Browse State-of-the-Art › Summarization
Summarization
4 papers with code · 1 benchmark · 8 datasets archive 2025-07-28
Summarization is the task of producing a shorter version of one or several documents that preserves most of the input's meaning.
Description from the archive archive 2025-07-28.
Benchmarks archive 2025-07-28
14 leaderboard tables shown for this task, 1 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted. 10 shown of 14 until expanded.
| Dataset | Best model (first row in archive order) | Paper | Code | Syntology | Compare |
|---|---|---|---|---|---|
| MuLD (VLSP) (2 rows) | Longformer | MuLD: The Multitask Long Document Benchmark | code | — | Compare |
| bazzhangz/sumdataset (0 rows) | no rows in the archive | — | — | ||
| big_patent (0 rows) | no rows in the archive | — | — | ||
| BillSum (0 rows) | no rows in the archive | — | — | ||
| ccdv/arxiv-summarization (0 rows) | no rows in the archive | — | — | ||
| cnn_dailymail (0 rows) | no rows in the archive | — | — | ||
| kmfoda/booksum (0 rows) | no rows in the archive | — | — | ||
| launch/gov_report (0 rows) | no rows in the archive | — | — | ||
| MLSUM de (0 rows) | no rows in the archive | — | — | ||
| multi_news (0 rows) | no rows in the archive | — | — | ||
| SAMSum (0 rows) | no rows in the archive | — | — | ||
| SAMSum Corpus: A Human-annotated Dialogue Dataset for Abstractive Summarization (0 rows) | no rows in the archive | — | — | ||
| scientific_papers (0 rows) | no rows in the archive | — | — | ||
| XSum (0 rows) | no rows in the archive | — | — | ||
Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.
Libraries
Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.
Datasets archive 2025-07-28
8 datasets whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
2 subtasks in the archive's task tree.
Most implemented papers archive 2025-07-28
4 shown of 4 papers with code (8 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
-
19 Feb 2016 4 repositories listed Syntology ran 5 of 6 samples · 1 unverifiedIn this work, we model abstractive text summarization using Attentional Encoder-Decoder Recurrent Neural Networks, and show that they achieve state-of-the-art performance on two different corpora.
-
18 Jun 2024 1 repository listedIt assesses the complexity of tasks with the Hierarchical Prompting Index (HPI), which demonstrates the cognitive competencies of LLMs across diverse datasets and offers insights into the cognitive demands that datasets…
-
15 Feb 2022 1 repository listedThe impressive progress in NLP techniques has been driven by the development of multi-task benchmarks such as GLUE and SuperGLUE.
-
10 Sep 2020 1 repository listedA reduction of quadratic time and memory complexity to sublinear was achieved due to a robust trainable top-k operator.
Syntology lines on 1 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections