RewardBench: the first evaluation tool for reward models.
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Updated
Sep 30, 2026 - 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
Pairwise LLM judges (A/B/tie): budget-aware multi-turn packing, position-bias correction, pseudo-label distillation. Generalized from the 4th-place (gold) solution to Kaggle LMSYS Chatbot Arena.
The MAGICAL benchmark suite for robust imitation learning (NeurIPS 2020)
Self-evolving agentic reward framework for image-editing evaluation — 47.4% on EditReward-Bench from only 100 preference demos, no reward-model training. arXiv 2605.08703.
Policy-driven preference data for content moderation, with source-linked evidence, resumable runs, budget controls and TRL/ShareGPT exports.
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
Accelerate LLM preference tuning via prefix sharing with a single line of code
Official implementation of Bootstrapping Language Models via DPO Implicit Rewards
Code for the paper "Aligning LLM Agents by Learning Latent Preference from User Edits".
Policy Learning from Large Vision-Language Model Feedback Without Reward Modeling (IROS 2025)
Official code for ICML 2024 paper, "RIME: Robust Preference-based Reinforcement Learning with Noisy Preferences" (ICML 2024 Spotlight)
[ICLR 2026] MergeMix: A Unified Augmentation Paradigm for Visual and Multi-Modal Understanding
PyTorch implementations for Offline Preference-Based RL (PbRL) algorithms
[ICLR 2025 Spotlight] Weak-to-strong preference optimization: stealing reward from weak aligned model
Data and models for the paper "Configurable Safety Tuning of Language Models with Synthetic Preference Data"
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"
Code for "Monocular Depth Estimation via Listwise Ranking using the Plackett-Luce Model" as published at CVPR 2021.
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