Can large language models infer causation from correlation?
Causal inference is one of the hallmarks of human intelligence. While the field of CausalNLP
has attracted much interest in the recent years, existing causal inference datasets in NLP …
has attracted much interest in the recent years, existing causal inference datasets in NLP …
Large language models for propaganda span annotation
M Hasanain, F Ahmad, F Alam - arXiv preprint arXiv:2311.09812, 2023 - arxiv.org
The use of propagandistic techniques in online content has increased in recent years aiming
to manipulate online audiences. Fine-grained propaganda detection and extraction of …
to manipulate online audiences. Fine-grained propaganda detection and extraction of …
Argument-based detection and classification of fallacies in political debates
Fallacies are arguments that employ faulty reasoning. Given their persuasive and seemingly
valid nature, fallacious arguments are often used in political debates. Employing these …
valid nature, fallacious arguments are often used in political debates. Employing these …
Modeling appropriate language in argumentation
Online discussion moderators must make ad-hoc decisions about whether the contributions
of discussion participants are appropriate or should be removed to maintain civility. Existing …
of discussion participants are appropriate or should be removed to maintain civility. Existing …
Discourse structures guided fine-grained propaganda identification
Propaganda is a form of deceptive narratives that instigate or mislead the public, usually
with a political purpose. In this paper, we aim to identify propaganda in political news at two …
with a political purpose. In this paper, we aim to identify propaganda in political news at two …
Human-in-the-loop evaluation for early misinformation detection: A case study of COVID-19 treatments
We present a human-in-the-loop evaluation framework for fact-checking novel
misinformation claims and identifying social media messages that support them. Our …
misinformation claims and identifying social media messages that support them. Our …
Detecting argumentative fallacies in the wild: Problems and limitations of large language models
R Ruiz-Dolz, J Lawrence - Proceedings of the 10th …, 2023 - discovery.dundee.ac.uk
Previous work on the automatic identification of fallacies in natural language text has
typically approached the problem in constrained experimental setups that make it difficult to …
typically approached the problem in constrained experimental setups that make it difficult to …
Hierarchical machine learning models can identify stimuli of climate change misinformation on social media
C Rojas, F Algra-Maschio, M Andrejevic… - … Earth & Environment, 2024 - nature.com
Misinformation about climate change poses a substantial threat to societal well-being,
prompting the urgent need for effective mitigation strategies. However, the rapid proliferation …
prompting the urgent need for effective mitigation strategies. However, the rapid proliferation …
Grounding fallacies misrepresenting scientific publications in evidence
Health-related misinformation claims often falsely cite a credible biomedical publication as
evidence, which superficially appears to support the false claim. The publication does not …
evidence, which superficially appears to support the false claim. The publication does not …
Vi-AbSQA: multi-task prompt instruction tuning model for Vietnamese aspect-based sentiment quadruple analysis
TV Dang, D Hao, N Nguyen - ACM Transactions on Asian and Low …, 2024 - dl.acm.org
Aspect-based sentiment analysis (ABSA) has recently received considerable attention within
the Natural Language Processing (NLP) community, especially for complex tasks like triplet …
the Natural Language Processing (NLP) community, especially for complex tasks like triplet …