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Bypassing synthetic data, MLLMCLIP achieves state-of-the-art compositional accuracy in vision-language tasks through innovative feature-level distillation.
MemDefrag reveals that a simple tracing mechanism can boost knowledge retention in LLMs by over 25% after multiple memory updates.
