4 citations · 6 across the 3 of their papers we have counts for
3 papers
Interpreting Language Model Hidden States at Scale
Jordan Pettyjohn, Mansi Sakarvadia, Nathaniel Hudson +3
Lens methods interpret large language models (LLMs) by mapping intermediate activations to the output vocabulary, revealing how next-token predictions develop through the network.…
On Logical Extrapolation for Mazes with Recurrent and Implicit Networks
Brandon Knutson, Amandin Chyba Rabeendran, Michael Ivanitskiy +4
Recent work suggests that certain neural network architectures -- particularly recurrent neural networks (RNNs) and implicit neural networks (INNs) -- are capable of logical extrap…
Operator Splitting for Learning to Predict Equilibria in Convex Games
Daniel McKenzie, Howard Heaton, Qiuwei Li +3
Systems of competing agents can often be modeled as games. Assuming rationality, the most likely outcomes are given by an equilibrium (e.g. a Nash equilibrium). In many practical s…