# Estimating the Causal Effect of Early ArXiving on Paper Acceptance

arXiv: https://arxiv.org/abs/2306.13891 · HTML: https://mlsanity.com/paper/2306.13891/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 9 of its 43 references that are in the map.
- First posted on arXiv 24 Jun 2023.

## Builds on (most cited first, 9 of 9)

- [RoBERTa: A Robustly Optimized BERT Pretraining Approach](https://mlsanity.com/paper/1907.11692/) (2019)
- [Longformer: The Long-Document Transformer](https://mlsanity.com/paper/2004.05150/) (2020)
- [SPECTER: Document-level Representation Learning using Citation-informed Transformers](https://mlsanity.com/paper/2004.07180/) (2020)
- [Causal Inference in Natural Language Processing: Estimation, Prediction, Interpretation and Beyond](https://mlsanity.com/paper/2109.00725/) (2021)
- [The Semantic Scholar Open Data Platform](https://mlsanity.com/paper/2301.10140/) (2023)
- [Investigating Fairness Disparities in Peer Review: A Language Model Enhanced Approach](https://mlsanity.com/paper/2211.06398/) (2022)
- [Citation Count Analysis for Papers with Preprints](https://mlsanity.com/paper/1805.05238/) (2018)
- [Single versus Double Blind Reviewing at WSDM 2017](https://mlsanity.com/paper/1702.00502/) (2017)
- [Some Reflections on Drawing Causal Inference using Textual Data: Parallels Between Human Subjects and Organized Texts](https://mlsanity.com/paper/2202.00848/) (2022)

## Built on by (most cited first, 4 of 4)

- [AgentReview: Exploring Peer Review Dynamics with LLM Agents](https://mlsanity.com/paper/2406.12708/) (2024)
- [On Behalf of the Stakeholders: Trends in NLP Model Interpretability in the Era of LLMs](https://mlsanity.com/paper/2407.19200/) (2024)
- [Position: AI/ML Influencers Have a Place in the Academic Process](https://mlsanity.com/paper/2401.13782/) (2024)
- [Who Pays for Open Review? Visible Author Reputation and Its Effect on Ratings](https://mlsanity.com/paper/2609.11983/) (2026)

## Abstract (arXiv)

What is the effect of releasing a preprint of a paper before it is submitted for peer review? No randomized controlled trial has been conducted, so we turn to observational data to answer this question. We use data from the ICLR conference (2018--2022) and apply methods from causal inference to estimate the effect of arXiving a paper before the reviewing period (early arXiving) on its acceptance to the conference. Adjusting for confounders such as topic, authors, and quality, we may estimate the causal effect. However, since quality is a challenging construct to estimate, we use the negative outcome control method, using paper citation count as a control variable to debias the quality confounding effect. Our results suggest that early arXiving may have a small effect on a paper's chances of acceptance. However, this effect (when existing) does not differ significantly across different groups of authors, as grouped by author citation count and institute rank. This suggests that early arXiving does not provide an advantage to any particular group.