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Mohamed bin Zayed University of Artificial Intelligence
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Projector-level forgetting in MLLMs can be mitigated, leading to significant performance gains in continual instruction tuning without excessive parameter growth.
LEEVLA reveals that effectively guiding attention to task-critical evidence can dramatically enhance performance in vision-language-action tasks.
