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autoregressive-models 开源项目推荐(187 个)
autoregressive-models 话题在 GitHub 上没有填写简介,这里按 Star 数汇总最相关的热门仓库。
热门项目 前 20
按 Star 数排序展示前 20 个 · GitHub 共 187 个仓库[CVPR 2025 Oral]Infinity ∞ : Scaling Bitwise AutoRegressive Modeling for High-Resolution Image Synthesis
PDEBench: An Extensive Benchmark for Scientific Machine Learning
[ICML 2026] Official codebase for "Causal Forcing: Autoregressive Diffusion Distillation Done Right for High-Quality Real-Time Interactive Video Generation" & Causal Forcing++
[NeurIPS 2025 Oral]Infinity⭐️: Unified Spacetime AutoRegressive Modeling for Visual Generation
[ICLR 2025] Autoregressive Video Generation without Vector Quantization
(Accepted by IJCV) Liquid: Language Models are Scalable and Unified Multi-modal Generators
[NeurIPS 2025 Spotlight] A Unified Tokenizer for Visual Generation and Understanding
VibeVoiceFusion 是一个全栈、多扬声器语音生成网络系统,具备 LoRA 微调、批量生成和显存优化功能。基于Microsoft的VibeVoice(AR + 扩散架构)
Code for "ATISS: Autoregressive Transformers for Indoor Scene Synthesis", NeurIPS 2021
High-performance Image Tokenizers for VAR and AR
Interactive Character Control with Auto-Regressive Motion Diffusion Models
SSR-Speech: Towards Stable, Safe and Robust Zero-shot Speech Editing and Synthesis
the official repo for "D-AR: Diffusion via Autoregressive Models"
An Efficient Text-to-Image Generation Pretrain Pipeline
Generative model for sequential recommendation based on Convolution Neural Networks (CNN))
Offical implementation of "Auto-Regressively Generating Multi-View Consistent Images". (ICCV 2025)
[CVPR 2026]Official PyTorch implementation of AvatarPointillist: AutoRegressive 4D Gaussian Avatarization.
Raster2Seq: Polygon Sequence Generation for Floorplan Reconstruction (SIGGRAPH 2026)
official training and inference code of bitwise tokenizer
关于这个话题
- 清单取自 GitHub 话题页并按 Star 数排序,每次展示前 20 个项目;原始页面见 https://github.com/topics/autoregressive-models。
- 该话题在 GitHub 上共有 187 个仓库, 本站收录的是其中最热门的 20 个,不是全量列表。
- Star / Fork 每日自动刷新一次,实时数据以 GitHub 为准。
- 当前 20 个项目累计 1.7 万 Star,覆盖 2 种主要语言,数据更新于 2026-11-08。
- 中文介绍来自 GitHub 官方话题说明(github/explore)的机器翻译,可点「查看原文」对照;译文缺失时会先展示原文。