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Ditch the textual explanations: symbolic outputs like bounding boxes are the secret sauce for boosting multimodal verifier performance.
YOCO++ proves you can halve the KV cache size in LLMs and still beat a standard Transformer, thanks to a clever residual connection trick.
Multimodal models are often blind at birth: a new "Visual Attention Score" reveals they struggle to focus on visual inputs during cold-start, but a simple attention-guided fix can boost performance by 7%.
