title":"IPC: A Benchmark Data Set for Learning with Graph-Structured Data","date":"2019-05-15","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/gated-graph-sequence-neural-networks","title":"Gated Graph Sequence Neural Networks","date":"2015-11-17","rows_on_this_dataset":1,"code_links":13,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":12,"samples_ran":0,"samples_unverified":12,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":1,"samples_harvested":12,"samples_ran":0,"samples_unverified":12,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":1,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}