Lists (18)
Starred repositories
One Model to Unite Them All: Personalized Federated Learning of Multi-Contrast MRI Synthesis (pFLSynth)
ViLReF: A Chinese Vision-Language Retinal Foundation Model
A reading list on LLM based Synthetic Data Generation 🔥
Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. arXiv:2408.07666.
The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery 🧑🔬
✨✨VITA: Towards Open-Source Interactive Omni Multimodal LLM
[Embodied-AI-Survey-2024] Paper list and projects for Embodied AI
Official repository for Towards Multi-modal Transformers in Federated Learning (ECCV2024)
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Updated Jul 5, 2024
The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM 2), links for downloading the trained model checkpoints, and example notebooks that show how to use th…
This is a collection of research papers for Federated Learning for Large Language Models (FedLLM). And the repository will be continuously updated to track the frontier of FedLLM.
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Updated Jul 16, 2024
Papers and resources related to the security and privacy of LLMs 🤖
A survey of privacy problems in Large Language Models (LLMs). Contains summary of the corresponding paper along with relevant code
COALA: A Practical and Vision-Centric Federated Learning Platform, accepted to ICML'24
A collection of awesome-prompt-datasets, awesome-instruction-dataset, to train ChatLLM such as chatgpt 收录各种各样的指令数据集, 用于训练 ChatLLM 模型。
✨✨Beyond LLaVA-HD: Diving into High-Resolution Large Multimodal Models
Get up and running with Llama 3.1, Mistral, Gemma 2, and other large language models.
One-size-fits-all model for mobile AI, a novel paradigm for mobile AI in which the OS and hardware co-manage a foundation model that is capable of addressing most, if not all, mobile AI tasks.
Official codes for CIKM '24 full paper: Tackling Noisy Clients in Federated Learning with End-to-end Label Correction
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Updated Aug 9, 2024
Paper list for Personal LLM Agents
Understand Human Behavior to Align True Needs
The implementation of the FedCVT algorithm, published in the paper "FedCVT: Semi-supervised Vertical Federated Learning with Cross-view Training"
The implementation of the PrADA algorithm published in the paper "Privacy-preserving Federated Adversarial Domain Adaptation over Feature Groups for Interpretability"
The implementation of FedCG algorithm, published in the paper "FedCG: Leverage Conditional GAN for Protecting Privacy and Maintaining Competitive Performance in Federated Learning"
