Argument Mining
83 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 |
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x-stance
UKP
DebateSum
Subtasks
Latest papers
DeepA2: A Modular Framework for Deep Argument Analysis with Pretrained Neural Text2Text Language Models
vamsi995/paraphrase-generator
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*SEM (NAACL) 2022
In this paper, we present and implement a multi-dimensional, modular framework for performing deep argument analysis (DeepA2) using current pre-trained language models (PTLMs).
Key Point Analysis via Contrastive Learning and Extractive Argument Summarization
Key point analysis is the task of extracting a set of concise and high-level statements from a given collection of arguments, representing the gist of these arguments.
Active Learning for Argument Strength Estimation
High-quality arguments are an essential part of decision-making.
Combining Transformers with Natural Language Explanations
Many NLP applications require models to be interpretable.
Tree-Constrained Graph Neural Networks For Argument Mining
hl2exe/tcgnn
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By imposing a series of regularization constraints to the learning problem, we exploit a pooling mechanism that incorporates such notion of fragments within the node soft assignment function that produces the embeddings.
DESYR: Definition and Syntactic Representation Based Claim Detection on the Web
lcs2-iiitd/desyr-cikm-2021
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To demarcate between a claim and a non-claim is arduous for both humans and machines, owing to latent linguistic variance between the two and the inadequacy of extensive definition-based formalization.
KGAP: Knowledge Graph Augmented Political Perspective Detection in News Media
BunsenFeng/news_stance_detection
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Specifically, we construct a political knowledge graph to serve as domain-specific external knowledge.
Spurious Correlations in Cross-Topic Argument Mining
Recent work in cross-topic argument mining attempts to learn models that generalise across topics rather than merely relying on within-topic spurious correlations.
ABCD: A Graph Framework to Convert Complex Sentences to a Covering Set of Simple Sentences
serenayj/ABCD-ACL2021
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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
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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.
