20 citations · 21 across the 5 of their papers we have counts for
6 papers
Unsupervised Elicitation of Moral Values from Language Models
Meysam Alizadeh, Fabrizio Gilardi, Zeynab Samei
As AI systems become pervasive, grounding their behavior in human values is critical. Prior work suggests that language models (LMs) exhibit limited inherent moral reasoning, leadi…
Web-Browsing LLMs Can Access Social Media Profiles and Infer User Demographics
Meysam Alizadeh, Fabrizio Gilardi, Zeynab Samei +1
Large language models (LLMs) have traditionally relied on static training data, limiting their knowledge to fixed snapshots. Recent advancements, however, have equipped LLMs with w…
Simple Prompt Injection Attacks Can Leak Personal Data Observed by LLM Agents During Task Execution
Meysam Alizadeh, Zeynab Samei, Daria Stetsenko +1
Previous benchmarks on prompt injection in large language models (LLMs) have primarily focused on generic tasks and attacks, offering limited insights into more complex threats lik…
Exploring Relationships Between Cryptocurrency News Outlets and Influencers' Twitter Activity and Market Prices
Meysam Alizadeh, Yasaman Asgari, Zeynab Samei +7
Academics increasingly acknowledge the predictive power of social media for a wide variety of events and, more specifically, for financial markets. Anecdotal and empirical findings…
Comparing Methods for Creating a National Random Sample of Twitter Users
Meysam Alizadeh, Darya Zare, Zeynab Samei +5
Twitter data has been widely used by researchers across various social and computer science disciplines. A common aim when working with Twitter data is the construction of a random…
Open-Source LLMs for Text Annotation: A Practical Guide for Model Setting and Fine-Tuning
Meysam Alizadeh, Maël Kubli, Zeynab Samei +5
This paper studies the performance of open-source Large Language Models (LLMs) in text classification tasks typical for political science research. By examining tasks like stance,…