RewardBench: the first evaluation tool for reward models.
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Updated
Jun 12, 2025 - Python
RewardBench: the first evaluation tool for reward models.
Free and open source code of the https://tournesol.app platform. Meet the community on Discord https://discord.gg/WvcSG55Bf3
Explore concepts like Self-Correct, Self-Refine, Self-Improve, Self-Contradict, Self-Play, and Self-Knowledge, alongside o1-like reasoning elevation🍓 and hallucination alleviation🍄.
A Survey of Direct Preference Optimization (DPO)
The MAGICAL benchmark suite for robust imitation learning (NeurIPS 2020)
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.
Python-based GUI to collect Feedback of Chemist in Molecules
Official implementation of Bootstrapping Language Models via DPO Implicit Rewards
Accelerate LLM preference tuning via prefix sharing with a single line of code
Code for the paper "Aligning LLM Agents by Learning Latent Preference from User Edits".
Official code for ICML 2024 paper, "RIME: Robust Preference-based Reinforcement Learning with Noisy Preferences" (ICML 2024 Spotlight)
PyTorch implementations for Offline Preference-Based RL (PbRL) algorithms
Data and models for the paper "Configurable Safety Tuning of Language Models with Synthetic Preference Data"
[ICLR 2025 Spotlight] Weak-to-strong preference optimization: stealing reward from weak aligned model
Code for "Monocular Depth Estimation via Listwise Ranking using the Plackett-Luce Model" as published at CVPR 2021.
This repository contains the source code for our paper: "Feedback-efficient Active Preference Learning for Socially Aware Robot Navigation", accepted to IROS-2022. For more details, please refer to our project website at https://sites.google.com/view/san-fapl.
Official PyTorch implementation of "LPOI: Listwise Preference Optimization for Vision Language Models" (ACL 2025 Main)
Official implementation of "Learning User Preferences for Image Generation Models"
[ICML 2025] TGDPO: Harnessing Token-Level Reward Guidance for Enhancing Direct Preference Optimization
Preference Learning with Gaussian Processes and Bayesian Optimization
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