Xubing Ye's starred repositories
generative-models
Generative Models by Stability AI
Awesome-Multimodal-Large-Language-Models
:sparkles::sparkles:Latest Advances on Multimodal Large Language Models
mistral-src
Reference implementation of Mistral AI 7B v0.1 model.
awesome-RLHF
A curated list of reinforcement learning with human feedback resources (continually updated)
Awesome-Text-to-Image
(ෆ`꒳´ෆ) A Survey on Text-to-Image Generation/Synthesis.
direct-preference-optimization
Reference implementation for DPO (Direct Preference Optimization)
RPG-DiffusionMaster
[ICML 2024] Mastering Text-to-Image Diffusion: Recaptioning, Planning, and Generating with Multimodal LLMs (RPG)
Video-Swin-Transformer
This is an official implementation for "Video Swin Transformers".
Awesome-Multimodal-Research
A curated list of Multimodal Related Research.
ImageReward
[NeurIPS 2023] ImageReward: Learning and Evaluating Human Preferences for Text-to-image Generation
llm-hallucination-survey
Reading list of hallucination in LLMs. Check out our new survey paper: "Siren’s Song in the AI Ocean: A Survey on Hallucination in Large Language Models"
ReferFormer
[CVPR2022] Official Implementation of ReferFormer
deep-learning-dynamics-paper-list
This is a list of peer-reviewed representative papers on deep learning dynamics (optimization dynamics of neural networks). The success of deep learning attributes to both network architecture and stochastic optimization. Thus, deep learning dynamics play an essentially important role in theoretical foundation of deep learning.
tongji-undergrad-thesis
:page_facing_up: 同济大学本科生毕业设计论文模板 | Tongji University Undergraduate Thesis Template | Overleaf / Mac / Linux / Windows / Workshop / Docker
segment-caption-anything
[CVPR 24] The repository provides code for running inference and training for "Segment and Caption Anything" (SCA) , links for downloading the trained model checkpoints, and example notebooks / gradio demo that show how to use the model.
Awesome-Video-Object-Segmentation
:bookmark: Curated list of video object segmentation (VOS) papers, datasets, and projects.