6 papers
Crowding Out The Noise: Algorithmic Collective Action Under Differential Privacy
Rushabh Solanki, Meghana Bhange, Ulrich Aïvodji +1
The integration of AI into daily life has generated considerable attention and excitement, while also raising concerns about automating algorithmic harms and re-entrenching existin…
Conscious Data Contribution via Community-Driven Chain-of-Thought Distillation
Lena Libon, Meghana Bhange, Rushabh Solanki +2
The current era of AI development places a heavy emphasis on training large models on increasingly scaled-up datasets. This paradigm has catalyzed entirely new product categories,…
Active Slice Discovery in Large Language Models
Minhui Zhang, Prahar Ijner, Yoav Wald +1
Large Language Models (LLMs) often exhibit systematic errors on specific subsets of data, known as error slices. For instance, a slice can correspond to a certain demographic, wher…
Say It Another Way: Auditing LLMs with a User-Grounded Automated Paraphrasing Framework
Cléa Chataigner, Rebecca Ma, Prakhar Ganesh +4
Large language models (LLMs) are highly sensitive to subtle changes in prompt phrasing, posing challenges for reliable auditing. Prior methods often apply unconstrained prompt para…
Show, Don't Tell: Uncovering Implicit Character Portrayal using LLMs
Brandon Jaipersaud, Zining Zhu, Frank Rudzicz +1
Tools for analyzing character portrayal in fiction are valuable for writers and literary scholars in developing and interpreting compelling stories. Existing tools, such as visuali…
Promoting User Data Autonomy During the Dissolution of a Monopolistic Firm
Rushabh Solanki, Elliot Creager
The deployment of AI in consumer products is currently focused on the use of so-called foundation models, large neural networks pre-trained on massive corpora of digital records. T…