Argument Mining
85 papers with code • 1 benchmarks • 6 datasets
Argument Mining is a field of corpus-based discourse analysis that involves the automatic identification of argumentative structures in text.
Source: AMPERSAND: Argument Mining for PERSuAsive oNline Discussions
Benchmarks
These leaderboards are used to track progress in Argument Mining
| Trend | Dataset | Best Model | Paper | Code | Compare |
|---|---|---|---|---|---|
|
x-stance
UKP
DebateSum
Subtasks
Latest papers
ABCD: A Graph Framework to Convert Complex Sentences to a Covering Set of Simple Sentences
serenayj/ABCD-ACL2021
•
•
ACL 2021
On DeSSE, which has a more even balance of complex sentence types, our model achieves higher accuracy on the number of atomic sentences than an encoder-decoder baseline.
ConvoSumm: Conversation Summarization Benchmark and Improved Abstractive Summarization with Argument Mining
Yale-LILY/ConvoSumm
•
•
ACL 2021
While online conversations can cover a vast amount of information in many different formats, abstractive text summarization has primarily focused on modeling solely news articles.
Classifying Argumentative Relations Using Logical Mechanisms and Argumentation Schemes
While argument mining has achieved significant success in classifying argumentative relations between statements (support, attack, and neutral), we have a limited computational understanding of logical mechanisms that constitute those relations.
GrASP: A Library for Extracting and Exploring Human-Interpretable Textual Patterns
Data exploration is an important step of every data science and machine learning project, including those involving textual data.
Multi-Task Attentive Residual Networks for Argument Mining
AGalassi/StructurePrediction18
•
•
We explore the use of residual networks and neural attention for multiple argument mining tasks.
LESA: Linguistic Encapsulation and Semantic Amalgamation Based Generalised Claim Detection from Online Content
LCS2-IIITD/LESA-EACL-2021
•
•
EACL 2021
We resolve the latter issue by annotating a Twitter dataset which aims at providing a testing ground on a large unstructured dataset.
Argument Mining Driven Analysis of Peer-Reviews
Valentyn1997/semi-supervised-text-classification
•
•
Peer reviewing is a central process in modern research and essential for ensuring high quality and reliability of published work.
DebateSum: A large-scale argument mining and summarization dataset
Finally, we present a search engine for this dataset which is utilized extensively by members of the National Speech and Debate Association today.
Aspect-Based Argument Mining
In this work, we are presenting the task of Aspect-Based Argument Mining (ABAM), with the essential subtasks of Aspect Term Extraction (ATE) and Nested Segmentation (NS).
Extracting Implicitly Asserted Propositions in Argumentation
yohanjo/emnlp20_prop_extr
•
•
EMNLP 2020
Our study may inform future research on argument mining and the semantics of these rhetorical devices in argumentation.
