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  "title": "WAM Survey: How Prediction Serves Control",
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        "summary": "World prediction and action selection can be optimized separately contradicts route bet: the behavior/action part must be a unified model, opposing modular assembly",
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        "summary": "World prediction and action selection can be optimized separately contradicts core claim: what a world model should do is not assist during training, nor serve as an external simulator, but act as a verifier inside the action generation step",
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        "paper_id": "slim_05b_learning_action_grounded_predictive_latents_for_robot_manipulation_2026_08",
        "title": "Lower Prediction Error, but the Representation Has Already Collapsed",
        "url": "https://haiguangboy.com/posts/slim-05b",
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        "summary": "Neural simulators can support closed-loop policy improvement contradicts core claim: future prediction should be a training signal that shapes representations, not the model's output",
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        "url": "https://haiguangboy.com/posts/d4rt_efficiently_reconstructing_dynamic_scenes_one",
        "relation": "same_track",
        "summary": "2D video prediction does not automatically guarantee 3D and multi-view consistency validates D4RT output is relative/up-to-scale, not metric—this is the crux for embodied 3D data sources",
        "strength": "strong"
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    "text": "💡 Looking at it together with OpenWAM\nIn its evaluation, OpenWAM found that without embodied pretraining, unidirectional information flow is slightly superior; after adding pretraining, the advantages of bidirectional interaction emerge. This adds a condition to the survey's classification: architectural pros and cons change with pretraining conditions, and one cannot pick a side based solely on \"unified\" or \"decoupled.\"\n\nLooking back half a year later, what is worth testing is: with fixed data and compute budgets, can separately optimizing the world and the policy reduce real-world execution degradation caused by model bias? This result is what helps judge the value of separate optimization."
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  "published_at": "2026-09-18T08:26:27+08:00",
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