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LVLMs can maintain sharper visual focus during long-form generation by adding a lightweight, learnable memory module that bypasses attention dilution.
ReID models implicitly encode a hierarchy of attributes like BMI and pose, revealing potential biases and vulnerabilities that vary across spectral modalities.
A lightweight 6B model, when harnessed within the GEMS agent framework, leapfrogs state-of-the-art models in multimodal generation, suggesting architectural innovations in agents can compensate for raw parameter count.
