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Found 20 papers, 11 papers with code
From Argument Search to Argumentative Dialogue: A Topic-independent Approach to Argument Acquisition for Dialogue Systems
Despite the remarkable progress in the field of computational argumentation, dialogue systems concerned with argumentative tasks often rely on structured knowledge about arguments and their relations.
Crowdsourcing on Sensitive Data with Privacy-Preserving Text Rewriting
Most tasks in NLP require labeled data.
Diversity Over Size: On the Effect of Sample and Topic Sizes for Argument Mining Datasets
The task of Argument Mining, that is extracting argumentative sentences for a specific topic from large document sources, is an inherently difficult task for machine learning models and humans alike, as large Argument Mining datasets are rare and recognition of argumentative sentences requires expert knowledge.
Augmented SBERT: Data Augmentation Method for Improving Bi-Encoders for Pairwise Sentence Scoring Tasks
Bi-encoders, on the other hand, require substantial training data and fine-tuning over the target task to achieve competitive performance.
How to Probe Sentence Embeddings in Low-Resource Languages: On Structural Design Choices for Probing Task Evaluation
We then probe embeddings in a multilingual setup with design choices that lie in a 'stable region', as we identify for English, and find that results on English do not transfer to other languages.
Evaluation of Argument Search Approaches in the Context of Argumentative Dialogue Systems
We present an approach to evaluate argument search techniques in view of their use in argumentative dialogue systems by assessing quality aspects of the retrieved arguments.
Aspect-Controlled Neural Argument Generation
In this work, we train a language model for argument generation that can be controlled on a fine-grained level to generate sentence-level arguments for a given topic, stance, and aspect.
Stance Detection Benchmark: How Robust Is Your Stance Detection?
Stance Detection (StD) aims to detect an author's stance towards a certain topic or claim and has become a key component in applications like fake news detection, claim validation, and argument search.
Classification and Clustering of Arguments with Contextualized Word Embeddings
We experiment with two recent contextualized word embedding methods (ELMo and BERT) in the context of open-domain argument search.
Fine-Grained Argument Unit Recognition and Classification
In this work, we argue that the task should be performed on a more fine-grained level of sequence labeling.
Cross-lingual Argumentation Mining: Machine Translation (and a bit of Projection) is All You Need!
Argumentation mining (AM) requires the identification of complex discourse structures and has lately been applied with success monolingually.
ArgumenText: Searching for Arguments in Heterogeneous Sources
Argument mining is a core technology for enabling argument search in large corpora.
Multi-Task Learning for Argumentation Mining in Low-Resource Settings
We investigate whether and where multi-task learning (MTL) can improve performance on NLP problems related to argumentation mining (AM), in particular argument component identification.
Distantly Supervised POS Tagging of Low-Resource Languages under Extreme Data Sparsity: The Case of Hittite
To our knowledge, this is the first attempt of statistical POS tagging of a cuneiform language.
What is the Essence of a Claim? Cross-Domain Claim Identification
Argument mining has become a popular research area in NLP.
Neural End-to-End Learning for Computational Argumentation Mining
Contrary to models that operate on the argument component level, we find that framing AM as dependency parsing leads to subpar performance results.
