Combating misinformation in the age of llms: Opportunities and challenges
Misinformation such as fake news and rumors is a serious threat on information ecosystems
and public trust. The emergence of Large Language Models (LLMs) has great potential to …
and public trust. The emergence of Large Language Models (LLMs) has great potential to …
Can llm-generated misinformation be detected?
The advent of Large Language Models (LLMs) has made a transformative impact. However,
the potential that LLMs such as ChatGPT can be exploited to generate misinformation has …
the potential that LLMs such as ChatGPT can be exploited to generate misinformation has …
Multi-modal misinformation detection: Approaches, challenges and opportunities
S Abdali - arXiv preprint arXiv:2203.13883, 2022 - arxiv.org
As social media platforms are evolving from text-based forums into multi-modal
environments, the nature of misinformation in social media is also changing accordingly …
environments, the nature of misinformation in social media is also changing accordingly …
Zero-and few-shot event detection via prompt-based meta learning
With emerging online topics as a source for numerous new events, detecting unseen/rare
event types presents an elusive challenge for existing event detection methods, where only …
event types presents an elusive challenge for existing event detection methods, where only …
JustiLM: Few-shot Justification Generation for Explainable Fact-Checking of Real-world Claims
F Zeng, W Gao - Transactions of the Association for Computational …, 2024 - direct.mit.edu
Justification is an explanation that supports the veracity assigned to a claim in fact-checking.
However, the task of justification generation has been previously oversimplified as …
However, the task of justification generation has been previously oversimplified as …
Metric-Free Learning Network with Dual Relations Propagation for Few-Shot Aspect Category Sentiment Analysis
Abstract Few-shot Aspect Category Sentiment Analysis (ACSA) is a crucial task for aspect-
based sentiment analysis, which aims to detect sentiment polarity for a given aspect …
based sentiment analysis, which aims to detect sentiment polarity for a given aspect …
Modelling information warfare dynamics to counter propaganda using a nonlinear differential equation with a PINN-based learning approach
R Pandey, M Pandey, AN Nazarov - International Journal of Information …, 2024 - Springer
The widespread dissemination of misinformation and propaganda has become a crucial
issue in societal conversations. This study presents an innovative framework to counter …
issue in societal conversations. This study presents an innovative framework to counter …
T3RD: Test-Time Training for Rumor Detection on Social Media
With the increasing number of news uploaded to the internet daily, rumor detection has
garnered significant attention in recent years. Existing rumor detection methods excel on …
garnered significant attention in recent years. Existing rumor detection methods excel on …
A Domain Adaptive Graph Learning Framework to Early Detection of Emergent Healthcare Misinformation on Social Media
A fundamental issue in healthcare misinformation detection is the lack of timely resources
(eg, medical knowledge, annotated data), making it challenging to accurately detect …
(eg, medical knowledge, annotated data), making it challenging to accurately detect …
Evidence-Driven Retrieval Augmented Response Generation for Online Misinformation
The proliferation of online misinformation has posed significant threats to public interest.
While numerous online users actively participate in the combat against misinformation …
While numerous online users actively participate in the combat against misinformation …