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cs.LG2026
Omissive Bias in Religious Representation: Benchmarking LLM Answers to Everyday Ethical Decision-making
David Wingate, Sheryl Carty, Joshua Coates +13
As large language models become a default source of guidance on personal, moral, and existential questions, it matters whether they draw on the religious frameworks that have histo…
cs.LG2025
Features that Make a Difference: Leveraging Gradients for Improved Dictionary Learning
Jeffrey Olmo, Jared Wilson, Max Forsey +3
Sparse Autoencoders (SAEs) are a promising approach for extracting neural network representations by learning a sparse and overcomplete decomposition of the network's internal acti…