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Found 8 papers, 4 papers with code
BeautifulPrompt: Towards Automatic Prompt Engineering for Text-to-Image Synthesis
Then, to ensure that our generated prompts can generate more beautiful images, we further propose a Reinforcement Learning with Visual AI Feedback technique to fine-tune our model to maximize the reward values of the generated prompts, where the reward values are calculated based on the PickScore and the Aesthetic Scores.
No Privacy Left Outside: On the (In-)Security of TEE-Shielded DNN Partition for On-Device ML
These solutions, referred to as TEE-Shielded DNN Partition (TSDP), partition a DNN model into two parts, offloading the privacy-insensitive part to the GPU while shielding the privacy-sensitive part within the TEE.
PAI-Diffusion: Constructing and Serving a Family of Open Chinese Diffusion Models for Text-to-image Synthesis on the Cloud
Text-to-image synthesis for the Chinese language poses unique challenges due to its large vocabulary size, and intricate character relationships.
Recent Advances on Federated Learning: A Systematic Survey
In this paper, we provide a systematic survey on federated learning, aiming to review the recent advanced federated methods and applications from different aspects.
DistFL: Distribution-aware Federated Learning for Mobile Scenarios
Previous studies focus on the "symptoms" directly, as they try to improve the accuracy or detect possible attacks by adding extra steps to conventional FL models.
ModelDiff: Testing-Based DNN Similarity Comparison for Model Reuse Detection
The knowledge of a deep learning model may be transferred to a student model, leading to intellectual property infringement or vulnerability propagation.
PFA: Privacy-preserving Federated Adaptation for Effective Model Personalization
Based on the grouping results, PFA conducts an FL process in a group-wise way on the federated model to accomplish the adaptation.
TransTailor: Pruning the Pre-trained Model for Improved Transfer Learning
This paper aims to improve the transfer performance from another angle - in addition to tuning the weights, we tune the structure of pre-trained models, in order to better match the target task.
