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J++ Lens beats J-Lens on latent variable extraction

J++ Lens beats J-Lens on latent variable extraction

Kola Ayonrinde, Anthropic Fellows, and Jack Lindsey, Anthropic, released the J++ Lens, a drop-in replacement for the J-Lens that filters noisy gradients before the averaged Jacobian, scoring 55% on latent variable extraction versus J-Lens's 36% and R-Lens's 38%.

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