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Found 5 papers, 5 papers with code
Misinfo Reaction Frames: Reasoning about Readers’ Reactions to News Headlines
Even to a simple and short news headline, readers react in a multitude of ways: cognitively (e. g. inferring the writer’s intent), emotionally (e. g. feeling distrust), and behaviorally (e. g. sharing the news with their friends).
SecGPT: An Execution Isolation Architecture for LLM-Based Systems
These LLM apps leverage the de facto natural language-based automated execution paradigm of LLMs: that is, apps and their interactions are defined in natural language, provided access to user data, and allowed to freely interact with each other and the system.
LLM Platform Security: Applying a Systematic Evaluation Framework to OpenAI's ChatGPT Plugins
In this paper, we propose a framework that lays a foundation for LLM platform designers to analyze and improve the security, privacy, and safety of current and future plugin-integrated LLM platforms.
Misinfo Reaction Frames: Reasoning about Readers' Reactions to News Headlines
We propose Misinfo Reaction Frames (MRF), a pragmatic formalism for modeling how readers might react to a news headline.
Defending Against Neural Fake News
We find that best current discriminators can classify neural fake news from real, human-written, news with 73% accuracy, assuming access to a moderate level of training data.
Ranked #2 on
Fake News Detection
on Grover-Mega
