3 papers
cs.LG2026
How Transparent is DiffusionGemma?
Joshua Engels, Callum McDougall, Bilal Chughtai +13
LLM reasoning transparency is a critical affordance for understanding model decisions, mitigating misuse and misalignment, and debugging surprising model behaviors. However, Diffus…
cs.LG2025
Evaluating Sparse Autoencoders for Monosemantic Representation
Moghis Fereidouni, Muhammad Umair Haider, Peizhong Ju +1
A key barrier to interpreting large language models is polysemanticity, where neurons activate for multiple unrelated concepts. Sparse autoencoders (SAEs) have been proposed to mit…
cs.LG2024
Jumping Ahead: Improving Reconstruction Fidelity with JumpReLU Sparse Autoencoders
Senthooran Rajamanoharan, Tom Lieberum, Nicolas Sonnerat +4
Sparse autoencoders (SAEs) are a promising unsupervised approach for identifying causally relevant and interpretable linear features in a language model's (LM) activations. To be u…