This is a repository dedicated to organizing articles and related works on Unified Multimodal Model for Understanding and Generation.

📖 This is a repository for organizing papers, codes and other resources related to unified multimodal models.

Reading notes about Multimodal Large Language Models, Large Language Models, and Diffusion Models

✨✨ MME-RealWorld: Could Your Multimodal LLM Challenge High-Resolution Real-World Scenarios that are Difficult for Humans?

✨✨VITA-1.5: Towards GPT-4o Level Real-Time Vision and Speech Interaction

✨✨Beyond LLaVA-HD: Diving into High-Resolution Large Multimodal Models

✨✨Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis

A project page template for academic papers. Demo at https://eliahuhorwitz.github.io/Academic-project-page-template/

This is the official repo for Debiasing Large Visual Language Models, including a Post-Hoc debias method and Visual Debias Decoding strategy.

🎨 ML Visuals contains figures and templates which you can reuse and customize to improve your scientific writing.

Recent LLM-based CV and related works. Welcome to comment/contribute!

This is an official PyTorch implementation of the NeurIPS 2023 paper 《OneNet: Enhancing Time Series Forecasting Models under Concept Drift by Online Ensembling》

This is an official PyTorch implementation of the ICML 2023 paper AdaNPC and SIGKDD paper DRM.

Contrastive Learning for Domain Adaptation of Time Series

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

AcadHomepage: A Modern and Responsive Academic Personal Homepage

This codebase is the official implementation of Test-Time Classifier Adjustment Module for Model-Agnostic Domain Generalization (NeurIPS2021, Spotlight)

DomainBed is a suite to test domain generalization algorithms

Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习