--- title: "Who cites Abstractive Summarization of Product Reviews…" description: "71 papers of the Elamur Research library cite «Abstractive Summarization of Product Reviews Using Discourse Structure», found in their bibliographies…" canonical: "https://research.elamur.ai/free/en/papers/gerani-2014-abstractive-summarization-product-reviews-discourse/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/gerani-2014-abstractive-summarization-product-reviews-discourse/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Abstractive Summarization of Product Reviews…](https://md.research.elamur.ai/free/en/papers/gerani-2014-abstractive-summarization-product-reviews-discourse/) / cited by # Who cites «Abstractive Summarization of Product Reviews Using Discourse Structure» 71 papers of our library cite it (of the 140,884 whose bibliographies we read) · 16 with a page here, the most cited first · [← the paper](https://md.research.elamur.ai/free/en/papers/gerani-2014-abstractive-summarization-product-reviews-discourse/) 1. [**Toward Abstractive Summarization Using Semantic Representations**Fei Liu, Jeffrey Flanigan, Sam Thomson, et al.*2015 · 337 citations*](https://md.research.elamur.ai/free/en/papers/liu-2015-abstractive-summarization-semantic-representations/) 2. [**Multi-Reward Reinforced Summarization with Saliency and Entailment**Ramakanth Pasunuru, Mohit Bansal*2018 · 252 citations*](https://md.research.elamur.ai/free/en/papers/pasunuru-2018-multi-reward-reinforced-summarization-saliency/) 3. [**Better Document-level Sentiment Analysis from RST Discourse Parsing**Parminder Bhatia, Yangfeng Ji, Jacob Eisenstein*2015 · 235 citations*](https://md.research.elamur.ai/free/en/papers/bhatia-2015-better-document-level-sentiment-analysis/) 4. [**Abstract Meaning Representation for Multi-Document Summarization**Kexin Liao, Logan Lebanoff, Fei Liu*2018 · 166 citations*](https://md.research.elamur.ai/free/en/papers/liao-2018-abstract-meaning-representation-multi-document/) 5. [**Adversarial Connective-exploiting Networks for Implicit Discourse Relation Classification**Lianhui Qin, Zhisong Zhang, Hai Zhao, et al.*2017 · 144 citations*](https://md.research.elamur.ai/free/en/papers/qin-2017-adversarial-connective-exploiting-networks-implicit/) 6. [**SciDTB: Discourse Dependency TreeBank for Scientific Abstracts**An Yang, Sujian Li*2018 · 83 citations*](https://md.research.elamur.ai/free/en/papers/yang-2018-scidtb-discourse-dependency-treebank-scientific/) 7. [**Employing the Correspondence of Relations and Connectives to Identify Implicit Discourse Relations via Label Embeddings**Linh The Nguyen, Linh Van Ngo, Khoat Than, et al.*2019 · 52 citations*](https://md.research.elamur.ai/free/en/papers/nguyen-2019-employing-correspondence-relations-connectives-identify/) 8. [**Implicit Discourse Relation Recognition using Neural Tensor Network with Interactive Attention and Sparse Learning**Fengyu Guo, Ruifang He, Di Jin, et al.*2018 · 49 citations*](https://md.research.elamur.ai/free/en/papers/guo-2018-implicit-discourse-relation-recognition-neural/) 9. [**A Regularization Approach for Incorporating Event Knowledge and Coreference Relations into Neural Discourse Parsing**Zeyu Dai, Ruihong Huang*2019 · 46 citations*](https://md.research.elamur.ai/free/en/papers/dai-2019-regularization-approach-incorporating-event-knowledge/) 10. [**TransS-Driven Joint Learning Architecture for Implicit Discourse Relation Recognition**Ruifang He, Jian Wang, Fengyu Guo, et al.*2020 · 41 citations*](https://md.research.elamur.ai/free/en/papers/he-2020-transs-driven-joint-learning-architecture/) 11. [**MEGA RST Discourse Treebanks with Structure and Nuclearity from Scalable Distant Sentiment Supervision**Patrick Huber, Giuseppe Carenini*2020 · 35 citations*](https://md.research.elamur.ai/free/en/papers/huber-2020-mega-rst-discourse-treebanks-structure/) 12. [**Coreference for Discourse Parsing: A Neural Approach**Grigorii Guz, Giuseppe Carenini*2020 · 31 citations*](https://md.research.elamur.ai/free/en/papers/guz-2020-coreference-discourse-parsing-neural-approach/) 13. [**discopy: A Neural System for Shallow Discourse Parsing**René Knaebel*2021 · 23 citations*](https://md.research.elamur.ai/free/en/papers/knaebel-2021-discopy-neural-system-shallow-discourse/) 14. [**Discourse Analysis via Questions and Answers: Parsing Dependency Structures of Questions Under Discussion**Wei-Jen Ko, Yating Wu, Cutter Dalton, et al.*2023 · 21 citations*](https://md.research.elamur.ai/free/en/papers/ko-2023-discourse-analysis-questions-answers-parsing/) 15. [**Unleashing the Power of Neural Discourse Parsers - A Context and Structure Aware Approach Using Large Scale Pretraining**Grigorii Guz, Patrick Huber, Giuseppe Carenini*2020 · 19 citations*](https://md.research.elamur.ai/free/en/papers/guz-2020-unleashing-power-neural-discourse-parsers/) 16. [**Acquiring Annotated Data with Cross-lingual Explicitation for Implicit Discourse Relation Classification**Wei Shi, Frances Yung, Vera Demberg*2019 · 11 citations*](https://md.research.elamur.ai/free/en/papers/shi-2019-acquiring-annotated-data-cross-lingual/) 55 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/gerani-2014-abstractive-summarization-product-reviews-discourse/) — Abstractive Summarization of Product Reviews Using Discourse Structure