{"url":"/dataset/agenda","name":"AGENDA","full_name":"Abstract GENeration DAtaset","description_markdown":"Abstract GENeration DAtaset (AGENDA) is a dataset of knowledge graphs paired with scientific abstracts. The dataset consists of 40k paper titles and abstracts from the Semantic Scholar Corpus taken from the proceedings of 12 top AI conferences.\r\n\r\nSource: [Text Generation from Knowledge Graphs with Graph Transformers](https://arxiv.org/pdf/1904.02342v2.pdf)","description_withheld":null,"homepage":"https://github.com/rikdz/GraphWriter","introduced_date":"2019-04-04","introduced_date_note":null,"introduced_by":{"paper":"/paper/text-generation-from-knowledge-graphs-with","title":"Text Generation from Knowledge Graphs with Graph Transformers","first_author":"Rik Koncel-Kedziorski","url":null},"license":{"name":"Unknown","url":null},"modalities":[{"name":"Graphs","url":"/datasets/modality/graphs"}],"tasks":[{"name":"KG-to-Text Generation","url":"/task/kg-to-text","datasets_with_task":"/datasets/task/kg-to-text"}],"languages":[],"variants":["AGENDA"],"data_loaders":[],"num_papers_in_archive":19,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/kg-to-text-generation-on-agenda","task":"KG-to-Text Generation","dataset_variant":"AGENDA","rows":6,"metrics":["BLEU"],"first_row_in_archive_order":{"model":"BART-large+ STA","paper":"/paper/investigating-pretrained-language-models-for","metrics":{"BLEU":"25.66"},"code_links":[{"title":"bjascob/amrlib","url":"https://github.com/bjascob/amrlib"},{"title":"UKPLab/plms-graph2text","url":"https://github.com/UKPLab/plms-graph2text"},{"title":"ukplab/m-amr2text","url":"https://github.com/ukplab/m-amr2text"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/how-to-train-your-agent-to-read-and-write","title":"How to Train Your Agent to Read and Write","date":"2021-01-04","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/investigating-pretrained-language-models-for","title":"Investigating Pretrained Language Models for Graph-to-Text Generation","date":"2020-07-16","rows_on_this_dataset":2,"code_links":3,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":12,"samples_ran":2,"samples_unverified":10,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/modeling-graph-structure-via-relative","title":"Modeling Graph Structure via Relative Position for Text Generation from Knowledge Graphs","date":"2020-06-16","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/modeling-global-and-local-node-contexts-for","title":"Modeling Global and Local Node Contexts for Text Generation from Knowledge Graphs","date":"2020-01-29","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/text-generation-from-knowledge-graphs-with","title":"Text Generation from Knowledge Graphs with Graph Transformers","date":"2019-04-04","rows_on_this_dataset":1,"code_links":3,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":1,"samples_ran":1,"samples_unverified":0,"pointer_only_for_licence":1,"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":2,"samples_harvested":13,"samples_ran":3,"samples_unverified":10,"pointer_only_for_licence":1,"papers_with_no_sample_that_ran":0,"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."}