Review Generation

11 papers with code • 0 benchmarks • 1 datasets

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Most implemented papers

DP-GAN: Diversity-Promoting Generative Adversarial Network for Generating Informative and Diversified Text

lancopku/DPGAN 5 Feb 2018

Existing text generation methods tend to produce repeated and "boring" expressions.

Unsupervised Opinion Summarization as Copycat-Review Generation

ixlan/CopyCat-abstractive-opinion-summarizer ACL 2020

At test time, when generating summaries, we force the novelty to be minimal, and produce a text reflecting consensus opinions.

Personalized Review Generation By Expanding Phrases and Attending on Aspect-Aware Representations

nijianmo/textExpansion ACL 2018

In this paper, we focus on the problem of building assistive systems that can help users to write reviews.

Judge the Judges: A Large-Scale Evaluation Study of Neural Language Models for Online Review Generation

Crista23/JudgeTheJudges IJCNLP 2019

We conduct a large-scale, systematic study to evaluate the existing evaluation methods for natural language generation in the context of generating online product reviews.

Generating Long and Informative Reviews with Aspect-Aware Coarse-to-Fine Decoding

turboLJY/Coarse-to-Fine-Review-Generation ACL 2019

In this paper, we propose a novel review generation model by characterizing an elaborately designed aspect-aware coarse-to-fine generation process.

Knowledge-Enhanced Personalized Review Generation with Capsule Graph Neural Network

turboLJY/CapsGNN-Review-Generation 4 Oct 2020

First, based on graph capsules, we adaptively learn aspect capsules for inferring the aspect sequence.

ReviewRobot: Explainable Paper Review Generation based on Knowledge Synthesis

EagleW/ReviewRobot INLG (ACL) 2020

To assist human review process, we build a novel ReviewRobot to automatically assign a review score and write comments for multiple categories such as novelty and meaningful comparison.

Multimodal Review Generation with Privacy and Fairness Awareness

reml-ai/mg-prifair COLING 2020

Users express their opinions towards entities (e. g., restaurants) via online reviews which can be in diverse forms such as text, ratings, and images.

Can We Automate Scientific Reviewing?

neulab/ReviewAdvisor 30 Jan 2021

The rapid development of science and technology has been accompanied by an exponential growth in peer-reviewed scientific publications.