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Found 13 papers, 6 papers with code
What to Fact-Check: Guiding Check-Worthy Information Detection in News Articles through Argumentative Discourse Structure
We discuss the connection between argument structure and check-worthy statements and develop several baseline models for detecting check-worthy statements in the climate change domain.
“Sharks are not the threat humans are”: Argument Component Segmentation in School Student Essays
Argument mining is often addressed by a pipeline method where segmentation of text into argumentative units is conducted first and proceeded by an argument component identification task.
Large Language Models are Few-Shot Training Example Generators: A Case Study in Fallacy Recognition
In this study, we aim to enhance existing models for fallacy recognition by incorporating additional context and by leveraging large language models to generate synthetic data, thus increasing the representation of the infrequent classes.
Multitask Instruction-based Prompting for Fallacy Recognition
To move towards solving the fallacy recognition task, we approach these differences across datasets as multiple tasks and show how instruction-based prompting in a multitask setup based on the T5 model improves the results against approaches built for a specific dataset such as T5, BERT or GPT-3.
AraStance: A Multi-Country and Multi-Domain Dataset of Arabic Stance Detection for Fact Checking
With the continuing spread of misinformation and disinformation online, it is of increasing importance to develop combating mechanisms at scale in the form of automated systems that support multiple languages.
"Sharks are not the threat humans are": Argument Component Segmentation in School Student Essays
Argument mining is often addressed by a pipeline method where segmentation of text into argumentative units is conducted first and proceeded by an argument component identification task.
Fact vs. Opinion: the Role of Argumentation Features in News Classification
A 2018 study led by the Media Insight Project showed that most journalists think that a clearmarking of what is news reporting and what is commentary or opinion (e. g., editorial, op-ed)is essential for gaining public trust.
Machine Generation and Detection of Arabic Manipulated and Fake News
Finally, we develop the first models for detecting manipulated Arabic news and achieve state-of-the-art results on Arabic fake news detection (macro F1=70. 06).
DeSePtion: Dual Sequence Prediction and Adversarial Examples for Improved Fact-Checking
The increased focus on misinformation has spurred development of data and systems for detecting the veracity of a claim as well as retrieving authoritative evidence.
Fine-Tuned Neural Models for Propaganda Detection at the Sentence and Fragment levels
This paper presents the CUNLP submission for the NLP4IF 2019 shared-task on FineGrained Propaganda Detection.
Spider-Jerusalem at SemEval-2019 Task 4: Hyperpartisan News Detection
This paper describes our system for detecting hyperpartisan news articles, which was submitted for the shared task in SemEval 2019 on Hyperpartisan News Detection.
Where is Your Evidence: Improving Fact-checking by Justification Modeling
Fact-checking is a journalistic practice that compares a claim made publicly against trusted sources of facts.
Robust Document Retrieval and Individual Evidence Modeling for Fact Extraction and Verification.
Our team finished 6th out of 24 teams on the leader-board based on the preliminary results with a FEVER score of 49. 06 on the blind test set compared to 27. 45 of the baseline system.
