# Automatic Academic Paper Rating Based on Modularized Hierarchical Convolutional Neural Network

arXiv: https://arxiv.org/abs/1805.03977 · HTML: https://mlsanity.com/paper/1805.03977/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 10 May 2018.

## Built on by (most cited first, 7 of 7)

- [Automated scholarly paper review: Concepts, technologies, and challenges](https://mlsanity.com/paper/2111.07533/) (2021)
- [MultiSChuBERT: Effective Multimodal Fusion for Scholarly Document Quality Prediction](https://mlsanity.com/paper/2308.07971/) (2023)
- [Unveiling the Sentinels: Assessing AI Performance in Cybersecurity Peer Review](https://mlsanity.com/paper/2309.05457/) (2023)
- [Content Significance Distribution of Sub-Text Blocks in Articles and Its Application to Article-Organization Assessment](https://mlsanity.com/paper/2311.01673/) (2023)
- [Navigating Through Paper Flood: Advancing LLM-based Paper Evaluation through Domain-Aware Retrieval and Latent Reasoning](https://mlsanity.com/paper/2508.05129/) (2025)
- [What do writing features tell us about AI papers?](https://mlsanity.com/paper/2107.06310/) (2021)
- [Efficient Attribute Injection for Pretrained Language Models](https://mlsanity.com/paper/2109.07953/) (2021)

## Abstract (arXiv)

As more and more academic papers are being submitted to conferences and journals, evaluating all these papers by professionals is time-consuming and can cause inequality due to the personal factors of the reviewers. In this paper, in order to assist professionals in evaluating academic papers, we propose a novel task: automatic academic paper rating (AAPR), which automatically determine whether to accept academic papers. We build a new dataset for this task and propose a novel modularized hierarchical convolutional neural network to achieve automatic academic paper rating. Evaluation results show that the proposed model outperforms the baselines by a large margin. The dataset and code are available at urlhttps://github.com/lancopku/AAPR