Analysis of 500k ChatGPT logs shows over one-third of conversations generate fiction, dominated by power users with repetitive and niche patterns.
In: Bouamor H, Pino J, Bali K (eds) Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
4 Pith papers cite this work, alongside 10 external citations. Polarity classification is still indexing.
4
Pith papers citing it
10
external citations · OpenAlex
verdicts
UNVERDICTED 4representative citing papers
Training data for open LLMs is systematically left-leaning, with pre-training corpora containing more political material than post-training data and model stances aligning with data distributions.
Generative AI evaluation must shift from static benchmark scores to measuring sustained improvements in human capabilities within specific deployment contexts.
Survey of Italian adults finds generative AI adoption and capital-enhancing uses stratified by education, age, tech familiarity, and gender, with AI training as key predictor of purposeful engagement.
citing papers explorer
-
AI Fiction in the Wild
Analysis of 500k ChatGPT logs shows over one-third of conversations generate fiction, dominated by power users with repetitive and niche patterns.
-
What Is The Political Content in LLMs' Pre- and Post-Training Data?
Training data for open LLMs is systematically left-leaning, with pre-training corpora containing more political material than post-training data and model stances aligning with data distributions.
-
Benchmarked Yet Not Measured -- Generative AI Should be Evaluated Against Real-World Utility
Generative AI evaluation must shift from static benchmark scores to measuring sustained improvements in human capabilities within specific deployment contexts.
-
Generative AI Practices, Literacy, and Divides: An Empirical Analysis in the Italian Context
Survey of Italian adults finds generative AI adoption and capital-enhancing uses stratified by education, age, tech familiarity, and gender, with AI training as key predictor of purposeful engagement.