Name: Yi-Fan Zhang
Type: User
Company: State Key Laboratory of Pattern Recognition
Bio: The third year Ph.D. student @CASIA, NLPR, advised by Prof. Tieniu Tan. Formerly @microsoft Research Asia and @Alibaba DAMO Academy.
Location: Haidian Beijing
Blog: https://yfzhang114.github.io/
Yi-Fan Zhang's Projects
AcadHomepage: A Modern and Responsive Academic Personal Homepage
A project page template for academic papers. Demo at https://eliahuhorwitz.github.io/Academic-project-page-template/
This is an official PyTorch implementation of the ICML 2023 paper AdaNPC and SIGKDD paper DRM.
Reading notes about Multimodal Large Language Models, Large Language Models, and Diffusion Models
Awesome Person Re-identification
[ICML 2020] Continuously Indexed Domain Adaptation
Torchreid: Deep learning person re-identification in PyTorch.
DomainBed is a suite to test domain generalization algorithms
This is an official PyTorch implementation of the ICLR 2023 paper 《Free Lunch for Domain Adversarial Training: Environment Label Smoothing》.
关于domain generalization,domain adaptation,causality,robutness,prompt,optimization,generative model各式各样研究的阅读笔记
Python 基于BP神经网络实现鸢尾花的分类
This is the official repo for Debiasing Large Visual Language Models, including a Post-Hoc debias method and Visual Debias Decoding strategy.
✨✨ MME-RealWorld: Could Your Multimodal LLM Challenge High-Resolution Real-World Scenarios that are Difficult for Humans?
Neural Logic Inductive Learning
This is an official PyTorch implementation of the NeurIPS 2023 paper 《OneNet: Enhancing Time Series Forecasting Models under Concept Drift by Online Ensembling》
My personal homepage
[ICML 2022]Source code for "A Closer Look at Smoothness in Domain Adversarial Training",
✨✨Beyond LLaVA-HD: Diving into High-Resolution Large Multimodal Models
This codebase is the official implementation of Test-Time Classifier Adjustment Module for Model-Agnostic Domain Generalization (NeurIPS2021, Spotlight)
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes