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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Official repository for "RLVR-World: Training World Models with Reinforcement Learning" (NeurIPS 2025), https://arxiv.org/abs/2505.13934
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# 🌏 RLVR-World: Training World Models with Reinforcement Learning (NeurIPS 2025) [](https://thuml.github.io/RLVR-World/) [](https://arxiv.org/abs/2505.13934) [](https://huggingface.co/collections/thuml/rlvr-world-682f331c75a904b8febc366a) This is the official code base for the paper [RLVR-World: Training World Models with Reinforcement Learning](https://arxiv.org/abs/2505.13934). Give it a star 🌟 if you find our work useful! ## 🔥 News - 🚩 **2025.10.28**: NeurIPS 2025 camera-ready version is released on [arXiv](https://arxiv.org/abs/2505.13934v2). - 🚩 **2024.09.18**: RLVR-World has been accepted by NeurIPS 2025, congrats! - 🚩 **2025.05.26**: We release all models and datasets. - 🚩 **2025.05.21**: We open-source our training codes. - 🚩 **2025.05.21**: Our paper is released on [arXiv](https://arxiv.org/abs/2505.13934). ## 📋 TL;DR We pioneer training world models through RLVR: - World models across various modalities (particularly, language and videos) are unified under a sequence modeling formulation; - Task-specific prediction metrics serve as verifiable rewards directly optimized by RL.  ## 🤗 Models and Datasets At the moment, we provide the following models and datasets: | Modality | Type | Domain | Name | | -------- | ----------- | ------------------ | ------------------------------------------------------------ | | Language | Dataset | Text game | [bytesized32-world-model-cot](https://huggingface.co/datasets/thuml/bytesized32-world-model-cot) | | Language | World model | Text game | [bytesized32-world-model-sft](https://huggingface.co/thuml/bytesized32-world-model-sft) | | Language | World model | Text game | [bytesized32-world-model-rlvr-binary-reward](https://huggingface.co/thuml/bytesized32-world-model-rlvr-binary-reward) | | Language | World model | Text game | [bytesized32-world-model-rlvr-task-specific-reward](https://huggingface.co/thuml/bytesized32-world-model-rlvr-task-specific-reward) | | Language | Dataset | Web navigation | [webarena-world-model-cot](https://huggingface.co/datasets/thuml/webarena-world-model-cot) | | Language | World model | Web navigation | [webarena-world-model-sft](https://huggingface.co/thuml/webarena-world-model-sft) | | Language | World model | Web navigation | [webarena-world-model-rlvr](https://huggingface.co/thuml/webarena-world-model-rlvr) | | Video | Tokenizer | Robot manipulation | [rt1-frame-tokenizer](https://huggingface.co/thuml/rt1-frame-tokenizer) | | Video | World model | Robot manipulation | [rt1-world-model-single-step-base](https://huggingface.co/thuml/rt1-world-model-single-step-base) | | Video | World model | Robot manipulation | [rt1-world-model-single-step-rlvr](https://huggingface.co/thuml/rt1-world-model-single-step-rlvr) | | Video | Tokenizer | Robot manipulation | [rt1-compressive-tokenizer](https://huggingface.co/thuml/rt1-compressive-tokenizer) | | Video | World model | Robot manipulation | [rt1-world-model-multi-step-base](https://huggingface.co/thuml/rt1-world-model-multi-step-base) | | Video | World model | Robot manipulation | [rt1-world-model-multi-step-rlvr](https://huggingface.co/thuml/rt1-world-model-multi-step-rlvr) | ## 💬 Evaluating Language World Models See [`lang_wm`](/lang_wm): - Text game state prediction - Web page state prediction - Application: Model predictive control for web agents ## 🎇 Evaluating Video World Models See [`vid_wm`](/vid_wm): - Robot manipulation trajectory prediction - Application: Real2sim policy evaluation ## 🎥 Showcases  ## 🚀 Release Progress - [x]
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Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:90244b9ff8f12acb, topic:video-generation
matched fp:90244b9ff8f12acb, topic:web-agent