Generating Related Work
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Abstract (arXiv)
Communicating new research ideas involves highlighting similarities and differences with past work. Authors write fluent, often long sections to survey the distinction of a new paper with related work. In this work we model generating related work sections while being cognisant of the motivation behind citing papers. Our content planning model generates a tree of cited papers before a surface realization model lexicalizes this skeleton. Our model outperforms several strong state-of-the-art summarization and multi-document summarization models on generating related work on an ACL Anthology (AA) based dataset which we contribute.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 24 of its 48 references that are in the map. First posted on arXiv 18 Apr 2021.
Builds on
24 of 48 references.
References · 24
- 2017Attention Is All You Needcited by 59,932
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
- 2019BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehensioncited by 5,874
- 2019BERTScore: Evaluating Text Generation with BERTcited by 5,462
- 2017Get To The Point: Summarization with Pointer-Generator Networkscited by 1,281
- 2019Generalization through Memorization: Nearest Neighbor Language Modelscited by 788
- 2018Wizard of Wikipedia: Knowledge-Powered Conversational agentscited by 530
- 2019Multi-News: a Large-Scale Multi-Document Summarization Dataset and Abstractive Hierarchical Modelcited by 431
- 2015A Neural Attention Model for Abstractive Sentence Summarizationcited by 394
- 2018Generating Wikipedia by Summarizing Long Sequencescited by 333
- 2019Hierarchical Transformers for Multi-Document Summarizationcited by 132
- 2016Neural Summarization by Extracting Sentences and Wordscited by 114
12 more
- 2020Multi-XScience: A Large-scale Dataset for Extreme Multi-document Summarization of Scientific Articlescited by 96
- 2017Generating Sentences by Editing Prototypescited by 88
- 2019On Extractive and Abstractive Neural Document Summarization with Transformer Language Modelscited by 83
- 2018Retrieve and Refine: Improved Sequence Generation Models For Dialoguecited by 82
- 2018Towards Exploiting Background Knowledge for Building Conversation Systemscited by 57
- 2020Augmenting Transformers with KNN-Based Composite Memory for Dialoguecited by 53
- 2018Adapting the Neural Encoder-Decoder Framework from Single to Multi-Document Summarizationcited by 42
- 2018Query Focused Abstractive Summarization: Incorporating Query Relevance, Multi-Document Coverage, and Summary Length Constraints into seq2seq Modelscited by 39
- 2019Automatic Fact-guided Sentence Modificationcited by 28
- 2019Informative and Controllable Opinion Summarizationcited by 27
- 2019Neural Generative Rhetorical Structure Parsingcited by 5
- 2021Nutribullets Hybrid: Multi-document Health Summarizationcited by 3
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Citing papers per year: 2022: 2; 2023: 0; 2024: 1.
3 papers.