558 citations · 3.6k across the 65 of their papers we have counts for
11 papers · 1 filter
Discovering Latent Knowledge in Language Models Without Supervision
Collin Burns, Haotian Ye, Dan Klein +1
Existing techniques for training language models can be misaligned with the truth: if we train models with imitation learning, they may reproduce errors that humans make; if we tra…
Interpretability in the Wild: a Circuit for Indirect Object Identification in GPT-2 small
Kevin Wang, Alexandre Variengien, Arthur Conmy +2
Research in mechanistic interpretability seeks to explain behaviors of machine learning models in terms of their internal components. However, most previous work either focuses on…
How Would The Viewer Feel? Estimating Wellbeing From Video Scenarios
Mantas Mazeika, Eric Tang, Andy Zou +6
In recent years, deep neural networks have demonstrated increasingly strong abilities to recognize objects and activities in videos. However, as video understanding becomes widely…
Forecasting Future World Events with Neural Networks
Andy Zou, Tristan Xiao, Ryan Jia +7
Forecasting future world events is a challenging but valuable task. Forecasts of climate, geopolitical conflict, pandemics and economic indicators help shape policy and decision ma…
Auditing Visualizations: Transparency Methods Struggle to Detect Anomalous Behavior
Jean-Stanislas Denain, Jacob Steinhardt
Model visualizations provide information that outputs alone might miss. But can we trust that model visualizations reflect model behavior? For instance, can they diagnose abnormal…
Supply-Side Equilibria in Recommender Systems
Meena Jagadeesan, Nikhil Garg, Jacob Steinhardt
Algorithmic recommender systems such as Spotify and Netflix affect not only consumer behavior but also producer incentives. Producers seek to create content that will be shown by t…