mlsanityData to 14 Oct 2026

Shaping Political Discourse using multi-source News Summarization

arXiv 2312.11703 ↗First posted 18 Dec 2023cs.CL cs.CY cs.IRcited by 5

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Abstract (arXiv)

Multi-document summarization is the process of automatically generating a concise summary of multiple documents related to the same topic. This summary can help users quickly understand the key information from a large collection of documents. Multi-document summarization systems are more complex than single-document summarization systems due to the need to identify and combine information from multiple sources. In this paper, we have developed a machine learning model that generates a concise summary of a topic from multiple news documents. The model is designed to be unbiased by sampling its input equally from all the different aspects of the topic, even if the majority of the news sources lean one way.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 12 of its 16 references that are in the map. First posted on arXiv 18 Dec 2023.

Builds on

12 of 16 references.

References · 12

  1. 2019Text Summarization with Pretrained Encoderscited by 556
  2. 2018Generating Wikipedia by Summarizing Long Sequencescited by 335
  3. 2016Parsing Argumentation Structures in Persuasive Essayscited by 101
  4. 2018Cross-topic Argument Mining from Heterogeneous Sources Using Attention-based Neural Networkscited by 58
  5. 2019Classification and Clustering of Arguments with Contextualized Word Embeddingscited by 57
  6. 2017Graph-based Neural Multi-Document Summarizationcited by 54
  7. 2018Adapting the Neural Encoder-Decoder Framework from Single to Multi-Document Summarizationcited by 42
  8. 2019Using Local Knowledge Graph Construction to Scale Seq2Seq Models to Multi-Document Inputscited by 38
  9. 2018Footwear Size Recommendation Systemcited by 10
  10. 2019One Embedding To Do Them Allcited by 10
  11. 2023Classification for everyone : Building geography agnostic models for fairer recognitioncited by 5
  12. 2023Exploring Graph Based Approaches for Author Name Disambiguationcited by 4

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 2; 2024: 2; 2025: 0; 2026: 1.

5 papers.

  1. 2024Summarization of Opinionated Political Documents with Varied Perspectivescited by 3
  2. 2026When Bigger Isn't Better: A Comprehensive Fairness Evaluation of Political Bias in Multi-News Summarisationcited by 2
  3. 2024Zero-shot Active Learning Using Self Supervised Learningcited by 1
  4. 2023Detecting anxiety from short clips of free-form speechcited by 0
  5. 2023Exploring intra-task relations to improve meta-learning algorithmscited by 0