1 code implementation • ACL 2022 • Saadia Gabriel, Skyler Hallinan, Maarten Sap, Pemi Nguyen, Franziska Roesner, Eunsol Choi, Yejin Choi
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).
1 code implementation • 8 Mar 2024 • Yuhao Wu, Franziska Roesner, Tadayoshi Kohno, Ning Zhang, Umar Iqbal
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.
1 code implementation • 19 Sep 2023 • Umar Iqbal, Tadayoshi Kohno, Franziska Roesner
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.
1 code implementation • 18 Apr 2021 • Saadia Gabriel, Skyler Hallinan, Maarten Sap, Pemi Nguyen, Franziska Roesner, Eunsol Choi, Yejin Choi
We propose Misinfo Reaction Frames (MRF), a pragmatic formalism for modeling how readers might react to a news headline.
4 code implementations • NeurIPS 2019 • Rowan Zellers, Ari Holtzman, Hannah Rashkin, Yonatan Bisk, Ali Farhadi, Franziska Roesner, Yejin Choi
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