Summary of Mopd: Mixture-of-prompts Distillation For Vision-language Models, by Yang Chen et al.
MoPD: Mixture-of-Prompts Distillation for Vision-Language Modelsby Yang Chen, Shuai Fu, Yu ZhangFirst submitted to arxiv…
Summary of Recommending Pre-trained Models For Iot Devices, by Parth V. Patil et al.
Recommending Pre-Trained Models for IoT Devicesby Parth V. Patil, Wenxin Jiang, Huiyun Peng, Daniel Lugo,…
Summary of Exploring Embedding Priors in Prompt-tuning For Improved Interpretability and Control, by Sergey Sedov et al.
Exploring Embedding Priors in Prompt-Tuning for Improved Interpretability and Controlby Sergey Sedov, Sumanth Bharadwaj Hachalli…
Summary of Better Knowledge Enhancement For Privacy-preserving Cross-project Defect Prediction, by Yuying Wang et al.
Better Knowledge Enhancement for Privacy-Preserving Cross-Project Defect Predictionby Yuying Wang, Yichen Li, Haozhao Wang, Lei…
Summary of Generative Diffusion Modeling: a Practical Handbook, by Zihan Ding et al.
Generative Diffusion Modeling: A Practical Handbookby Zihan Ding, Chi JinFirst submitted to arxiv on: 22…
Summary of Lillama: Large Language Models Compression Via Low-rank Feature Distillation, by Yaya Sy and Christophe Cerisara and Irina Illina
Lillama: Large Language Models Compression via Low-Rank Feature Distillationby Yaya Sy, Christophe Cerisara, Irina IllinaFirst…
Summary of Novelty-guided Data Reuse For Efficient and Diversified Multi-agent Reinforcement Learning, by Yangkun Chen et al.
Novelty-Guided Data Reuse for Efficient and Diversified Multi-Agent Reinforcement Learningby Yangkun Chen, Kai Yang, Jian…
Summary of Preventing Local Pitfalls in Vector Quantization Via Optimal Transport, by Borui Zhang et al.
Preventing Local Pitfalls in Vector Quantization via Optimal Transportby Borui Zhang, Wenzhao Zheng, Jie Zhou,…
Summary of Toward Efficient Data-free Unlearning, by Chenhao Zhang et al.
Toward Efficient Data-Free Unlearningby Chenhao Zhang, Shaofei Shen, Weitong Chen, Miao XuFirst submitted to arxiv…
Summary of On Local Overfitting and Forgetting in Deep Neural Networks, by Uri Stern et al.
On Local Overfitting and Forgetting in Deep Neural Networksby Uri Stern, Tomer Yaacoby, Daphna WeinshallFirst…