20 citations · 23 across the 5 of their papers we have counts for
5 papers
Measuring What Matters: Synthetic Benchmarks for Concept Bottleneck Models
Julian Skirzynski, Harry Cheon, Shreyas Kadekodi +2
Concept bottleneck models predict outcomes from high-level concepts detected in inputs. Although concepts provide a simple way to reap benefits from interpretability, very few data…
Quantifying Cognitive Bias Induction in LLM-Generated Content
Abeer Alessa, Param Somane, Akshaya Lakshminarasimhan +3
Large language models (LLMs) are integrated into applications like shopping reviews, summarization, or medical diagnosis support, where their use affects human decisions. We invest…
Boosting human decision-making with AI-generated decision aids
Frederic Becker, Julian Skirzyński, Bas van Opheusden +1
Human decision-making is plagued by many systematic errors. Many of these errors can be avoided by providing decision aids that guide decision-makers to attend to the important inf…
Automatic Discovery and Description of Human Planning Strategies
Julian Skirzynski, Yash Raj Jain, Falk Lieder
Scientific discovery concerns finding patterns in data and creating insightful hypotheses that explain these patterns. Traditionally, this process required human ingenuity, but wit…
Automatic Discovery of Interpretable Planning Strategies
Julian Skirzyński, Frederic Becker, Falk Lieder
When making decisions, people often overlook critical information or are overly swayed by irrelevant information. A common approach to mitigate these biases is to provide decision-…