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FilmBench reveals that leading video generation models fall short of cinematic standards, scoring significantly lower than on traditional benchmarks, which could redefine how we evaluate AI-generated video quality.
Selected features from sparse autoencoders can causally steer language models toward desired behaviors, like refusal, revealing new avenues for interpretability and control.
