Search Results for author:
Found 5 papers, 3 papers with code
DELL: Generating Reactions and Explanations for LLM-Based Misinformation Detection
Large language models are limited by challenges in factuality and hallucinations to be directly employed off-the-shelf for judging the veracity of news articles, where factual accuracy is paramount.
What Does the Bot Say? Opportunities and Risks of Large Language Models in Social Media Bot Detection
Social media bot detection has always been an arms race between advancements in machine learning bot detectors and adversarial bot strategies to evade detection.
GraTO: Graph Neural Network Framework Tackling Over-smoothing with Neural Architecture Search
Further experiments bear out the quality of node representations learned with GraTO and the effectiveness of model architecture.
BIC: Twitter Bot Detection with Text-Graph Interaction and Semantic Consistency
In addition, given the stealing behavior of novel Twitter bots, BIC proposes to model semantic consistency in tweets based on attention weights while using it to augment the decision process.
TwiBot-22: Towards Graph-Based Twitter Bot Detection
Twitter bot detection has become an increasingly important task to combat misinformation, facilitate social media moderation, and preserve the integrity of the online discourse.
