2 papers
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.HC2024
Confidence-weighted integration of human and machine judgments for superior decision-making
Felipe Yáñez, Xiaoliang Luo, Omar Valerio Minero +1
Large language models (LLMs) can surpass humans in certain forecasting tasks. What role does this leave for humans in the overall decision process? One possibility is that humans,…