mlsanityData to 14 Oct 2026

Returning to the Start: Generating Narratives with Related Endpoints

arXiv 2404.00829 ↗First posted 31 Mar 2024cs.CLcited by 3

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Abstract (arXiv)

Human writers often bookend their writing with ending sentences that relate back to the beginning sentences in order to compose a satisfying narrative that "closes the loop." Motivated by this observation, we propose RENarGen, a controllable story-generation paradigm that generates narratives by ensuring the first and last sentences are related and then infilling the middle sentences. Our contributions include an initial exploration of how various methods of bookending from Narratology affect language modeling for stories. Automatic and human evaluations indicate RENarGen produces better stories with more narrative closure than current autoregressive models.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 21 of its 51 references that are in the map. First posted on arXiv 31 Mar 2024.

Builds on

21 of 51 references.

References · 21

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 13,028
  3. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,170
  4. 2018A Call for Clarity in Reporting BLEU Scorescited by 1,799
  5. 2018Hierarchical Neural Story Generationcited by 1,193
  6. 2019SpanBERT: Improving Pre-training by Representing and Predicting Spanscited by 834
  7. 2016A Corpus and Evaluation Framework for Deeper Understanding of Commonsense Storiescited by 417
  8. 2019MASS: Masked Sequence to Sequence Pre-training for Language Generationcited by 347
  9. 2018Plan-And-Write: Towards Better Automatic Storytellingcited by 234
  10. 2022Re3: Generating Longer Stories With Recursive Reprompting and Revisioncited by 193
  11. 2019Strategies for Structuring Story Generationcited by 124
  12. 2020Enabling Language Models to Fill in the Blankscited by 122
9 more
  1. 2019Insertion-based Decoding with automatically Inferred Generation Ordercited by 43
  2. 2020Modeling Protagonist Emotions for Emotion-Aware Storytellingcited by 42
  3. 2021Uncovering Implicit Gender Bias in Narratives through Commonsense Inferencecited by 32
  4. 2021Automatic Story Generation: Challenges and Attemptscited by 28
  5. 2020Narrative Interpolation for Generating and Understanding Storiescited by 19
  6. 2021Is Everything in Order? A Simple Way to Order Sentencescited by 15
  7. 2023Affective and Dynamic Beam Search for Story Generationcited by 12
  8. 2022Towards Inter-character Relationship-driven Story Generationcited by 11
  9. 2022FastKASSIM: A Fast Tree Kernel-Based Syntactic Similarity Metriccited by 9

Built on by

Cited by year

Citing papers per year: 2024: 1; 2025: 2.

3 papers.

  1. 2024Are Large Language Models Capable of Generating Human-Level Narratives?cited by 79
  2. 2025LLMs Behind the Scenes: Enabling Narrative Scene Illustrationcited by 1
  3. 2025Beyond Direct Generation: A Decomposed Approach to Well-Crafted Screenwriting with LLMscited by 1