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  "title": "Humanoid Transfer and Adaptation of Pretrained WAM",
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      "Embodied Intelligence",
      "World Models",
      "wam",
      "Humanoid Robots",
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      {
        "paper_id": "omega_eva_envision_verify_and_act_with_latent_interactive_world_models_2026_08",
        "title": "World Models: Should We Imagine at Inference Time?",
        "url": "https://haiguangboy.com/posts/omega-eva",
        "relation": "contrast",
        "summary": "Existing ablations do not isolate the benefit of the world model prediction objective itself contradicts decomposition ablation: removing the future imagination branch drops 1.4 points and falls below the unrefined baseline, removing the proposal branch drops 2.6 points",
        "strength": "strong"
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        "paper_id": "dyna_blog_dyna_2_20260811_2026_08",
        "title": "The First Human-to-Robot Zero-Shot Transfer Scaling Law",
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        "summary": "Existing ablations do not isolate the benefit of the world model prediction objective itself contradicts route bet: the cause that makes cross-embodiment transfer emerge is world modeling (predicting future video) itself, not just data volume—the WAM architecture outperforms pure VLA",
        "strength": "strong"
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        "paper_id": "gemini_robotics_2_safety_2026_07",
        "title": "Gemini_Robotics_2_Safety",
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        "summary": "CASA provides kinematic guidance, which does not yet constitute an executability guarantee validates empirical finding: there is a clear gap between the model \"understanding constraints\" and \"acting according to constraints\"",
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        "paper_id": "jepa_wam_learning_vision_language_action_policies_with_joint_embedding_world_modeling_2026_08",
        "title": "JEPA-WAM: An Innovative Method That Makes World Models Better Understand State Changes",
        "url": "https://haiguangboy.com/posts/jepa-wam",
        "relation": "same_track",
        "summary": "The real-robot lead includes post-training differences and cannot be fully attributed to structural gains validates five ablation groups: joint objective 79.2 vs. future-only objective 77.3, preserving spatial structure vs. iREPA convolution 74.7",
        "strength": "strong"
      },
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        "paper_id": "latent_action_pretraining_through_world_modeling_2026_07",
        "title": "LAWM: Why Action Labels Become a Burden",
        "url": "https://haiguangboy.com/posts/latent_action_pretraining_through_world_modeling",
        "relation": "same_track",
        "summary": "LAWM: Why Action Labels Become a Burden",
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        "title": "N0-Foundation: Opening a New Era of Touch",
        "url": "https://haiguangboy.com/posts/mathcaln_0_foundation_towards_the_age_of_tactile_intelligence",
        "relation": "same_track",
        "summary": "N0-Foundation: Opening a New Era of Touch",
        "strength": "strong"
      }
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  "analyst_take": {
    "type": "author_opinion",
    "text": "📚 ω0 likewise focuses on the coordination of locomotion and manipulation. WholeBodyWAM focuses more on humanoid transfer of existing WAM: connecting pretrained priors, controller semantics, and coordination mechanisms so that existing manipulation capabilities gain a whole-body execution pathway.\n\n❇️ Looking back half a year later, the key is whether the structural gains can be preserved in same-data real-robot comparisons, and how much mapping and fine-tuning cost is still required when switching controllers. These two items directly test the reuse value of this adaptation path."
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  "published_at": "2026-09-17T07:23:24+08:00",
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