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cs.AI2024
Inducing Human-like Biases in Moral Reasoning Language Models
Artem Karpov, Seong Hah Cho, Austin Meek +3
In this work, we study the alignment (BrainScore) of large language models (LLMs) fine-tuned for moral reasoning on behavioral data and/or brain data of humans performing the same…
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…