Document Summarization

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

7 leaderboard tables shown for this task, 7 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.

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

28 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

1 subtask in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

30 shown of 226 papers with code (760 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.

• Get To The Point: Summarization with Pointer-Generator Networks
  14 Apr 2017 39 repositories listed Syntology ran 30 of 64 samples · 34 unverified · 44 pointer-only (licence)
  Neural sequence-to-sequence models have provided a viable new approach for abstractive text summarization (meaning they are not restricted to simply selecting and rearranging passages from the original text).
• Language Models are Unsupervised Multitask Learners
  14 Feb 2019 21 repositories listed
  Natural language processing tasks, such as question answering, machine translation, reading comprehension, and summarization, are typically approached with supervised learning on taskspecific datasets.
• Text Summarization with Pretrained Encoders
  22 Aug 2019 19 repositories listed Syntology ran 7 of 21 samples · 14 unverified
  For abstractive summarization, we propose a new fine-tuning schedule which adopts different optimizers for the encoder and the decoder as a means of alleviating the mismatch between the two (the former is pretrained…
• Unified Language Model Pre-training for Natural Language Understanding and Generation
  8 May 2019 9 repositories listed
  This paper presents a new Unified pre-trained Language Model (UniLM) that can be fine-tuned for both natural language understanding and generation tasks.
• GLM: General Language Model Pretraining with Autoregressive Blank Infilling
  18 Mar 2021 8 repositories listed Syntology ran 1 of 1 samples · 0 unverified
  On a wide range of tasks across NLU, conditional and unconditional generation, GLM outperforms BERT, T5, and GPT given the same model sizes and data, and achieves the best performance from a single pretrained model with…
• Extending Context Window of Large Language Models via Positional Interpolation
  27 Jun 2023 7 repositories listed Syntology ran 9 of 15 samples · 6 unverified · 8 pointer-only (licence)
  We present Position Interpolation (PI) that extends the context window sizes of RoPE-based pretrained LLMs such as LLaMA models to up to 32768 with minimal fine-tuning (within 1000 steps), while demonstrating strong…
• SummaRuNNer: A Recurrent Neural Network based Sequence Model for Extractive Summarization of Documents
  14 Nov 2016 7 repositories listed Syntology ran 0 of 7 samples · 7 unverified
  We present SummaRuNNer, a Recurrent Neural Network (RNN) based sequence model for extractive summarization of documents and show that it achieves performance better than or comparable to state-of-the-art.
• Bottom-Up Abstractive Summarization
  31 Aug 2018 5 repositories listed Syntology ran 5 of 6 samples · 1 unverified
  We use this selector as a bottom-up attention step to constrain the model to likely phrases.
• Generating Wikipedia by Summarizing Long Sequences
  30 Jan 2018 4 repositories listed
  We show that generating English Wikipedia articles can be approached as a multi- document summarization of source documents.
• PRIMERA: Pyramid-based Masked Sentence Pre-training for Multi-document Summarization
  16 Oct 2021 3 repositories listed Syntology ran 4 of 7 samples · 3 unverified
  We introduce PRIMERA, a pre-trained model for multi-document representation with a focus on summarization that reduces the need for dataset-specific architectures and large amounts of fine-tuning labeled data.
• DebateSum: A large-scale argument mining and summarization dataset
  14 Nov 2020 3 repositories listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  Finally, we present a search engine for this dataset which is utilized extensively by members of the National Speech and Debate Association today.
• AREDSUM: Adaptive Redundancy-Aware Iterative Sentence Ranking for Extractive Document Summarization
  13 Apr 2020 3 repositories listed
  Redundancy-aware extractive summarization systems score the redundancy of the sentences to be included in a summary either jointly with their salience information or separately as an additional sentence scoring step.
• Scoring Sentence Singletons and Pairs for Abstractive Summarization
  31 May 2019 3 repositories listed
  There is thus a crucial gap between sentence selection and fusion to support summarizing by both compressing single sentences and fusing pairs.
• Don't Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarization
  27 Aug 2018 3 repositories listed Syntology ran 0 of 4 samples · 4 unverified
  We introduce extreme summarization, a new single-document summarization task which does not favor extractive strategies and calls for an abstractive modeling approach.
• Arctic Long Sequence Training: Scalable And Efficient Training For Multi-Million Token Sequences
  16 Jun 2025 2 repositories listed
  ALST supports training Meta's Llama 8B model with 500K sequence length on a single H100 GPU, 3.
• L-CiteEval: Do Long-Context Models Truly Leverage Context for Responding?
  3 Oct 2024 2 repositories listed
  Long-context models (LCMs) have made remarkable strides in recent years, offering users great convenience for handling tasks that involve long context, such as document summarization.
• OARelatedWork: A Large-Scale Dataset of Related Work Sections with Full-texts from Open Access Sources
  3 May 2024 2 repositories listed
  We show that the estimated upper bound for extractive summarization increases by 217% in the ROUGE-2 score, when using full content instead of abstracts.
• An Extractive-Abstractive Approach for Multi-document Summarization of Scientific Articles for Literature Review
  1 Oct 2022 2 repositories listed
  Research in the biomedical domain is con- stantly challenged by its large amount of ever- evolving textual information.
• Proposition-Level Clustering for Multi-Document Summarization
  16 Dec 2021 2 repositories listed
  Text clustering methods were traditionally incorporated into multi-document summarization (MDS) as a means for coping with considerable information repetition.
• Summ^N: A Multi-Stage Summarization Framework for Long Input Dialogues and Documents
  16 Oct 2021 2 repositories listed
  To the best of our knowledge, Summᴺ is the first multi-stage split-then-summarize framework for long input summarization.
• MS2: Multi-Document Summarization of Medical Studies
  13 Apr 2021 2 repositories listed Syntology ran 0 of 5 samples · 5 unverified
  In support of this goal, we release MS^2 (Multi-Document Summarization of Medical Studies), a dataset of over 470k documents and 20k summaries derived from the scientific literature.
• Quantitative Argument Summarization and Beyond: Cross-Domain Key Point Analysis
  11 Oct 2020 2 repositories listed
  Recent work has proposed to summarize arguments by mapping them to a small set of expert-generated key points, where the salience of each key point corresponds to the number of its matching arguments.
• Global-aware Beam Search for Neural Abstractive Summarization
  15 Sep 2020 2 repositories listed
  A global scoring mechanism is then developed to regulate beam search to generate summaries in a near-global optimal fashion.
• Generating (Factual?) Narrative Summaries of RCTs: Experiments with Neural Multi-Document Summarization
  25 Aug 2020 2 repositories listed
  We enlist medical professionals to evaluate generated summaries, and we find that modern summarization systems yield consistently fluent and relevant synopses, but that they are not always factual.
• Pre-training via Paraphrasing
  26 Jun 2020 2 repositories listed Syntology ran 15 of 18 samples · 3 unverified · 3 pointer-only (licence)
  The objective noisily captures aspects of paraphrase, translation, multi-document summarization, and information retrieval, allowing for strong zero-shot performance on several tasks.
• Leveraging Graph to Improve Abstractive Multi-Document Summarization
  20 May 2020 2 repositories listed
  Graphs that capture relations between textual units have great benefits for detecting salient information from multiple documents and generating overall coherent summaries.
• On Faithfulness and Factuality in Abstractive Summarization
  2 May 2020 2 repositories listed Syntology ran 0 of 2 samples · 2 unverified
  It is well known that the standard likelihood training and approximate decoding objectives in neural text generation models lead to less human-like responses for open-ended tasks such as language modeling and story…
• Screenplay Summarization Using Latent Narrative Structure
  27 Apr 2020 2 repositories listed
  Most general-purpose extractive summarization models are trained on news articles, which are short and present all important information upfront.
• Extractive Summarization as Text Matching
  19 Apr 2020 2 repositories listed
  This paper creates a paradigm shift with regard to the way we build neural extractive summarization systems.
• TF-Ranking: Scalable TensorFlow Library for Learning-to-Rank
  30 Nov 2018 2 repositories listed Syntology ran 0 of 4 samples · 4 unverified
  We propose TensorFlow Ranking, the first open source library for solving large-scale ranking problems in a deep learning framework.

Syntology lines on 13 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.