Popular GitHub Repositories for Feedback

??? 60+ Implementations/tutorials of deep learning papers with side-by-side notes ?; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), ? reinforcement learning (ppo, dqn), capsnet, distillation, ... ?

TensorZero creates a feedback loop for optimizing LLM applications — turning production data into smarter, faster, and cheaper models.

Implementation of RLHF (Reinforcement Learning with Human Feedback) on top of the PaLM architecture. Basically ChatGPT but with PaLM

A repo for distributed training of language models with Reinforcement Learning via Human Feedback (RLHF)

Align Anything: Training All-modality Model with Feedback

A curated list of reinforcement learning with human feedback resources (continually updated)

Distilabel is a framework for synthetic data and AI feedback for engineers who need fast, reliable and scalable pipelines based on verified research papers.

Motion planning algorithms commonly used on autonomous vehicles. (path planning + path tracking)

推荐/广告/搜索领域工业界经典以及最前沿论文集合。A collection of industry classics and cutting-edge papers in the field of recommendation/advertising/search.

PyTorch implementation of various methods for continual learning (XdG, EWC, SI, LwF, FROMP, DGR, BI-R, ER, A-GEM, iCaRL, Generative Classifier) in three different scenarios.

Safe RLHF: Constrained Value Alignment via Safe Reinforcement Learning from Human Feedback

Textbook on reinforcement learning from human feedback

This repository collects papers for "A Survey on Knowledge Distillation of Large Language Models". We break down KD into Knowledge Elicitation and Distillation Algorithms, and explore the Skill & Vertical Distillation of LLMs.

Feedback on GitHub Copilot Chat UX in Visual Studio Code.

AI Code Reviewer: Enhance your GitHub workflow with AI-powered code review! Get intelligent feedback and suggestions on pull requests using OpenAI's GPT-4 API, improving code quality and saving developers time.

:milky_way: Open Source AI for large scale open ended feedback

A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convolutional Network.

A simulation framework for RLHF and alternatives. Develop your RLHF method without collecting human data.

LLMs can generate feedback on their work, use it to improve the output, and repeat this process iteratively.

Artemis - Interactive Learning with Automated Feedback