108 citations · 301 across the 20 of their papers we have counts for
5 papers · 1 filter
Can Language Models Recognize Convincing Arguments?
Paula Rescala, Manoel Horta Ribeiro, Tiancheng Hu +1
The capabilities of large language models (LLMs) have raised concerns about their potential to create and propagate convincing narratives. Here, we study their performance in detec…
Prevalence and prevention of large language model use in crowd work
Veniamin Veselovsky, Manoel Horta Ribeiro, Philip Cozzolino +3
We show that the use of large language models (LLMs) is prevalent among crowd workers, and that targeted mitigation strategies can significantly reduce, but not eliminate, LLM use.…
ACTI at EVALITA 2023: Overview of the Conspiracy Theory Identification Task
Giuseppe Russo, Niklas Stoehr, Manoel Horta Ribeiro
Conspiracy Theory Identication task is a new shared task proposed for the first time at the Evalita 2023. The ACTI challenge, based exclusively on comments published on conspirator…
Artificial Artificial Artificial Intelligence: Crowd Workers Widely Use Large Language Models for Text Production Tasks
Veniamin Veselovsky, Manoel Horta Ribeiro, Robert West
Large language models (LLMs) are remarkable data annotators. They can be used to generate high-fidelity supervised training data, as well as survey and experimental data. With the…
Generating Faithful Synthetic Data with Large Language Models: A Case Study in Computational Social Science
Veniamin Veselovsky, Manoel Horta Ribeiro, Akhil Arora +3
Large Language Models (LLMs) have democratized synthetic data generation, which in turn has the potential to simplify and broaden a wide gamut of NLP tasks. Here, we tackle a perva…