mlsanityData to 14 Oct 2026

Changing the Narrative Perspective: From Deictic to Anaphoric Point of View

arXiv 2103.04176 ↗First posted 6 Mar 2021cs.CL cs.AIcited by 1

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Abstract (arXiv)

We introduce the task of changing the narrative point of view, where characters are assigned a narrative perspective that is different from the one originally used by the writer. The resulting shift in the narrative point of view alters the reading experience and can be used as a tool in fiction writing or to generate types of text ranging from educational to self-help and self-diagnosis. We introduce a benchmark dataset containing a wide range of types of narratives annotated with changes in point of view from deictic (first or second person) to anaphoric (third person) and describe a pipeline for processing raw text that relies on a neural architecture for mention selection. Evaluations on the new benchmark dataset show that the proposed architecture substantially outperforms the baselines by generating mentions that are less ambiguous and more natural.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 12 of its 84 references that are in the map. First posted on arXiv 6 Mar 2021.

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References · 12

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2014Adam: A Method for Stochastic Optimizationcited by 37,240
  3. 2016Deep Biaffine Attention for Neural Dependency Parsingcited by 334
  4. 2017Style Transfer from Non-Parallel Text by Cross-Alignmentcited by 248
  5. 2017End-to-end Neural Coreference Resolutioncited by 241
  6. 2018Dear Sir or Madam, May I introduce the GYAFC Dataset: Corpus, Benchmarks and Metrics for Formality Style Transfercited by 211
  7. 2017Style Transfer in Text: Exploration and Evaluationcited by 146
  8. 2018Style Transfer Through Back-Translationcited by 124
  9. 2017Shakespearizing Modern Language Using Copy-Enriched Sequence-to-Sequence Modelscited by 57
  10. 2017Dynamic Entity Representations in Neural Language Modelscited by 19
  11. 2018NeuralREG: An end-to-end approach to referring expression generationcited by 7
  12. 2017Modeling Semantic Expectation: Using Script Knowledge for Referent Predictioncited by 6

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