✨Can Visual Input Be Compressed? A Visual Token Compression Benchmark for Large Multimodal Models
📝 Summary:
UniPruneBench is a new benchmark for evaluating visual token pruning in large multimodal models LMMs. It standardizes evaluation across tasks and models, revealing that random pruning is a strong baseline and OCR is most sensitive to pruning. The pruning ratio greatly impacts performance.
🔹 Publication Date: Published on Nov 4
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.02650
• PDF: https://arxiv.org/pdf/2511.02650
• Project Page: https://uniprunebench-lmm.github.io/
• Github: https://github.com/TianfanPeng/VLMUniPruneBench
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For more data science resources:
✓ https://t.iss.one/DataScienceT
#LMMs #VisualCompression #DeepLearning #ComputerVision #AIResearch
📝 Summary:
UniPruneBench is a new benchmark for evaluating visual token pruning in large multimodal models LMMs. It standardizes evaluation across tasks and models, revealing that random pruning is a strong baseline and OCR is most sensitive to pruning. The pruning ratio greatly impacts performance.
🔹 Publication Date: Published on Nov 4
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.02650
• PDF: https://arxiv.org/pdf/2511.02650
• Project Page: https://uniprunebench-lmm.github.io/
• Github: https://github.com/TianfanPeng/VLMUniPruneBench
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#LMMs #VisualCompression #DeepLearning #ComputerVision #AIResearch