# LPAttack: A Feasible Annotation Scheme for Capturing Logic Pattern of Attacks in Arguments

arXiv: https://arxiv.org/abs/2204.01512 · HTML: https://mlsanity.com/paper/2204.01512/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 14 of its 48 references that are in the map.
- First posted on arXiv 4 Apr 2022.

## Builds on (most cited first, 14 of 14)

- [ExplaGraphs: An Explanation Graph Generation Task for Structured Commonsense Reasoning](https://mlsanity.com/paper/2104.07644/) (2021)
- [The Argument Reasoning Comprehension Task: Identification and Reconstruction of Implicit Warrants](https://mlsanity.com/paper/1708.01425/) (2017)
- [Argument Generation with Retrieval, Planning, and Realization](https://mlsanity.com/paper/1906.03717/) (2019)
- [Argument Mining with Structured SVMs and RNNs](https://mlsanity.com/paper/1704.06869/) (2017)
- [Neural Argument Generation Augmented with Externally Retrieved Evidence](https://mlsanity.com/paper/1805.10254/) (2018)
- [Argument Undermining: Counter-Argument Generation by Attacking Weak Premises](https://mlsanity.com/paper/2105.11752/) (2021)
- [Classifying Argumentative Relations Using Logical Mechanisms and Argumentation Schemes](https://mlsanity.com/paper/2105.07571/) (2021)
- [Detecting Attackable Sentences in Arguments](https://mlsanity.com/paper/2010.02660/) (2020)
- [Implicit Knowledge in Argumentative Texts: An Annotated Corpus](https://mlsanity.com/paper/1912.10161/) (2019)
- [Knowledge-Enhanced Evidence Retrieval for Counterargument Generation](https://mlsanity.com/paper/2109.09057/) (2021)
- [Corruption Is Not All Bad: Incorporating Discourse Structure into Pre-training via Corruption for Essay Scoring](https://mlsanity.com/paper/2010.06137/) (2020)
- [TYPIC: A Corpus of Template-Based Diagnostic Comments on Argumentation](https://mlsanity.com/paper/2201.06674/) (2022)
- [Riposte! A Large Corpus of Counter-Arguments](https://mlsanity.com/paper/1910.03246/) (2019)
- [CO-NNECT: A Framework for Revealing Commonsense Knowledge Paths as Explicitations of Implicit Knowledge in Texts](https://mlsanity.com/paper/2105.03157/) (2021)

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

- [Teach Me How to Improve My Argumentation Skills: A Survey on Feedback in Argumentation](https://mlsanity.com/paper/2307.15341/) (2023)
- [From Words to Wisdom: Discourse Annotation and Baseline Models for Student Dialogue Understanding](https://mlsanity.com/paper/2511.20547/) (2025)

## Abstract (arXiv)

In argumentative discourse, persuasion is often achieved by refuting or attacking others arguments. Attacking is not always straightforward and often comprise complex rhetorical moves such that arguers might agree with a logic of an argument while attacking another logic. Moreover, arguer might neither deny nor agree with any logics of an argument, instead ignore them and attack the main stance of the argument by providing new logics and presupposing that the new logics have more value or importance than the logics present in the attacked argument. However, no existing studies in the computational argumentation capture such complex rhetorical moves in attacks or the presuppositions or value judgements in them. In order to address this gap, we introduce LPAttack, a novel annotation scheme that captures the common modes and complex rhetorical moves in attacks along with the implicit presuppositions and value judgements in them. Our annotation study shows moderate inter-annotator agreement, indicating that human annotation for the proposed scheme is feasible. We publicly release our annotated corpus and the annotation guidelines.