# Text Segmentation as a Supervised Learning Task

arXiv: https://arxiv.org/abs/1803.09337 · HTML: https://mlsanity.com/paper/1803.09337/

## Key facts

- Cited by 76 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 25 Mar 2018.

## Built on by (most cited first, 30 of 76)

- [Improving Unsupervised Dialogue Topic Segmentation with Utterance-Pair Coherence Scoring](https://mlsanity.com/paper/2106.06719/) (2021)
- [Toward Unifying Text Segmentation and Long Document Summarization](https://mlsanity.com/paper/2210.16422/) (2022)
- [TIAGE: A Benchmark for Topic-Shift Aware Dialog Modeling](https://mlsanity.com/paper/2109.04562/) (2021)
- [Transformer over Pre-trained Transformer for Neural Text Segmentation with Enhanced Topic Coherence](https://mlsanity.com/paper/2110.07160/) (2021)
- [Detecting AI-Generated Sentences in Human-AI Collaborative Hybrid Texts: Challenges, Strategies, and Insights](https://mlsanity.com/paper/2403.03506/) (2024)
- [Stance Detection: A Practical Guide to Classifying Political Beliefs in Text](https://mlsanity.com/paper/2305.01723/) (2023)
- [Improving Long Document Topic Segmentation Models With Enhanced Coherence Modeling](https://mlsanity.com/paper/2310.11772/) (2023)
- [Sequence Model with Self-Adaptive Sliding Window for Efficient Spoken Document Segmentation](https://mlsanity.com/paper/2107.09278/) (2021)
- [Reconstructing Context: Evaluating Advanced Chunking Strategies for Retrieval-Augmented Generation](https://mlsanity.com/paper/2504.19754/) (2025)
- [HiChunk: Evaluating and Enhancing Retrieval-Augmented Generation with Hierarchical Chunking](https://mlsanity.com/paper/2509.11552/) (2025)
- [Iterative Hierarchical Attention for Answering Complex Questions over Long Documents](https://mlsanity.com/paper/2106.00200/) (2021)
- [SuperDialseg: A Large-scale Dataset for Supervised Dialogue Segmentation](https://mlsanity.com/paper/2305.08371/) (2023)
- [Learning Constraints and Descriptive Segmentation for Subevent Detection](https://mlsanity.com/paper/2109.06316/) (2021)
- [Enhancing Retrieval Augmented Generation with Hierarchical Text Segmentation Chunking](https://mlsanity.com/paper/2507.09935/) (2025)
- [VT-SSum: A Benchmark Dataset for Video Transcript Segmentation and Summarization](https://mlsanity.com/paper/2106.05606/) (2021)
- [Human Guided Exploitation of Interpretable Attention Patterns in Summarization and Topic Segmentation](https://mlsanity.com/paper/2112.05364/) (2021)
- [MHMS: Multimodal Hierarchical Multimedia Summarization](https://mlsanity.com/paper/2204.03734/) (2022)
- [Structured Summarization: Unified Text Segmentation and Segment Labeling as a Generation Task](https://mlsanity.com/paper/2209.13759/) (2022)
- [Semantics-Consistent Cross-domain Summarization via Optimal Transport Alignment](https://mlsanity.com/paper/2210.04722/) (2022)
- [Recent Trends in Linear Text Segmentation: a Survey](https://mlsanity.com/paper/2411.16613/) (2024)
- [Chunk Twice, Embed Once: A Systematic Study of Segmentation and Representation Trade-offs in Chemistry-Aware Retrieval-Augmented Generation](https://mlsanity.com/paper/2506.17277/) (2025)
- [Membox: Weaving Topic Continuity into Long-Range Memory for LLM Agents](https://mlsanity.com/paper/2601.03785/) (2026)
- [Predicting Above-Sentence Discourse Structure using Distant Supervision from Topic Segmentation](https://mlsanity.com/paper/2112.06196/) (2021)
- [Improving Topic Segmentation by Injecting Discourse Dependencies](https://mlsanity.com/paper/2209.08626/) (2022)
- [Topic Segmentation in the Wild: Towards Segmentation of Semi-structured & Unstructured Chats](https://mlsanity.com/paper/2211.14954/) (2022)
- [Large Language Models for Page Stream Segmentation](https://mlsanity.com/paper/2408.11981/) (2024)
- [DAMASHA: Detecting AI in Mixed Adversarial Texts via Segmentation with Human-interpretable Attribution](https://mlsanity.com/paper/2512.04838/) (2025)
- [Topical Segmentation of Spoken Narratives: A Test Case on Holocaust Survivor Testimonies](https://mlsanity.com/paper/2210.13783/) (2022)
- [Topic Shift Detection in Chinese Dialogues: Corpus and Benchmark](https://mlsanity.com/paper/2305.01195/) (2023)
- [Unsupervised Dialogue Topic Segmentation in Hyperdimensional Space](https://mlsanity.com/paper/2308.10464/) (2023)

## Abstract (arXiv)

Text segmentation, the task of dividing a document into contiguous segments based on its semantic structure, is a longstanding challenge in language understanding. Previous work on text segmentation focused on unsupervised methods such as clustering or graph search, due to the paucity in labeled data. In this work, we formulate text segmentation as a supervised learning problem, and present a large new dataset for text segmentation that is automatically extracted and labeled from Wikipedia. Moreover, we develop a segmentation model based on this dataset and show that it generalizes well to unseen natural text.