Popular GitHub Repositories for Reward

Clean PyTorch implementations of imitation and reward learning algorithms

For deep RL and the future of AI.

Recipes to train reward model for RLHF.

[NeurIPS 2024] SimPO: Simple Preference Optimization with a Reference-Free Reward

RL starter files in order to immediately train, visualize and evaluate an agent without writing any line of code

RewardBench: the first evaluation tool for reward models.

A curated list of awesome exploration RL resources (continually updated)

[RSS 2019] End-to-End Robotic Reinforcement Learning without Reward Engineering

Online RL with Simple Reward Enables Training VLA Models with Only One Trajectory

Implementation of ChatGPT, but tailored towards primary care medicine, with the reward being able to collect patient histories in a thorough and efficient manner and come up with a reasonable differential diagnosis

Multi-hop knowledge graph reasoning learned via policy gradient with reward shaping and action dropout

在A股(股票)市场上训练强化学习交易智能体

Video Diffusion Alignment via Reward Gradients. We improve a variety of video diffusion models such as VideoCrafter, OpenSora, ModelScope and StableVideoDiffusion by finetuning them using various reward models such as HPS, PickScore, VideoMAE, VJEPA, YOLO, Aesthetics etc.

AlignProp uses direct reward backpropogation for the alignment of large-scale text-to-image diffusion models. Our method is 25x more sample and compute efficient than reinforcement learning methods (PPO) for finetuning Stable Diffusion

Random Network Distillation pytorch

This repository hosts a customized PPO based agent for Carla. The goal of this project is to make it easier to interact with and experiment in Carla with reinforcement learning based agents -- this, by wrapping Carla in a gym like environment that can handle custom reward functions, custom debug output, etc.

PyTorch code for "Fine-grained Image Captioning with CLIP Reward" (Findings of NAACL 2022)

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

Recurrent and multi-process PyTorch implementation of deep reinforcement Actor-Critic algorithms A2C and PPO

[ICLR 2025] IterComp: Iterative Composition-Aware Feedback Learning from Model Gallery for Text-to-Image Generation