HeadKV compresses KV cache for autoregressive image generation via head-aware budget allocation, early head-type identification from consistent patterns, and stratified token eviction.
Polaformer: Polarity- aware linear attention for vision transformers
3 Pith papers cite this work. Polarity classification is still indexing.
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VECA learns effective visual representations using core-periphery attention where patches interact exclusively via a resolution-invariant set of learned core embeddings, achieving linear O(N) complexity while maintaining competitive performance.
JetViT uses post-training attention search to hybridize full-attention ViTs with linear and window attention blocks, achieving up to 1.79x throughput gains on high-res images while preserving accuracy on DINOv3 and DepthAnythingV2.
citing papers explorer
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Head-Aware Key-Value Compression for Efficient Autoregressive Image Generation
HeadKV compresses KV cache for autoregressive image generation via head-aware budget allocation, early head-type identification from consistent patterns, and stratified token eviction.
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Elastic Attention Cores for Scalable Vision Transformers
VECA learns effective visual representations using core-periphery attention where patches interact exclusively via a resolution-invariant set of learned core embeddings, achieving linear O(N) complexity while maintaining competitive performance.
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JetViT: Efficient High-Resolution Vision Transformer with Post-Training Attention Search
JetViT uses post-training attention search to hybridize full-attention ViTs with linear and window attention blocks, achieving up to 1.79x throughput gains on high-res images while preserving accuracy on DINOv3 and DepthAnythingV2.