CIVIC: End-to-End Sequence Compactness for Efficient Vision-Language Models
📰 ArXiv cs.AI
Learn how CIVIC optimizes vision-language models by compacting sequences for efficient processing, improving performance without sacrificing accuracy
Action Steps
- Implement CIVIC to compact visual tokens in vision-language models
- Evaluate the impact of CIVIC on model performance and efficiency
- Compare the results with existing token reduction methods
- Fine-tune CIVIC for specific use cases to optimize performance
- Integrate CIVIC with other optimization techniques for enhanced efficiency
Who Needs to Know This
Computer vision and natural language processing teams can benefit from CIVIC to improve the efficiency of their vision-language models, reducing memory and latency bottlenecks
Key Insight
💡 CIVIC overcomes memory and latency bottlenecks in vision-language models by compacting sequences without sacrificing accuracy
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🚀 CIVIC: Efficient vision-language models through end-to-end sequence compactness! 💻
Key Takeaways
Learn how CIVIC optimizes vision-language models by compacting sequences for efficient processing, improving performance without sacrificing accuracy
Full Article
Title: CIVIC: End-to-End Sequence Compactness for Efficient Vision-Language Models
Abstract:
arXiv:2605.28115v1 Announce Type: new Abstract: Vision-Language Models (VLMs) face severe memory and latency bottlenecks due to high-resolution visual tokens. While current token reduction methods theoretically save FLOPs, post-hoc pruning introduces structural overhead, failing to yield proportional wall-clock acceleration. However, enforcing a contiguous compact pathway risks geometric disorientation and loss of fine-grained localization. To overcome these barriers, this paper introduces CIVIC
Abstract:
arXiv:2605.28115v1 Announce Type: new Abstract: Vision-Language Models (VLMs) face severe memory and latency bottlenecks due to high-resolution visual tokens. While current token reduction methods theoretically save FLOPs, post-hoc pruning introduces structural overhead, failing to yield proportional wall-clock acceleration. However, enforcing a contiguous compact pathway risks geometric disorientation and loss of fine-grained localization. To overcome these barriers, this paper introduces CIVIC
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