1.4k citations · 2.5k across the 47 of their papers we have counts for
6 papers · 1 filter
Consensus Sampling for Safer Generative AI
Adam Tauman Kalai, Yael Tauman Kalai, Or Zamir
Motivated by undetectable risks in generative AI, we study a general robust aggregation problem: how to aggregate several probability distributions to boost safety. We present cons…
The Singapore Consensus on Global AI Safety Research Priorities
Yoshua Bengio, Tegan Maharaj, Luke Ong +84
Rapidly improving AI capabilities and autonomy hold significant promise of transformation, but are also driving vigorous debate on how to ensure that AI is safe, i.e., trustworthy,…
Testing Language Model Agents Safely in the Wild
Silen Naihin, David Atkinson, Marc Green +5
A prerequisite for safe autonomy-in-the-wild is safe testing-in-the-wild. Yet real-world autonomous tests face several unique safety challenges, both due to the possibility of caus…
Supervising Unsupervised Learning
Vikas K. Garg, Adam Kalai
We introduce a framework to leverage knowledge acquired from a repository of (heterogeneous) supervised datasets to new unsupervised datasets. Our perspective avoids the subjectivi…
Textual Features for Programming by Example
Aditya Krishna Menon, Omer Tamuz, Sumit Gulwani +2
In Programming by Example, a system attempts to infer a program from input and output examples, generally by searching for a composition of certain base functions. Performing a nai…
Efficient Learning of Generalized Linear and Single Index Models with Isotonic Regression
Sham Kakade, Adam Tauman Kalai, Varun Kanade +1
Generalized Linear Models (GLMs) and Single Index Models (SIMs) provide powerful generalizations of linear regression, where the target variable is assumed to be a (possibly unknow…