Popular GitHub Repositories for Preference

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

RewardBench: the first evaluation tool for reward models.

The official implementation of Self-Play Preference Optimization (SPPO)

? OAT: A research-friendly framework for LLM online alignment, including preference learning, reinforcement learning, etc.

A curated list of Human Preference Datasets for LLM fine-tuning, RLHF, and eval.

Better Aligning Text-to-Image Models with Human Preference. ICCV 2023

VisionReward: Fine-Grained Multi-Dimensional Human Preference Learning for Image and Video Generation

[Paper][ACL 2024 Findings] Knowledgeable Preference Alignment for LLMs in Domain-specific Question Answering

Python based Graph Propagation algorithm, DeepWalk to evaluate and compare preference propagation algorithms in heterogeneous information networks from user item relation ship.

4th Place Solution for the Kaggle Competition: LMSYS - Chatbot Arena Human Preference Predictions

Explore concepts like Self-Correct, Self-Refine, Self-Improve, Self-Contradict, Self-Play, and Self-Knowledge, alongside o1-like reasoning elevation? and hallucination alleviation?.

Notus is a collection of fine-tuned LLMs using SFT, DPO, SFT+DPO, and/or any other RLHF techniques, while always keeping a data-first approach

Preference Transformer: Modeling Human Preferences using Transformers for RL (ICLR2023 Accepted)

The MAGICAL benchmark suite for robust imitation learning (NeurIPS 2020)

official implementation of ICLR'2025 paper: Rethinking Bradley-Terry Models in Preference-based Reward Modeling: Foundations, Theory, and Alternatives

This repository contains the source code for our paper: "NaviSTAR: Socially Aware Robot Navigation with Hybrid Spatio-Temporal Graph Transformer and Preference Learning". For more details, please refer to our project website at https://sites.google.com/view/san-navistar.

[ACL 2024] Self-Training with Direct Preference Optimization Improves Chain-of-Thought Reasoning

[NeurIPS 2024] Official code of $\beta$-DPO: Direct Preference Optimization with Dynamic $\beta$

A Survey of Direct Preference Optimization

Official implementation of "Direct Preference-based Policy Optimization without Reward Modeling" (NeurIPS 2023)