# Multi-Source Pointer Network for Product Title Summarization

arXiv: https://arxiv.org/abs/1808.06885 · HTML: https://mlsanity.com/paper/1808.06885/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Aug 2018.

## Built on by (most cited first, 9 of 9)

- [Abstractive Text Summarization: State of the Art, Challenges, and Improvements](https://mlsanity.com/paper/2409.02413/) (2024)
- [Probing Product Description Generation via Posterior Distillation](https://mlsanity.com/paper/2103.01594/) (2021)
- [User-Inspired Posterior Network for Recommendation Reason Generation](https://mlsanity.com/paper/2102.07919/) (2021)
- [InstructPTS: Instruction-Tuning LLMs for Product Title Summarization](https://mlsanity.com/paper/2310.16361/) (2023)
- [DSGPT: Domain-Specific Generative Pre-Training of Transformers for Text Generation in E-commerce Title and Review Summarization](https://mlsanity.com/paper/2112.08414/) (2021)
- [PK-Chat: Pointer Network Guided Knowledge Driven Generative Dialogue Model](https://mlsanity.com/paper/2304.00592/) (2023)
- [Unsupervised Meta Learning for One Shot Title Compression in Voice Commerce](https://mlsanity.com/paper/2102.10760/) (2021)
- [Generating Rich Product Descriptions for Conversational E-commerce Systems](https://mlsanity.com/paper/2111.15298/) (2021)
- [Enhanced Multi-Tuple Extraction for Alloys: Integrating Pointer Networks and Augmented Attention](https://mlsanity.com/paper/2503.06861/) (2025)

## Abstract (arXiv)

In this paper, we study the product title summarization problem in E-commerce applications for display on mobile devices. Comparing with conventional sentence summarization, product title summarization has some extra and essential constraints. For example, factual errors or loss of the key information are intolerable for E-commerce applications. Therefore, we abstract two more constraints for product title summarization: (i) do not introduce irrelevant information; (ii) retain the key information (e.g., brand name and commodity name). To address these issues, we propose a novel multi-source pointer network by adding a new knowledge encoder for pointer network. The first constraint is handled by pointer mechanism. For the second constraint, we restore the key information by copying words from the knowledge encoder with the help of the soft gating mechanism. For evaluation, we build a large collection of real-world product titles along with human-written short titles. Experimental results demonstrate that our model significantly outperforms the other baselines. Finally, online deployment of our proposed model has yielded a significant business impact, as measured by the click-through rate.