新闻
Beyond One-Size-Fits-All: Sample-Adaptive Strategy Routing for Vision Token Pruning in MLLMs
arXiv cs.AI · 发布于 · 阅读约3分钟
30秒读懂
- 发生了什么
- VIP-Router selects optimal vision token pruning strategies per input in multimodal models, improving inference efficiency without modifying underlying algorithms.
- 为何重要
- Matters for engineers deploying multimodal LLMs where inference cost and latency are critical, especially with variable image complexity.
- 注意
- Method is new and unpublished code; real-world performance gains depend on whether input diversity matches the pruning-sensitive benchmarks used for evaluation.
- llm
- language model
- rag
- inference
- token
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