# SciDTB: Discourse Dependency TreeBank for Scientific Abstracts

arXiv: https://arxiv.org/abs/1806.03653 · HTML: https://mlsanity.com/paper/1806.03653/

## Key facts

- Cited by 24 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 10 Jun 2018.

## Built on by (most cited first, 24 of 24)

- [Why Can't Discourse Parsing Generalize? A Thorough Investigation of the Impact of Data Diversity](https://mlsanity.com/paper/2302.06488/) (2023)
- [eRST: A Signaled Graph Theory of Discourse Relations and Organization](https://mlsanity.com/paper/2403.13560/) (2024)
- [Enhanced Speaker-aware Multi-party Multi-turn Dialogue Comprehension](https://mlsanity.com/paper/2109.04066/) (2021)
- [The Nature of NLP: Analyzing Contributions in NLP Papers](https://mlsanity.com/paper/2409.19505/) (2024)
- [Unifying Discourse Resources with Dependency Framework](https://mlsanity.com/paper/2101.00167/) (2021)
- [Towards Unification of Discourse Annotation Frameworks](https://mlsanity.com/paper/2204.07781/) (2022)
- [Quality and Efficiency of Manual Annotation: Pre-annotation Bias](https://mlsanity.com/paper/2306.09307/) (2023)
- [Multi-tasking Dialogue Comprehension with Discourse Parsing](https://mlsanity.com/paper/2110.03269/) (2021)
- [Improving Topic Segmentation by Injecting Discourse Dependencies](https://mlsanity.com/paper/2209.08626/) (2022)
- [Full-Text Argumentation Mining on Scientific Publications](https://mlsanity.com/paper/2210.13084/) (2022)
- [Improve Discourse Dependency Parsing with Contextualized Representations](https://mlsanity.com/paper/2205.02090/) (2022)
- [DeDisCo at the DISRPT 2025 Shared Task: A System for Discourse Relation Classification](https://mlsanity.com/paper/2509.11498/) (2025)
- [On the Role of Context for Discourse Relation Classification in Scientific Writing](https://mlsanity.com/paper/2510.26354/) (2025)
- [ClaimFlow: Tracing the Evolution of Scientific Claims in NLP](https://mlsanity.com/paper/2603.16073/) (2026)
- [Biaffine Discourse Dependency Parsing](https://mlsanity.com/paper/2201.04450/) (2022)
- [DMON: A Simple yet Effective Approach for Argument Structure Learning](https://mlsanity.com/paper/2405.01216/) (2024)
- [A Novel Dependency Framework for Enhancing Discourse Data Analysis](https://mlsanity.com/paper/2407.12473/) (2024)
- [Dependency Parsing is More Parameter-Efficient with Normalization](https://mlsanity.com/paper/2505.20215/) (2025)
- [CLaC at DISRPT 2025: Hierarchical Adapters for Cross-Framework Multi-lingual Discourse Relation Classification](https://mlsanity.com/paper/2509.16903/) (2025)
- [Improving Zero-shot Sentence Decontextualisation with Content Selection and Planning](https://mlsanity.com/paper/2509.17921/) (2025)
- [LLMs Underperform Graph-Based Parsers on Supervised Relation Extraction for Complex Graphs](https://mlsanity.com/paper/2604.08752/) (2026)
- [DiscoExplorer: An Open Interface for the Study of Multilingual Discourse Relations](https://mlsanity.com/paper/2605.15304/) (2026)
- [Crossing the Validation Crisis: Cross-Validation Reduces Benchmarking Variance Surprisingly Well](https://mlsanity.com/paper/2606.12552/) (2026)
- [MUSE: A Full-Text Cross-Domain Knowledge Base of Scientific Problems, Solutions, and Rationales](https://mlsanity.com/paper/2608.10974/) (2026)

## Abstract (arXiv)

Annotation corpus for discourse relations benefits NLP tasks such as machine translation and question answering. In this paper, we present SciDTB, a domain-specific discourse treebank annotated on scientific articles. Different from widely-used RST-DT and PDTB, SciDTB uses dependency trees to represent discourse structure, which is flexible and simplified to some extent but do not sacrifice structural integrity. We discuss the labeling framework, annotation workflow and some statistics about SciDTB. Furthermore, our treebank is made as a benchmark for evaluating discourse dependency parsers, on which we provide several baselines as fundamental work.