Zhikai Li

最新

• I-ViT: Integer-only Quantization for Efficient Vision Transformer Inference
• RepQ-ViT: Scale Reparameterization for Post-Training Quantization of Vision Transformers
• Patch Similarity Aware Data-Free Quantization for Vision Transformers
• Patch-Wise Mixed-Precision Quantization of Vision Transformer
• MGRQ: Post-Training Quantization For Vision Transformer With Mixed Granularity Reconstruction
• LLM Inference Unveiled: Survey and Roofline Model Insights
• RepQuant: Towards Accurate Post-Training Quantization of Large Transformer Models via Scale Reparameterization
• Enhanced Distribution Alignment for Post-Training Quantization of Diffusion Models
• Qft: Quantized full-parameter tuning of llms with affordable resources
• PSAQ-ViT V2: Towards Accurate and General Data-Free Quantization for Vision Transformers
• BinaryViT: Towards Efficient and Accurate Binary Vision Transformers
• DCIFPN: Deformable cross-scale interaction feature pyramid network for object detection
• Region Probability Map-Guided Fast Wide-Area Multiobject Detection
• Rethinking Prediction Alignment in One-stage Object Detection
• Dual-Discriminator Adversarial Framework for Data-Free Quantization
• Mechanical Particle Filter Based Active Vision System for Fast Wide-Area Multi-Object Detection
• Hardware-Oriented Algorithm for High-Speed Laser Centerline Extraction Based on Hessian Matrix