---
title: "Who cites Summarizing Opinions: Aspect Extraction Meets…"
description: "87 papers of the Elamur Research library cite «Summarizing Opinions: Aspect Extraction Meets Sentiment Prediction and They Are Both Weakly Supervised»…"
canonical: "https://research.elamur.ai/free/en/papers/angelidis-2018-summarizing-opinions-aspect-extraction-meets/cited-by/"
---
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# Who cites «Summarizing Opinions: Aspect Extraction Meets Sentiment Prediction and They Are Both Weakly Supervised»

87 papers of our library cite it (of the 140,884 whose bibliographies we read) · 4 with a page here, the most cited first · [← the paper](https://md.research.elamur.ai/free/en/papers/angelidis-2018-summarizing-opinions-aspect-extraction-meets/)

1. [**Justifying Recommendations using Distantly-Labeled Reviews and Fine-Grained Aspects**Jianmo Ni, Jiacheng Li, Julian McAuley*2019 · 1,421 citations*](https://md.research.elamur.ai/free/en/papers/ni-2019-justifying-recommendations-distantly-labeled-reviews/)
2. [**Multi-News: A Large-Scale Multi-Document Summarization Dataset and Abstractive Hierarchical Model**Alexander Fabbri, Irene Li, Tianwei She, et al.*2019 · 738 citations*](https://md.research.elamur.ai/free/en/papers/fabbri-2019-multi-news-large-scale-multi/)
3. [**An Interactive Multi-Task Learning Network for End-to-End Aspect-Based Sentiment Analysis**Ruidan He, Wee Sun Lee, Hwee Tou Ng, et al.*2019 · 348 citations*](https://md.research.elamur.ai/free/en/papers/he-2019-interactive-multi-task-learning-network/)
4. [**RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval**Parth Sarthi, Salman Abdullah, Aditi Tuli, et al.*2024 · 191 citations*](https://md.research.elamur.ai/free/en/papers/sarthi-2024-raptor-recursive-abstractive-processing-tree/)

83 more papers of our library cite it; they have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/angelidis-2018-summarizing-opinions-aspect-extraction-meets/) — Summarizing Opinions: Aspect Extraction Meets Sentiment Prediction and They Are Both Weakly Supervised