3 citations · 5 across the 9 of their papers we have counts for
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cs.LG2024★ 2 cited
Quantifying Feature Space Universality Across Large Language Models via Sparse Autoencoders
Michael Lan, Philip Torr, Austin Meek +3
The Universality Hypothesis in large language models (LLMs) claims that different models converge towards similar concept representations in their latent spaces. Providing evidence…
cs.AI2024★ 3 cited
The Cognitive Revolution in Interpretability: From Explaining Behavior to Interpreting Representations and Algorithms
Adam Davies, Ashkan Khakzar
Artificial neural networks have long been understood as "black boxes": though we know their computation graphs and learned parameters, the knowledge encoded by these weights and fu…