# GOAL: Towards Benchmarking Few-Shot Sports Game Summarization

arXiv: https://arxiv.org/abs/2207.08635 · HTML: https://mlsanity.com/paper/2207.08635/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 11 of its 23 references that are in the map.
- First posted on arXiv 18 Jul 2022.

## Builds on (most cited first, 11 of 11)

- [Longformer: The Long-Document Transformer](https://mlsanity.com/paper/2004.05150/) (2020)
- [Get To The Point: Summarization with Pointer-Generator Networks](https://mlsanity.com/paper/1704.04368/) (2017)
- [Sentence Centrality Revisited for Unsupervised Summarization](https://mlsanity.com/paper/1906.03508/) (2019)
- [A Survey on Dialogue Summarization: Recent Advances and New Frontiers](https://mlsanity.com/paper/2107.03175/) (2021)
- [A Survey on Cross-Lingual Summarization](https://mlsanity.com/paper/2203.12515/) (2022)
- [Dialogue Discourse-Aware Graph Model and Data Augmentation for Meeting Summarization](https://mlsanity.com/paper/2012.03502/) (2020)
- [ClidSum: A Benchmark Dataset for Cross-Lingual Dialogue Summarization](https://mlsanity.com/paper/2202.05599/) (2022)
- [Knowledge Enhanced Sports Game Summarization](https://mlsanity.com/paper/2111.12535/) (2021)
- [The Cross-lingual Conversation Summarization Challenge](https://mlsanity.com/paper/2205.00379/) (2022)
- [Probing Simile Knowledge from Pre-trained Language Models](https://mlsanity.com/paper/2204.12807/) (2022)
- [SOCCER: An Information-Sparse Discourse State Tracking Collection in the Sports Commentary Domain](https://mlsanity.com/paper/2106.01972/) (2021)

## Built on by (most cited first, 2 of 2)

- [Long-Document Cross-Lingual Summarization](https://mlsanity.com/paper/2212.00586/) (2022)
- [SUMMIR: A Hallucination-Aware Framework for Ranking Sports Insights from LLMs](https://mlsanity.com/paper/2604.04947/) (2026)

## Abstract (arXiv)

Sports game summarization aims to generate sports news based on real-time commentaries. The task has attracted wide research attention but is still under-explored probably due to the lack of corresponding English datasets. Therefore, in this paper, we release GOAL, the first English sports game summarization dataset. Specifically, there are 103 commentary-news pairs in GOAL, where the average lengths of commentaries and news are 2724.9 and 476.3 words, respectively. Moreover, to support the research in the semi-supervised setting, GOAL additionally provides 2,160 unlabeled commentary documents. Based on our GOAL, we build and evaluate several baselines, including extractive and abstractive baselines. The experimental results show the challenges of this task still remain. We hope our work could promote the research of sports game summarization. The dataset has been released at https://github.com/krystalan/goal.