# Automatic generation of reviews of scientific papers

arXiv: https://arxiv.org/abs/2010.04147 · HTML: https://mlsanity.com/paper/2010.04147/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Oct 2020.

## Built on by (most cited first, 6 of 6)

- [Do Language Models Know When They're Hallucinating References?](https://mlsanity.com/paper/2305.18248/) (2023)
- [Breaking the Reviewer: Assessing the Vulnerability of Large Language Models in Automated Peer Review Under Textual Adversarial Attacks](https://mlsanity.com/paper/2506.11113/) (2025)
- [Automated Review Generation Method Based on Large Language Models](https://mlsanity.com/paper/2407.20906/) (2024)
- [Controllable Citation Sentence Generation with Language Models](https://mlsanity.com/paper/2211.07066/) (2022)
- [Multi-use LLM Watermarking and the False Detection Problem](https://mlsanity.com/paper/2506.15975/) (2025)
- [Does AI Reviewer See the Full Picture? Attacking and Defending Multimodal Peer Review](https://mlsanity.com/paper/2606.12716/) (2026)

## Abstract (arXiv)

With an ever-increasing number of scientific papers published each year, it becomes more difficult for researchers to explore a field that they are not closely familiar with already. This greatly inhibits the potential for cross-disciplinary research. A traditional introduction into an area may come in the form of a review paper. However, not all areas and sub-areas have a current review. In this paper, we present a method for the automatic generation of a review paper corresponding to a user-defined query. This method consists of two main parts. The first part identifies key papers in the area by their bibliometric parameters, such as a graph of co-citations. The second stage uses a BERT based architecture that we train on existing reviews for extractive summarization of these key papers. We describe the general pipeline of our method and some implementation details and present both automatic and expert evaluations on the PubMed dataset.