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cs.CV2025
Can Visual Input Be Compressed? A Visual Token Compression Benchmark for Large Multimodal Models
Tianfan Peng, Yuntao Du, Pengzhou Ji +9
Large multimodal models (LMMs) often suffer from severe inference inefficiency due to the large number of visual tokens introduced by image encoders. While recent token compression…
cs.AI2025
MV-Debate: Multi-view Agent Debate with Dynamic Reflection Gating for Multimodal Harmful Content Detection in Social Media
Rui Lu, Jinhe Bi, Yunpu Ma +3
Social media has evolved into a complex multimodal environment where text, images, and other signals interact to shape nuanced meanings, often concealing harmful intent. Identifyin…
cs.CL2025
Domain-Specific Pruning of Large Mixture-of-Experts Models with Few-shot Demonstrations
Zican Dong, Han Peng, Peiyu Liu +4
Mixture-of-Experts (MoE) models achieve a favorable trade-off between performance and inference efficiency by activating only a subset of experts. However, the memory overhead of s…