Papers by Michael X. Guan

1 papers
Less is More: A Simple yet Effective Token Reduction Method for Efficient Multi-modal LLMs (2025.coling-main)

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Challenge: Recent advances in Multimodal Large Language Models have led to a significant surge in the resource consumption of these models.
Approach: They propose a method to reduce image tokens using visual query data by using CLIP metrics to reduce computational overhead and maintain consistent performance.
Outcome: The proposed method has been extensively tested across 12 datasets and shows a significant reduction in computational overhead while maintaining a consistent level of performance.

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