565 citations · 756 across the 13 of their papers we have counts for
4 papers · 1 filter
Breaking Feedback Loops in Recommender Systems with Causal Inference
Karl Krauth, Yixin Wang, Michael I. Jordan
Recommender systems play a key role in shaping modern web ecosystems. These systems alternate between (1) making recommendations (2) collecting user responses to these recommendati…
Recommendation Systems with Distribution-Free Reliability Guarantees
Anastasios N. Angelopoulos, Karl Krauth, Stephen Bates +2
When building recommendation systems, we seek to output a helpful set of items to the user. Under the hood, a ranking model predicts which of two candidate items is better, and we…
Modeling Content Creator Incentives on Algorithm-Curated Platforms
Jiri Hron, Karl Krauth, Michael I. Jordan +2
Content creators compete for user attention. Their reach crucially depends on algorithmic choices made by developers on online platforms. To maximize exposure, many creators adapt…
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models
Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao +448
Language models demonstrate both quantitative improvement and new qualitative capabilities with increasing scale. Despite their potentially transformative impact, these new capabil…