mlsanityData to 13 Oct 2026

μPLAN: Summarizing using a Content Plan as Cross-Lingual Bridge

arXiv 2305.14205 ↗First posted 23 May 2023cs.CLcited by 7

Not on the map. Why?

Abstract (arXiv)

Cross-lingual summarization consists of generating a summary in one language given an input document in a different language, allowing for the dissemination of relevant content across speakers of other languages. The task is challenging mainly due to the paucity of cross-lingual datasets and the compounded difficulty of summarizing and translating. This work presents μPLAN, an approach to cross-lingual summarization that uses an intermediate planning step as a cross-lingual bridge. We formulate the plan as a sequence of entities capturing the summary's content and the order in which it should be communicated. Importantly, our plans abstract from surface form: using a multilingual knowledge base, we align entities to their canonical designation across languages and generate the summary conditioned on this cross-lingual bridge and the input. Automatic and human evaluation on the XWikis dataset (across four language pairs) demonstrates that our planning objective achieves state-of-the-art performance in terms of informativeness and faithfulness. Moreover, μPLAN models improve the zero-shot transfer to new cross-lingual language pairs compared to baselines without a planning component.

Key facts. Cited by 7 papers in the map (data through 13 Oct 2026). Builds on 42 of its 62 references that are in the map. First posted on arXiv 23 May 2023.

Builds on

42 of 62 references.

References · 42

  1. 2017Attention Is All You Needcited by 60,106
  2. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,304
  3. 2019Unsupervised Cross-lingual Representation Learning at Scalecited by 3,916
  4. 2021The Power of Scale for Parameter-Efficient Prompt Tuningcited by 3,785
  5. 2018SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processingcited by 1,979
  6. 2020mT5: A massively multilingual pre-trained text-to-text transformercited by 1,815
  7. 2019PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarizationcited by 1,100
  8. 2015Teaching Machines to Read and Comprehendcited by 1,045
  9. 2020Multilingual Denoising Pre-training for Neural Machine Translationcited by 1,033
  10. 2018XNLI: Evaluating Cross-lingual Sentence Representationscited by 914
  11. 2020On Faithfulness and Factuality in Abstractive Summarizationcited by 898
  12. 2020XTREME: A Massively Multilingual Multi-task Benchmark for Evaluating Cross-lingual Generalizationcited by 741
30 more
  1. 2020TyDi QA: A Benchmark for Information-Seeking Question Answering in Typologically Diverse Languagescited by 487
  2. 2016Google's Multilingual Neural Machine Translation System: Enabling Zero-Shot Translationcited by 467
  3. 2018Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyondcited by 434
  4. 2015A Neural Attention Model for Abstractive Sentence Summarizationcited by 396
  5. 2021XL-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Languagescited by 346
  6. 2017Six Challenges for Neural Machine Translationcited by 335
  7. 2018Newsroom: A Dataset of 1.3 Million Summaries with Diverse Extractive Strategiescited by 293
  8. 2020Multilingual Translation with Extensible Multilingual Pretraining and Finetuningcited by 287
  9. 2020WikiLingua: A New Benchmark Dataset for Cross-Lingual Abstractive Summarizationcited by 154
  10. 2017A Survey Of Cross-lingual Word Embedding Modelscited by 142
  11. 2021Hallucinated but Factual! Inspecting the Factuality of Hallucinations in Abstractive Summarizationcited by 128
  12. 2020MLSUM: The Multilingual Summarization Corpuscited by 121
  13. 2018Data-to-Text Generation with Content Selection and Planningcited by 106
  14. 2019Step-by-Step: Separating Planning from Realization in Neural Data-to-Text Generationcited by 75
  15. 2021Planning with Learned Entity Prompts for Abstractive Summarizationcited by 75
  16. 2022ReFinED: An Efficient Zero-shot-capable Approach to End-to-End Entity Linkingcited by 74
  17. 2019NCLS: Neural Cross-Lingual Summarizationcited by 64
  18. 2019Cross-Lingual Natural Language Generation via Pre-Trainingcited by 63
  19. 2022Overcoming Catastrophic Forgetting in Zero-Shot Cross-Lingual Generationcited by 62
  20. 2022Stretching Sentence-pair NLI Models to Reason over Long Documents and Clusterscited by 44
  21. 2022Conditional Generation with a Question-Answering Blueprintcited by 44
  22. 2022mFACE: Multilingual Summarization with Factual Consistency Evaluationcited by 42
  23. 2022A Survey on Cross-Lingual Summarizationcited by 38
  24. 2021Controllable Neural Dialogue Summarization with Personal Named Entity Planningcited by 36
  25. 2022Models and Datasets for Cross-Lingual Summarisationcited by 36
  26. 2021Data-to-text Generation with Macro Planningcited by 34
  27. 2021Zero-shot Cross-lingual Transfer of Neural Machine Translation with Multilingual Pretrained Encoderscited by 24
  28. 2022Data-to-text Generation with Variational Sequential Planningcited by 17
  29. 2023Text-Blueprint: An Interactive Platform for Plan-based Conditional Generationcited by 9
  30. 2022EntityCS: Improving Zero-Shot Cross-lingual Transfer with Entity-Centric Code Switchingcited by 8

Built on by

Cited by year (2026 to 13 Oct)

Citing papers per year: 2023: 1; 2024: 3; 2025: 2; 2026: 1.

7 papers.