1 citations · 2 across the 5 of their papers we have counts for
5 papers
Do Sparse Autoencoders Generalize? A Case Study of Answerability
Lovis Heindrich, Philip Torr, Fazl Barez +1
Sparse autoencoders (SAEs) have emerged as a promising approach in language model interpretability, offering unsupervised extraction of sparse features. For interpretability method…
Discovering the curriculum with AI: A proof-of-concept demonstration with an intelligent tutoring system for teaching project selection
Lovis Heindrich, Falk Lieder
The decisions of individuals and organizations are often suboptimal because fully rational decision-making is too demanding in the real world. Recent work suggests that some errors…
Training Dynamics of Contextual N-Grams in Language Models
Lucia Quirke, Lovis Heindrich, Wes Gurnee +1
Prior work has shown the existence of contextual neurons in language models, including a neuron that activates on German text. We show that this neuron exists within a broader cont…
An intelligent tutor for planning in large partially observable environments
Lovis Heindrich, Saksham Consul, Falk Lieder
AI can not only outperform people in many planning tasks, but it can also teach them how to plan better. A recent and promising approach to improving human decision-making is to cr…
Improving Human Decision-Making by Discovering Efficient Strategies for Hierarchical Planning
Saksham Consul, Lovis Heindrich, Jugoslav Stojcheski +1
To make good decisions in the real world people need efficient planning strategies because their computational resources are limited. Knowing which planning strategies would work b…