mlsanityData to 7 Oct 2026

An Empirical Study on Neural Keyphrase Generation

arXiv 2009.10229 ↗First posted 22 Sep 2020cs.CLcited by 25

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Abstract (arXiv)

Recent years have seen a flourishing of neural keyphrase generation (KPG) works, including the release of several large-scale datasets and a host of new models to tackle them. Model performance on KPG tasks has increased significantly with evolving deep learning research. However, there lacks a comprehensive comparison among different model designs, and a thorough investigation on related factors that may affect a KPG system's generalization performance. In this empirical study, we aim to fill this gap by providing extensive experimental results and analyzing the most crucial factors impacting the generalizability of KPG models. We hope this study can help clarify some of the uncertainties surrounding the KPG task and facilitate future research on this topic.

Key facts. Cited by 25 papers in the map (data through 7 Oct 2026). First posted on arXiv 22 Sep 2020.

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Citing papers per year: 2021: 6; 2022: 7; 2023: 6; 2024: 4; 2025: 1; 2026: 1.

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  1. 2023A Survey of GPT-3 Family Large Language Models Including ChatGPT and GPT-4cited by 81
  2. 2021Learning Rich Representation of Keyphrases from Textcited by 36
  3. 2021MDERank: A Masked Document Embedding Rank Approach for Unsupervised Keyphrase Extractioncited by 20
  4. 2021Enhancing Taxonomy Completion with Concept Generation via Fusing Relational Representationscited by 19
  5. 2022Retrieval-Augmented Multilingual Keyphrase Generation with Retriever-Generator Iterative Trainingcited by 16
  6. 2021Heterogeneous Graph Neural Networks for Keyphrase Generationcited by 15
  7. 2023From Statistical Methods to Deep Learning, Automatic Keyphrase Prediction: A Surveycited by 14
  8. 2022Applying a Generic Sequence-to-Sequence Model for Simple and Effective Keyphrase Generationcited by 13
  9. 2022Generative Aspect-Based Sentiment Analysis with Contrastive Learning and Expressive Structurecited by 13
  10. 2022Pre-trained Language Models for Keyphrase Generation: A Thorough Empirical Studycited by 13
  11. 2023Rethinking Model Selection and Decoding for Keyphrase Generation with Pre-trained Sequence-to-Sequence Modelscited by 8
  12. 2021Unsupervised Deep Keyphrase Generationcited by 7
13 more
  1. 2021KPDrop: Improving Absent Keyphrase Generationcited by 6
  2. 2022A Large-Scale Dataset for Biomedical Keyphrase Generationcited by 6
  3. 2022General-to-Specific Transfer Labeling for Domain Adaptable Keyphrase Generationcited by 5
  4. 2024EUROPA: A Legal Multilingual Keyphrase Generation Datasetcited by 5
  5. 2023Search-Engine-augmented Dialogue Response Generation with Cheaply Supervised Query Productioncited by 4
  6. 2023SimCKP: Simple Contrastive Learning of Keyphrase Representationscited by 4
  7. 2024Unsupervised Domain Adaptation for Keyphrase Generation using Citation Contextscited by 4
  8. 2024On Leveraging Encoder-only Pre-trained Language Models for Effective Keyphrase Generationcited by 3
  9. 2022ITTC @ TREC 2021 Clinical Trials Trackcited by 1
  10. 2024Self-Compositional Data Augmentation for Scientific Keyphrase Generationcited by 1
  11. 2023Neural Keyphrase Generation: Analysis and Evaluationcited by 0
  12. 2025An Analysis of Datasets, Metrics and Models in Keyphrase Generationcited by 0
  13. 2026Evaluating the Homogeneity of Keyphrase Prediction Modelscited by 0