# Exploring Discourse Structures for Argument Impact Classification

arXiv: https://arxiv.org/abs/2106.00976 · HTML: https://mlsanity.com/paper/2106.00976/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- Builds on 17 of its 34 references that are in the map.
- First posted on arXiv 2 Jun 2021.

## Builds on (most cited first, 17 of 17)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Adam: A Method for Stochastic Optimization](https://mlsanity.com/paper/1412.6980/) (2014)
- [RoBERTa: A Robustly Optimized BERT Pretraining Approach](https://mlsanity.com/paper/1907.11692/) (2019)
- [XLNet: Generalized Autoregressive Pretraining for Language Understanding](https://mlsanity.com/paper/1906.08237/) (2019)
- [Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context](https://mlsanity.com/paper/1901.02860/) (2019)
- [Generating Long Sequences with Sparse Transformers](https://mlsanity.com/paper/1904.10509/) (2019)
- [Text Summarization with Pretrained Encoders](https://mlsanity.com/paper/1908.08345/) (2019)
- [Winning Arguments: Interaction Dynamics and Persuasion Strategies in Good-faith Online Discussions](https://mlsanity.com/paper/1602.01103/) (2016)
- [On the Importance of Word and Sentence Representation Learning in Implicit Discourse Relation Classification](https://mlsanity.com/paper/2004.12617/) (2020)
- [Exploring the Role of Prior Beliefs for Argument Persuasion](https://mlsanity.com/paper/1906.11301/) (2019)
- [Discourse-Aware Neural Rewards for Coherent Text Generation](https://mlsanity.com/paper/1805.03766/) (2018)
- [Exploring the Role of Argument Structure in Online Debate Persuasion](https://mlsanity.com/paper/2010.03538/) (2020)
- [Better Document-level Sentiment Analysis from RST Discourse Parsing](https://mlsanity.com/paper/1509.01599/) (2015)
- [The Role of Pragmatic and Discourse Context in Determining Argument Impact](https://mlsanity.com/paper/2004.03034/) (2020)
- [Multilingual Hierarchical Attention Networks for Document Classification](https://mlsanity.com/paper/1707.00896/) (2017)
- [What Changed Your Mind: The Roles of Dynamic Topics and Discourse in Argumentation Process](https://mlsanity.com/paper/2002.03536/) (2020)

## Built on by (most cited first, 7 of 7)

- [ChatGPT Evaluation on Sentence Level Relations: A Focus on Temporal, Causal, and Discourse Relations](https://mlsanity.com/paper/2304.14827/) (2023)
- [DiscoPrompt: Path Prediction Prompt Tuning for Implicit Discourse Relation Recognition](https://mlsanity.com/paper/2305.03973/) (2023)
- [Self-Consistent Narrative Prompts on Abductive Natural Language Inference](https://mlsanity.com/paper/2309.08303/) (2023)
- [Persua: A Visual Interactive System to Enhance the Persuasiveness of Arguments in Online Discussion](https://mlsanity.com/paper/2204.07741/) (2022)
- [Argument Quality Assessment in the Age of Instruction-Following Large Language Models](https://mlsanity.com/paper/2403.16084/) (2024)
- [Strategic Planning and Rationalizing on Trees Make LLMs Better Debaters](https://mlsanity.com/paper/2505.14886/) (2025)
- [Persona Knowledge-Aligned Prompt Tuning Method for Online Debate](https://mlsanity.com/paper/2410.04239/) (2024)

## Abstract (arXiv)

Discourse relations among arguments reveal logical structures of a debate conversation. However, no prior work has explicitly studied how the sequence of discourse relations influence a claim's impact. This paper empirically shows that the discourse relations between two arguments along the context path are essential factors for identifying the persuasive power of an argument. We further propose DisCOC to inject and fuse the sentence-level structural discourse information with contextualized features derived from large-scale language models. Experimental results and extensive analysis show that the attention and gate mechanisms that explicitly model contexts and texts can indeed help the argument impact classification task defined by Durmus et al. (2019), and discourse structures among the context path of the claim to be classified can further boost the performance.