{
  "schema_version": "2026.08-v1",
  "generated_at": "2026-08-25",
  "view": "contemporary-horizontal",
  "purpose": "同期横向视图：按季度时间窗把各团队/机构的论文铺到统一语义层，看同一时期各团队各自补了数据流的哪一块、是否在改同一个模块。",
  "windows": [
    {
      "window": "2026 Q2",
      "items": [
        {
          "paper_id": "arxiv-2606-09215",
          "team": "Mondo Robotics / HKUST-GZ",
          "semantic_layers": [
            "state-world-model",
            "wbc-contact-control",
            "sensor-encoding",
            "data-production-collection",
            "planning-action-generation",
            "embodiment-actuation-sysid",
            "sim2real-adaptation"
          ],
          "module_focus": "WAM 全身动作 latent + G1 真机"
        },
        {
          "paper_id": "arxiv-2606-19531",
          "team": "ImageWAM authors",
          "semantic_layers": [
            "state-world-model",
            "sensor-encoding",
            "planning-action-generation"
          ],
          "module_focus": "图像编辑 KV cache 替代视频生成"
        },
        {
          "paper_id": "arxiv-2606-31836",
          "team": "RoboTacDex authors",
          "semantic_layers": [
            "data-production-collection",
            "sensor-encoding",
            "wbc-contact-control"
          ],
          "module_focus": "G1 多模态触觉数据集"
        },
        {
          "paper_id": "arxiv-2606-03297",
          "team": "SplitAdapter authors",
          "semantic_layers": [
            "wbc-contact-control",
            "planning-action-generation",
            "data-production-collection",
            "embodiment-actuation-sysid",
            "sensor-encoding",
            "sim2real-adaptation"
          ],
          "module_focus": "负载感知人形 loco-manipulation 适配"
        },
        {
          "paper_id": "oa-w7163539690",
          "team": "NVIDIA / UCLA",
          "semantic_layers": [
            "data-production-collection",
            "multimodal-alignment",
            "planning-action-generation",
            "wbc-contact-control",
            "sim2real-adaptation"
          ],
          "module_focus": "3D资产+视频先验→G1合成loco-manipulation"
        },
        {
          "paper_id": "arxiv-2606-27813",
          "team": "Booster Lab authors",
          "semantic_layers": ["data-production-collection", "data-curation-valuation", "embodiment-actuation-sysid", "sim2real-adaptation"],
          "module_focus": "数据清洗、重定向、real-to-sim 标定与 T1/K1 真机反馈闭环"
        }
      ]
    },
    {
      "window": "2026 Q3",
      "items": [
        {
          "paper_id": "arxiv-2607-02840",
          "team": "Peking University / AI2 Robotics",
          "semantic_layers": [
            "state-world-model",
            "sensor-encoding",
            "multimodal-alignment",
            "planning-action-generation",
            "wbc-contact-control"
          ],
          "module_focus": "触觉世界模型自纠错 VLA 后训练"
        },
        {
          "paper_id": "arxiv-2607-07287",
          "team": "HIT Shenzhen / PHANES AI",
          "semantic_layers": [
            "state-world-model",
            "sensor-encoding",
            "multimodal-alignment",
            "planning-action-generation",
            "wbc-contact-control"
          ],
          "module_focus": "预测+反应式触觉基础模型分层控制"
        },
        {
          "paper_id": "arxiv-2607-22530",
          "team": "ShanghaiTech / InstAdapt",
          "semantic_layers": [
            "state-world-model",
            "sensor-encoding",
            "multimodal-alignment",
            "data-production-collection",
            "planning-action-generation",
            "wbc-contact-control"
          ],
          "module_focus": "视觉触觉世界模型轨迹增强"
        },
        {
          "paper_id": "arxiv-2608-15816",
          "team": "ICR Lab / ViTaR authors",
          "semantic_layers": ["sensor-encoding", "multimodal-alignment", "planning-action-generation", "sim2real-adaptation"],
          "module_focus": "冻结基础 VLA 的视觉-触觉残差适配；RealMan RM65-B 真机但制品未开放"
        },
        {
          "paper_id": "arxiv-2607-10132",
          "team": "Purdue / U Florida",
          "semantic_layers": [
            "sensor-encoding",
            "wbc-contact-control",
            "state-world-model",
            "embodiment-actuation-sysid",
            "sim2real-adaptation"
          ],
          "module_focus": "四足触觉 loco-manipulation RL"
        },
        {
          "paper_id": "arxiv-2608-02365",
          "team": "Huawei Noah's Ark / Celia",
          "semantic_layers": [
            "state-world-model",
            "planning-action-generation",
            "sensor-encoding"
          ],
          "module_focus": "DoT 低时延 WAM"
        },
        {
          "paper_id": "arxiv-2608-08558",
          "team": "Fudan / CUHK-SZ",
          "semantic_layers": [
            "state-world-model",
            "sensor-encoding",
            "planning-action-generation",
            "data-production-collection"
          ],
          "module_focus": "视频先验蒸馏 WAM"
        },
        {
          "paper_id": "arxiv-2608-06375",
          "team": "MARS Lab NTU / PKU",
          "semantic_layers": [
            "state-world-model",
            "sensor-encoding",
            "multimodal-alignment",
            "planning-action-generation",
            "wbc-contact-control",
            "data-production-collection",
            "embodiment-actuation-sysid"
          ],
          "module_focus": "潜在预测 WAM 全身 loco-manipulation"
        },
        {
          "paper_id": "arxiv-2608-20114",
          "team": "清华 / 上海AI Lab / 哈工大 / DEEP Robotics",
          "semantic_layers": [
            "data-production-collection",
            "multimodal-alignment",
            "state-world-model",
            "planning-action-generation",
            "wbc-contact-control",
            "embodiment-actuation-sysid",
            "sim2real-adaptation"
          ],
          "module_focus": "ARMDOG足式移动操作WAM：基地-机械臂解耦与ego-motion"
        },
        {
          "paper_id": "arxiv-2608-15060",
          "team": "EgoTac authors",
          "semantic_layers": [
            "data-production-collection",
            "sensor-encoding",
            "multimodal-alignment",
            "sim2real-adaptation"
          ],
          "module_focus": "自然场景视觉→触觉预测与跨数据集 OOD 泛化"
        },
        {
          "paper_id": "arxiv-2608-10780",
          "team": "StageWAM authors",
          "semantic_layers": [
            "sensor-encoding",
            "state-world-model",
            "planning-action-generation",
            "sim2real-adaptation"
          ],
          "module_focus": "阶段级JEPA未来 + 局部WAM动作/视频"
        },
        {
          "paper_id": "arxiv-2607-23782",
          "team": "NeoteAI / Fudan TEAI",
          "semantic_layers": [
            "data-production-collection",
            "sensor-encoding",
            "multimodal-alignment",
            "planning-action-generation",
            "sim2real-adaptation"
          ],
          "module_focus": "latent tactile tokens + offline advantage relabeling"
        },
        {
          "paper_id": "arxiv-2608-19574",
          "team": "HiTac-WAM authors",
          "semantic_layers": ["sensor-encoding", "state-world-model", "planning-action-generation", "wbc-contact-control", "sim2real-adaptation"],
          "module_focus": "分层触觉WAM：接触预测、候选动作筛选与在线重规划"
        },
        {
          "paper_id": "arxiv-2608-18234",
          "team": "GigaBrain-WBC authors",
          "semantic_layers": ["state-world-model", "planning-action-generation", "wbc-contact-control", "embodiment-actuation-sysid", "deployment-safety-continual"],
          "module_focus": "行为世界模型驱动全身控制、环境交互与恢复"
        },
        {
          "paper_id": "arxiv-2608-17496",
          "team": "Calibrated Predictive Safety authors",
          "semantic_layers": ["state-world-model", "planning-action-generation", "deployment-safety-continual"],
          "module_focus": "动作条件风险排序、本体硬盾与 safe-stop/recover/replan 回退梯；仅仿真"
        },
        {
          "paper_id": "arxiv-2608-13901",
          "team": "Ontology-Grounded World Models authors",
          "semantic_layers": ["state-world-model", "planning-action-generation", "deployment-safety-continual"],
          "module_focus": "typed predicates、失败路由、修复申请与 native verifier 门控"
        },
        {
          "paper_id": "arxiv-2607-11734",
          "team": "NeuralActuator authors",
          "semantic_layers": ["sensor-encoding", "embodiment-actuation-sysid", "sim2real-adaptation"],
          "module_focus": "低成本伺服遥测、可微动力学与无传感器力感知"
        },
        {
          "paper_id": "arxiv-2607-02205",
          "team": "Actuator Reality Shaping authors",
          "semantic_layers": ["embodiment-actuation-sysid", "sim2real-adaptation"],
          "module_focus": "500Hz 学习驱动器接口与 zero-shot sim-to-real"
        },
        {
          "paper_id": "arxiv-2607-06442",
          "team": "SIEVE authors",
          "semantic_layers": ["data-production-collection", "data-curation-valuation", "planning-action-generation"],
          "module_focus": "结构感知示范选择：半量数据/步数的 VLA 训练效率对照；策略结果仅仿真"
        },
        {
          "paper_id": "arxiv-2608-09516",
          "team": "HarnessWAM authors",
          "semantic_layers": ["state-world-model", "planning-action-generation", "deployment-safety-continual"],
          "module_focus": "WAM 任务级场景信念、能力投影、进度验证与失败恢复；仅仿真，制品未开放"
        },
        {
          "paper_id": "arxiv-2608-02578",
          "team": "CoWAM authors",
          "semantic_layers": ["state-world-model", "planning-action-generation", "wbc-contact-control", "deployment-safety-continual"],
          "module_focus": "WAM 候选动作的协调契约、选择性干预与弃权回退；仅 RoboTwin 仿真，制品未开放"
        },
        {
          "paper_id": "arxiv-2608-05799",
          "team": "Institute of Automation, Chinese Academy of Sciences / FiveAges",
          "semantic_layers": ["state-world-model", "planning-action-generation", "sim2real-adaptation"],
          "module_focus": "已见/未见本体世界模型泛化、像素动作对照与适配后遗忘；仅仿真，禁止外推真机"
        },
        {
          "paper_id": "arxiv-2608-00547",
          "team": "Brigham Young University / Beijing Academy of Science and Technology",
          "semantic_layers": ["sensor-encoding", "multimodal-alignment", "state-world-model", "planning-action-generation", "sim2real-adaptation"],
          "module_focus": "oracle 视觉—触觉未来接口与动作专家消费；七任务仿真，禁止外推真机"
        },
        {
          "paper_id": "arxiv-2608-15816",
          "team": "ViTaR authors",
          "semantic_layers": ["sensor-encoding", "multimodal-alignment", "planning-action-generation", "wbc-contact-control", "sim2real-adaptation"],
          "module_focus": "冻结 VLA 上的视觉—触觉有界残差适配；作者单臂真机自证，制品未开放"
        },
        {
          "paper_id": "arxiv-2608-19574",
          "team": "Institute of Automation, Chinese Academy of Sciences / ImprintX Robotics / BAAI",
          "semantic_layers": ["sensor-encoding", "state-world-model", "planning-action-generation", "wbc-contact-control", "deployment-safety-continual"],
          "module_focus": "分层接触—形变—滑移预测、候选动作筛选与执行期撤退；单臂真机，风险未校准"
        },
        {
          "paper_id": "arxiv-2608-02365",
          "team": "Huawei Noah's Ark Lab / Celia Team / 2012 Labs",
          "semantic_layers": ["state-world-model", "planning-action-generation", "sim2real-adaptation"],
          "module_focus": "视频 DiT 表征中心 + 轻量动作头的低延迟 WAM；全仿真，制品未开放"
        },
        {
          "paper_id": "arxiv-2608-08558",
          "team": "Fudan University / CUHK-Shenzhen / Shanghai Innovation Institute",
          "semantic_layers": ["data-production-collection", "state-world-model", "planning-action-generation", "sim2real-adaptation"],
          "module_focus": "视频扩散教师+IDM离线蒸馏 WAM；Piper 双臂量化，训练栈与真实数据未闭合"
        },
        {
          "paper_id": "arxiv-2608-08839",
          "team": "HKUST(GZ) / Ola Dimensions",
          "semantic_layers": ["sensor-encoding", "multimodal-alignment", "state-world-model", "planning-action-generation", "sim2real-adaptation"],
          "module_focus": "文本落地与空间深度未来引导 WAM；Cobot 双臂，项目页 404、制品未开放"
        },
        {
          "paper_id": "arxiv-2608-04657",
          "team": "Tsinghua / SJTU / HKUST(GZ) / Adelaide / Li Auto and partners",
          "semantic_layers": ["data-production-collection", "state-world-model", "planning-action-generation", "sim2real-adaptation", "deployment-safety-continual"],
          "module_focus": "RGB-only 移动 WAM + Chain-of-Foresight；ARX Lift2 分母与代码待核验"
        },
        {
          "paper_id": "arxiv-2608-04996",
          "team": "HUST / D-Robotics / Wuhan University / Horizon Robotics",
          "semantic_layers": ["sensor-encoding", "state-world-model", "planning-action-generation", "sim2real-adaptation"],
          "module_focus": "多目标视觉未来监督与 RGB-only WAM；代码/权重可得但许可证与训练栈不完整"
        },
        {
          "paper_id": "arxiv-2604-19522",
          "team": "Skolkovo Institute of Science and Technology",
          "semantic_layers": ["data-curation-valuation", "sensor-encoding", "planning-action-generation", "wbc-contact-control", "deployment-safety-continual"],
          "module_focus": "VLM-RAG→MPC/阻抗参数；真实仅导航，双臂操作为仿真"
        }
      ]
    }
  ]
}