LanSE: using sparse encoders to evaluate multimodal model outputs
xuanalogue · x · 2026-10-26
Yiming Tang of Tangible Research introduces LanSE (Language-Grounded Sparse Encoders), a new research direction. Unlike most interpretability work, the team applies sparse autoencoders to multimodal foundation models not to explain internal concepts, but to evaluate generated content — using language-grounded sparse features to analyze what a model produces. Paper at the original link.
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