mlsanityData to 7 Oct 2026

Text Generation with Exemplar-based Adaptive Decoding

arXiv 1904.04428 ↗First posted 9 Apr 2019cs.CLcited by 28

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Abstract (arXiv)

We propose a novel conditioned text generation model. It draws inspiration from traditional template-based text generation techniques, where the source provides the content (i.e., what to say), and the template influences how to say it. Building on the successful encoder-decoder paradigm, it first encodes the content representation from the given input text; to produce the output, it retrieves exemplar text from the training data as "soft templates," which are then used to construct an exemplar-specific decoder. We evaluate the proposed model on abstractive text summarization and data-to-text generation. Empirical results show that this model achieves strong performance and outperforms comparable baselines.

Key facts. Cited by 28 papers in the map (data through 7 Oct 2026). First posted on arXiv 9 Apr 2019.

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Citing papers per year: 2021: 11; 2022: 7; 2023: 2; 2024: 7; 2025: 1.

28 papers.

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  1. 2021What Makes Good In-Context Examples for GPT-3?cited by 1,184
  2. 2022A Survey on Retrieval-Augmented Text Generationcited by 157
  3. 2021Case-based Reasoning for Natural Language Queries over Knowledge Basescited by 107
  4. 2023Lift Yourself Up: Retrieval-augmented Text Generation with Self Memorycited by 103
  5. 2023Retrieving Multimodal Information for Augmented Generation: A Surveycited by 84
  6. 2021Tailor: Generating and Perturbing Text with Semantic Controlscited by 67
  7. 2022Multilingual Generative Language Models for Zero-Shot Cross-Lingual Event Argument Extractioncited by 40
  8. 2024VisDoM: Multi-Document QA with Visually Rich Elements Using Multimodal Retrieval-Augmented Generationcited by 40
  9. 2024Goldfish: Vision-Language Understanding of Arbitrarily Long Videoscited by 38
  10. 2021Few-shot Intent Classification and Slot Filling with Retrieved Examplescited by 35
  11. 2021Controllable Semantic Parsing via Retrieval Augmentationcited by 35
  12. 2021AdaTag: Multi-Attribute Value Extraction from Product Profiles with Adaptive Decodingcited by 32
16 more
  1. 2024On the Evaluation of Machine-Generated Reportscited by 23
  2. 2021RetGen: A Joint framework for Retrieval and Grounded Text Generation Modelingcited by 22
  3. 2022Recent Advances in Neural Text Generation: A Task-Agnostic Surveycited by 14
  4. 2024Accelerating Retrieval-Augmented Generationcited by 14
  5. 2022TegTok: Augmenting Text Generation via Task-specific and Open-world Knowledgecited by 9
  6. 2024XL-HeadTags: Leveraging Multimodal Retrieval Augmentation for the Multilingual Generation of News Headlines and Tagscited by 9
  7. 2022Nearest Neighbor Non-autoregressive Text Generationcited by 7
  8. 2021Improving Automated Evaluation of Open Domain Dialog via Diverse Reference Augmentationcited by 6
  9. 2022AutoTemplate: A Simple Recipe for Lexically Constrained Text Generationcited by 6
  10. 2021Data-to-text Generation by Splicing Together Nearest Neighborscited by 4
  11. 2021Automatic Document Sketching: Generating Drafts from Analogous Textscited by 4
  12. 2024Hierarchical Prompt Decision Transformer: Improving Few-Shot Policy Generalization with Global and Adaptive Guidancecited by 3
  13. 2025A Few Words Can Distort Graphs: Knowledge Poisoning Attacks on Graph-based Retrieval-Augmented Generation of Large Language Modelscited by 3
  14. 2021Adversarial Machine Learning in Text Analysis and Generationcited by 2
  15. 2022Sparse Optimization for Unsupervised Extractive Summarization of Long Documents with the Frank-Wolfe Algorithmcited by 0
  16. 2024Action Controlled Paraphrasingcited by 0