{
  "schema_version": 1,
  "slug": "teleworld",
  "canonical_url": "https://akira-l.github.io/publications/teleworld/",
  "language_urls": {
    "en": "https://akira-l.github.io/publications/teleworld/",
    "zh-CN": "https://akira-l.github.io/zh/publications/teleworld/"
  },
  "title": "TeleWorld: Towards Dynamic Multimodal Synthesis with a 4D World Model",
  "short_title": "TeleWorld",
  "authors": [
    "Yabo Chen",
    "Yuanzhi Liang",
    "Jiepeng Wang",
    "Tingxi Chen",
    "Junfei Cheng",
    "Zixiao Gu",
    "Yuyang Huang",
    "Zicheng Jiang",
    "Wei Li",
    "Tian Li",
    "Weichen Li",
    "Zuoxin Li",
    "Guangce Liu",
    "Jialun Liu",
    "Junqi Liu",
    "Haoyuan Wang",
    "Qizhen Weng",
    "Xuan'er Wu",
    "Xunzhi Xiang",
    "Xiaoyan Yang",
    "Xin Zhang",
    "Shiwen Zhang",
    "Junyu Zhou",
    "Chengcheng Zhou",
    "Haibin Huang",
    "Chi Zhang",
    "Xuelong Li"
  ],
  "publication": {
    "kind": "preprint",
    "venue": "arXiv",
    "citation_container_title": "arXiv",
    "status": "preprint",
    "year": 2025,
    "publication_date": "2025-12-31"
  },
  "identifiers": {
    "arxiv": "2601.00051",
    "arxiv_primary_class": "cs.CV"
  },
  "arxiv_dates": {
    "first_posted": "2025-12-31",
    "last_revised": "2025-12-31"
  },
  "keywords": [
    "4D world model",
    "video generation",
    "dynamic reconstruction",
    "long-term memory",
    "real-time synthesis"
  ],
  "official_abstract": "World models aim to endow AI systems with the ability to represent, generate, and interact with dynamic environments in a coherent and temporally consistent manner. While recent video generation models have demonstrated impressive visual quality, they remain limited in real-time interaction, long-horizon consistency, and persistent memory of dynamic scenes, hindering their evolution into practical world models. In this report, we present TeleWorld, a real-time multimodal 4D world modeling framework that unifies video generation, dynamic scene reconstruction, and long-term world memory within a closed-loop system. TeleWorld introduces a novel generation-reconstruction-guidance paradigm, where generated video streams are continuously reconstructed into a dynamic 4D spatio-temporal representation, which in turn guides subsequent generation to maintain spatial, temporal, and physical consistency. To support long-horizon generation with low latency, we employ an autoregressive diffusion-based video model enhanced with Macro-from-Micro Planning (MMPL)--a hierarchical planning method that reduces error accumulation from frame-level to segment-level-alongside efficient Distribution Matching Distillation (DMD), enabling real-time synthesis under practical computational budgets. Our approach achieves seamless integration of dynamic object modeling and static scene representation within a unified 4D framework, advancing world models toward practical, interactive, and computationally accessible systems. Extensive experiments demonstrate that TeleWorld achieves strong performance in both static and dynamic world understanding, long-term consistency, and real-time generation efficiency, positioning it as a practical step toward interactive, memory-enabled world models for multimodal generation and embodied intelligence.",
  "official_abstract_rights": "Excluded from the site's CC BY 4.0 license; original paper rights apply.",
  "primary_source": {
    "label": "arXiv record",
    "url": "https://arxiv.org/abs/2601.00051",
    "version": "arXiv:2601.00051v1",
    "method_locator": "Abstract; generation-reconstruction-guidance, MMPL, and DMD sections",
    "evidence_locator": "Abstract; static/dynamic understanding, consistency, and efficiency experiments"
  },
  "source_checked": "2026-07-31",
  "verification_status": "author-verified",
  "author_verified_on": "2026-07-31",
  "commentary": {
    "license": "https://creativecommons.org/licenses/by/4.0/",
    "en": {
      "summary": "TeleWorld closes a loop between video generation and 4D reconstruction: generated streams update a persistent spatiotemporal representation that guides later generation, while Macro-from-Micro Planning and distillation target long horizons and real-time latency.",
      "problem": "High-quality video generators still lack real-time interaction, persistent scene memory, and reliable long-horizon spatial, temporal, and physical consistency required of practical world models.",
      "contributions": [
        "Unifies video generation, dynamic scene reconstruction, and long-term world memory in a closed-loop 4D framework.",
        "Uses a generation–reconstruction–guidance cycle in which the reconstructed 4D state conditions subsequent generation.",
        "Combines Macro-from-Micro Planning with Distribution Matching Distillation for long-horizon, lower-latency synthesis."
      ],
      "evidence": "The report evaluates static and dynamic world understanding, long-term consistency, and real-time generation efficiency. Exact latency, hardware, scene, and benchmark conditions must be read from the experimental section.",
      "limitations": "A closed-loop world model can inherit reconstruction errors and generation errors, so long-term behavior depends on how accurately state is reconstructed and reused. Claims of real-time operation are conditional on the paper's reported compute and setup.",
      "positioning": "TeleWorld bridges video generation, dynamic reconstruction, and persistent memory. It is relevant to work that seeks a stateful, interactive world model rather than a one-shot video generator.",
      "citation_ready": "Chen et al. present TeleWorld, a closed-loop 4D world-model framework in which generated video is reconstructed into a persistent spatiotemporal state that guides subsequent generation, with hierarchical planning and distillation supporting long-horizon real-time synthesis."
    },
    "zh-CN": {
      "summary": "TeleWorld 在视频生成和 4D 重建之间形成闭环：生成流持续写入时空表示，这个持久状态再指导后续生成；Macro-from-Micro Planning 与蒸馏用于支持长时和低延迟合成。",
      "problem": "高质量视频生成器仍缺少实时交互、动态场景的持久记忆，以及长时间范围内可靠的空间、时间和物理一致性，因此尚不能直接作为实用 world model。",
      "contributions": [
        "在闭环 4D 框架中统一视频生成、动态场景重建与长期世界记忆。",
        "提出 generation–reconstruction–guidance 循环，用重建后的 4D 状态指导下一段生成。",
        "结合 Macro-from-Micro Planning 与 Distribution Matching Distillation，面向长时低延迟合成。"
      ],
      "evidence": "报告评测了静态与动态世界理解、长时一致性和实时生成效率；准确延迟、硬件、场景与 benchmark 条件应以实验章节为准。",
      "limitations": "闭环系统可能同时累积重建误差与生成误差，长时表现取决于状态被重建和复用的准确性；“实时”结论也受论文所用算力和配置约束。",
      "positioning": "TeleWorld 连接视频生成、动态重建和持久记忆，适合被定位为从一次性视频生成走向有状态、可交互 world model 的工作。",
      "citation_ready": "Chen 等提出 TeleWorld：将生成视频重建为持久 4D 时空状态并用于指导后续生成，同时以层次规划和蒸馏支持长时实时合成。"
    }
  },
  "citation": {
    "id": "chen2025teleworld",
    "type": "article",
    "title": "TeleWorld: Towards Dynamic Multimodal Synthesis with a 4D World Model",
    "author": [
      {
        "given": "Yabo",
        "family": "Chen"
      },
      {
        "given": "Yuanzhi",
        "family": "Liang"
      },
      {
        "given": "Jiepeng",
        "family": "Wang"
      },
      {
        "given": "Tingxi",
        "family": "Chen"
      },
      {
        "given": "Junfei",
        "family": "Cheng"
      },
      {
        "given": "Zixiao",
        "family": "Gu"
      },
      {
        "given": "Yuyang",
        "family": "Huang"
      },
      {
        "given": "Zicheng",
        "family": "Jiang"
      },
      {
        "given": "Wei",
        "family": "Li"
      },
      {
        "given": "Tian",
        "family": "Li"
      },
      {
        "given": "Weichen",
        "family": "Li"
      },
      {
        "given": "Zuoxin",
        "family": "Li"
      },
      {
        "given": "Guangce",
        "family": "Liu"
      },
      {
        "given": "Jialun",
        "family": "Liu"
      },
      {
        "given": "Junqi",
        "family": "Liu"
      },
      {
        "given": "Haoyuan",
        "family": "Wang"
      },
      {
        "given": "Qizhen",
        "family": "Weng"
      },
      {
        "given": "Xuan'er",
        "family": "Wu"
      },
      {
        "given": "Xunzhi",
        "family": "Xiang"
      },
      {
        "given": "Xiaoyan",
        "family": "Yang"
      },
      {
        "given": "Xin",
        "family": "Zhang"
      },
      {
        "given": "Shiwen",
        "family": "Zhang"
      },
      {
        "given": "Junyu",
        "family": "Zhou"
      },
      {
        "given": "Chengcheng",
        "family": "Zhou"
      },
      {
        "given": "Haibin",
        "family": "Huang"
      },
      {
        "given": "Chi",
        "family": "Zhang"
      },
      {
        "given": "Xuelong",
        "family": "Li"
      }
    ],
    "container-title": "arXiv",
    "issued": {
      "date-parts": [
        [
          2025,
          12,
          31
        ]
      ]
    },
    "URL": "https://arxiv.org/abs/2601.00051",
    "abstract": "World models aim to endow AI systems with the ability to represent, generate, and interact with dynamic environments in a coherent and temporally consistent manner. While recent video generation models have demonstrated impressive visual quality, they remain limited in real-time interaction, long-horizon consistency, and persistent memory of dynamic scenes, hindering their evolution into practical world models. In this report, we present TeleWorld, a real-time multimodal 4D world modeling framework that unifies video generation, dynamic scene reconstruction, and long-term world memory within a closed-loop system. TeleWorld introduces a novel generation-reconstruction-guidance paradigm, where generated video streams are continuously reconstructed into a dynamic 4D spatio-temporal representation, which in turn guides subsequent generation to maintain spatial, temporal, and physical consistency. To support long-horizon generation with low latency, we employ an autoregressive diffusion-based video model enhanced with Macro-from-Micro Planning (MMPL)--a hierarchical planning method that reduces error accumulation from frame-level to segment-level-alongside efficient Distribution Matching Distillation (DMD), enabling real-time synthesis under practical computational budgets. Our approach achieves seamless integration of dynamic object modeling and static scene representation within a unified 4D framework, advancing world models toward practical, interactive, and computationally accessible systems. Extensive experiments demonstrate that TeleWorld achieves strong performance in both static and dynamic world understanding, long-term consistency, and real-time generation efficiency, positioning it as a practical step toward interactive, memory-enabled world models for multimodal generation and embodied intelligence.",
    "keyword": "4D world model, video generation, dynamic reconstruction, long-term memory, real-time synthesis",
    "archive": "arXiv",
    "archive_location": "2601.00051",
    "genre": "Preprint"
  },
  "resources": [
    {
      "label": "arXiv",
      "url": "https://arxiv.org/abs/2601.00051"
    },
    {
      "label": "PDF",
      "url": "https://arxiv.org/pdf/2601.00051"
    }
  ]
}