# Attention-based model for predicting question relatedness on Stack Overflow

arXiv: https://arxiv.org/abs/2103.10763 · HTML: https://mlsanity.com/paper/2103.10763/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 13 of its 36 references that are in the map.
- First posted on arXiv 19 Mar 2021.

## Builds on (most cited first, 13 of 13)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [Adam: A Method for Stochastic Optimization](https://mlsanity.com/paper/1412.6980/) (2014)
- [Densely Connected Convolutional Networks](https://mlsanity.com/paper/1608.06993/) (2016)
- [Neural Machine Translation by Jointly Learning to Align and Translate](https://mlsanity.com/paper/1409.0473/) (2014)
- [Distributed Representations of Words and Phrases and their Compositionality](https://mlsanity.com/paper/1310.4546/) (2013)
- [A Convolutional Attention Network for Extreme Summarization of Source Code](https://mlsanity.com/paper/1602.03001/) (2016)
- [Natural Language Inference by Tree-Based Convolution and Heuristic Matching](https://mlsanity.com/paper/1512.08422/) (2015)
- [Simple and Effective Text Matching with Richer Alignment Features](https://mlsanity.com/paper/1908.00300/) (2019)
- [Semantic Sentence Matching with Densely-connected Recurrent and Co-attentive Information](https://mlsanity.com/paper/1805.11360/) (2018)
- [Neural Network Models for Paraphrase Identification, Semantic Textual Similarity, Natural Language Inference, and Question Answering](https://mlsanity.com/paper/1806.04330/) (2018)
- [Easy over Hard: A Case Study on Deep Learning](https://mlsanity.com/paper/1703.00133/) (2017)
- [Question Relatedness on Stack Overflow: The Task, Dataset, and Corpus-inspired Models](https://mlsanity.com/paper/1905.01966/) (2019)

## Built on by (most cited first, 3 of 3)

- [Feature Engineering in Learning-to-Rank for Community Question Answering Task](https://mlsanity.com/paper/2309.07610/) (2023)
- [StackRAG Agent: Improving Developer Answers with Retrieval-Augmented Generation](https://mlsanity.com/paper/2406.13840/) (2024)
- [Beyond Static: Related Questions Retrieval Through Conversations in Community Question Answering](https://mlsanity.com/paper/2604.22759/) (2026)

## Abstract (arXiv)

Stack Overflow is one of the most popular Programming Community-based Question Answering (PCQA) websites that has attracted more and more users in recent years. When users raise or inquire questions in Stack Overflow, providing related questions can help them solve problems. Although there are many approaches based on deep learning that can automatically predict the relatedness between questions, those approaches are limited since interaction information between two questions may be lost. In this paper, we adopt the deep learning technique, propose an Attention-based Sentence pair Interaction Model (ASIM) to predict the relatedness between questions on Stack Overflow automatically. We adopt the attention mechanism to capture the semantic interaction information between the questions. Besides, we have pre-trained and released word embeddings specific to the software engineering domain for this task, which may also help other related tasks. The experiment results demonstrate that ASIM has made significant improvement over the baseline approaches in Precision, Recall, and Micro-F1 evaluation metrics, achieving state-of-the-art performance in this task. Our model also performs well in the duplicate question detection task of AskUbuntu, which is a similar but different task, proving its generalization and robustness.