wuwukongkong

wuwukongkong's Stars

• huggingface/trl

  Train transformer language models with reinforcement learning.

  Language:Python12k841.5k1.6k

• ccfddl/ccf-deadlines

  ⏰ Collaboratively track deadlines of conferences recommended by CCF (Website, Python Cli, Wechat Applet) / If you find it useful, please star this project, thanks~

  Language:Vue6.9k2193476

• TencentARC/InstantMesh

  InstantMesh: Efficient 3D Mesh Generation from a Single Image with Sparse-view Large Reconstruction Models

  Language:Python3.7k49173394

• google-research/parti

  1.6k55984

• THUDM/ImageReward

  [NeurIPS 2023] ImageReward: Learning and Evaluating Human Preferences for Text-to-image Generation

  Language:Python1.3k149667

• nianticlabs/mickey

  [CVPR 2024 - Oral] Matching 2D Images in 3D: Metric Relative Pose from Metric Correspondences

  Language:Python529122235

• yuvalkirstain/PickScore

  Language:Python47533429

• cvpr-org/author-kit

  Language:TeX465113880

• tgxs002/HPSv2

  Human Preference Score v2: A Solid Benchmark for Evaluating Human Preferences of Text-to-Image Synthesis

  Language:Jupyter Notebook452104116

• mindspore-lab/mindone

  one for all, Optimal generator with No Exception

  Language:Python381136781

• yfzhang114/Awesome-Multimodal-Large-Language-Models

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

  254629

• openpsi-project/ReaLHF

  Super-Efficient RLHF Training of LLMs with Parameter Reallocation

  Language:Python22342113

• yk7333/d3po

  [CVPR 2024] Code for the paper "Using Human Feedback to Fine-tune Diffusion Models without Any Reward Model"

  Language:Python19571819

• RockeyCoss/SPO

  Aesthetic Post-Training Diffusion Models from Generic Preferences with Step-by-step Preference Optimization

  Language:Python1795236

• lyndonzheng/Free3D

  [CVPR'24] Consistent Novel View Synthesis without 3D Representation

  Language:Python1541574

• jiawei-ren/insactor

  [NeurIPS 2023] InsActor: Instruction-driven Physics-based Characters

  Language:Python13810313

• ExplainableML/ReNO

  [NeurIPS 2024] ReNO: Enhancing One-step Text-to-Image Models through Reward-based Noise Optimization

  Language:Python1235910

• sjtuplayer/SaRA

  SaRA: High-Efficient Diffusion Model Fine-tuning with Progressive Sparse Low-Rank Adaptation

  Language:Python108847

• rom1504/embedding-reader

  Efficiently read embedding in streaming from any filesystem

  Language:Python9842820

• abacusai/smaug

  66333

• liujf69/Classic-Generative-Model

  Simple code demos about classic AIGC models/Compilation of blogs and papers on classic AIGC models.

  Language:Python60107

• pinterest/atg-research

  Language:Python45611

• jacklishufan/diffusion-kto

  The official implementation of Diffusion-KTO: Aligning Diffusion Models by Optimizing Human Utility

  Language:Python35210

• Shentao-YANG/Dense_Reward_T2I

  Source code for "A Dense Reward View on Aligning Text-to-Image Diffusion with Preference" (ICML'24).

  Language:Python35210

• cccedric/cpql

  This is the official PyTorch implementation of the paper "Boosting Continuous Control with Consistency Policy".

  Language:Python31213

• general-preference/general-preference-model

  Official implementation of paper "Beyond Bradley-Terry Models: A General Preference Model for Language Model Alignment" (https://arxiv.org/abs/2410.02197)

  Language:Python22202

• princeton-nlp/unintentional-unalignment

  [ICLR 2025] Unintentional Unalignment: Likelihood Displacement in Direct Preference Optimization

  Language:Python19502

• ZiyiZhang27/sdpo

  Code for the paper "Aligning Few-Step Diffusion Models with Dense Reward Difference Learning"

  Language:Python130

• catalpaaa/DeMansia

  Language:Python8101

• atelion/DPO-Stable-Diffusion

  Language:Python42