parameter efficiency

Perceiver-VL: Efficient Vision-and-Language Modeling With Iterative Latent Attention WACV 2023 PILLOW: Enhancing Efficient Instruction Fine-tuning via Prompt Matching EMNLP 2023 Pit One Against Many: Leveraging Attention-head Embeddings for Parameter-efficient Multi-head Attention EMNLP 2023 PIVOT: Prompting for Video Continual Learning CVPR 2023 pNLP-Mixer: an Efficient all-MLP Architecture for Language ACL 2023 Prototypical Fine-Tuning: Towards Robust Performance under Varying Data Sizes AAAI 2023 PuMer: Pruning and Merging Tokens for Efficient Vision Language Models ACL 2023 Random Entity Quantization for Parameter-Efficient Compositional Knowledge Graph Representation EMNLP 2023 Read-only Prompt Optimization for Vision-Language Few-shot Learning ICCV 2023 Recipes for Sequential Pre-training of Multilingual Encoder and Seq2Seq Models ACL 2023 Rethinking Mobile Block for Efficient Attention-based Models ICCV 2023 Rethinking Vision Transformers for MobileNet Size and Speed ICCV 2023 Scaling Laws for BERT in Low-Resource Settings ACL 2023 Scaling Vision Transformers to 22 Billion Parameters ICML 2023 Scattering Vision Transformer: Spectral Mixing Matters NeurIPS 2023 SD-Conv: Towards the Parameter-Efficiency of Dynamic Convolution WACV 2023 Simple Hardware-Efficient Long Convolutions for Sequence Modeling ICML 2023 Sparse Universal Transformer EMNLP 2023 Strip-MLP: Efficient Token Interaction for Vision MLP ICCV 2023 SVDiff: Compact Parameter Space for Diffusion Fine-Tuning ICCV 2023 Task-Agnostic Structured Pruning of Speech Representation Models Interspeech 2023 Teacher and Student Models of Offensive Language in Social Media ACL 2023 Topological Convolutional Layers for Deep Learning JMLR 2023 Towards A Unified View of Sparse Feed-Forward Network in Pretraining Large Language Model EMNLP 2023 Towards Being Parameter-Efficient: A Stratified Sparsely Activated Transformer with Dynamic Capacity EMNLP 2023