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  "edition_id": "mp-2026-08-29-morning-0051",
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  "edition_number": 51,
  "edition_label": "Morning edition",
  "status": "published",
  "revision": 1,
  "published_at": "2026-08-29T09:00:00.000-04:00",
  "modified_at": "2026-08-29T09:00:00.000-04:00",
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  "lead_story_id": "mp-2026-08-29-001",
  "lead_summary": "Evolution-strategy post-training improved first-answer accuracy while preserving broader reasoning coverage than GRPO in the reported comparisons.",
  "coverage_window": {
    "start": "2026-08-27T04:34:53.000-04:00",
    "end": "2026-08-29T08:24:00.000-04:00"
  },
  "story_count": 27,
  "stories": [
    {
      "story_id": "mp-2026-08-29-001",
      "source_story_id": "tmp-lead-evolution-strategies-coverage",
      "edition_id": "mp-2026-08-29-morning-0051",
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      "position": 1,
      "story_type": "lead",
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      "headline": "The Population Kept More Ways to Be Right",
      "slug": "the-population-kept-more-ways-to-be-right",
      "dek": "Evolution-strategy post-training improved first-answer accuracy while preserving broader reasoning coverage than GRPO in the reported comparisons.",
      "summary": "Evolution-strategy post-training improved first-answer accuracy while preserving broader reasoning coverage than GRPO in the reported comparisons.",
      "body_text": "The study separates success on the most likely answer from coverage across multiple attempts. Its authors report that evolution strategies increased Pass@1 while retaining higher Pass@K than GRPO, whose sampled reasoning diversity narrowed during training. A sequential GRPO-then-ES schedule combined the two tendencies. The paper also found that task gains came from a sparse subset of larger parameter updates despite broad movement across the model. These are author-reported experiments and theory on selected models and tasks, not evidence that evolution strategies dominate every reasoning workload.",
      "why_it_matters": "Evolution-strategy post-training improved first-answer accuracy while preserving broader reasoning coverage than GRPO in the reported comparisons.",
      "limitations": [
        "These are author-reported experiments and theory on selected models and tasks, not evidence that evolution strategies dominate every reasoning workload."
      ],
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      "canonical_url": "https://themachinepress.com/story/mp-2026-08-29-001/the-population-kept-more-ways-to-be-right",
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      "first_published_at": "2026-08-29T09:00:00.000-04:00",
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          "text": "Evolution-strategy post-training improved first-answer accuracy while preserving broader reasoning coverage than GRPO in the reported comparisons.",
          "source_ids": [
            "source-2026-08-29-001"
          ],
          "qualification": "These are author-reported experiments and theory on selected models and tasks, not evidence that evolution strategies dominate every reasoning workload."
        }
      ],
      "source_ids": [
        "source-2026-08-29-001"
      ],
      "tags": [
        "reasoning models",
        "evolution strategies",
        "post-training"
      ],
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    {
      "story_id": "mp-2026-08-29-002",
      "source_story_id": "tmp-feature-parallel-reasoning-systems",
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      "position": 2,
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      "headline": "Reasoning Training Became a Systems Problem",
      "slug": "reasoning-training-became-a-systems-problem",
      "dek": "A compute-centered survey maps how reinforcement-learning post-training turns multiple models, memory paths and asynchronous stages into one distributed workload.",
      "summary": "A compute-centered survey maps how reinforcement-learning post-training turns multiple models, memory paths and asynchronous stages into one distributed workload.",
      "body_text": "The paper systematizes PPO, GRPO and related post-training pipelines through the work-depth model of parallel computing. Its taxonomy spans familiar data, tensor, pipeline, sequence, context and expert parallelism alongside disaggregated placement, stage fusion, hybrid layouts and asynchronous execution. The central argument is architectural: reasoning-model training couples generation, reward, inference and optimization so tightly that algorithm choices cannot be separated from placement and communication costs. This is a synthesis and set of design guidelines, not a measured claim that one framework or topology is universally fastest.",
      "why_it_matters": "A compute-centered survey maps how reinforcement-learning post-training turns multiple models, memory paths and asynchronous stages into one distributed workload.",
      "limitations": [
        "The central argument is architectural: reasoning-model training couples generation, reward, inference and optimization so tightly that algorithm choices cannot be separated from placement and communication costs.",
        "This is a synthesis and set of design guidelines, not a measured claim that one framework or topology is universally fastest."
      ],
      "importance": 9,
      "canonical_url": "https://themachinepress.com/story/mp-2026-08-29-002/reasoning-training-became-a-systems-problem",
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      "first_published_at": "2026-08-29T09:00:00.000-04:00",
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          "text": "A compute-centered survey maps how reinforcement-learning post-training turns multiple models, memory paths and asynchronous stages into one distributed workload.",
          "source_ids": [
            "source-2026-08-29-002"
          ],
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        }
      ],
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      "tags": [
        "reasoning models",
        "distributed systems",
        "reinforcement learning"
      ],
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      "story_id": "mp-2026-08-29-003",
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      "headline": "One Realized Token Removed Most of the Blindness",
      "slug": "one-realized-token-removed-most-of-the-blindness",
      "dek": "A new information floor separates unavoidable rejection in parallel token drafting from errors caused by the draft model itself.",
      "summary": "A new information floor separates unavoidable rejection in parallel token drafting from errors caused by the draft model itself.",
      "body_text": "Across four domains and five targets, the authors report that the final position in an all-parallel block faced a substantial unavoidable rejection floor. Revealing one earlier token removed 86 to 100 percent of that floor, while current drafters still sat well above the theoretical limit. The decomposition turns accepted length into two distinct engineering targets: short-range conditioning and proposal quality.",
      "why_it_matters": "A new information floor separates unavoidable rejection in parallel token drafting from errors caused by the draft model itself.",
      "limitations": [],
      "importance": 8,
      "canonical_url": "https://themachinepress.com/story/mp-2026-08-29-003/one-realized-token-removed-most-of-the-blindness",
      "json_url": "https://themachinepress.com/story/mp-2026-08-29-003.json",
      "first_published_at": "2026-08-29T09:00:00.000-04:00",
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          "text": "A new information floor separates unavoidable rejection in parallel token drafting from errors caused by the draft model itself.",
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            "source-2026-08-29-003"
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          "qualification": null
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      ],
      "source_ids": [
        "source-2026-08-29-003"
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      "tags": [
        "speculative decoding",
        "attention",
        "inference"
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      "story_id": "mp-2026-08-29-004",
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      "headline": "Ten Simulated Qubits Joined the Ultrasound Classifier",
      "slug": "ten-simulated-qubits-joined-the-ultrasound-classifier",
      "dek": "QuantumBoostNet switches between classical and quantum heads while learning cardiac ultrasound views.",
      "summary": "QuantumBoostNet switches between classical and quantum heads while learning cardiac ultrasound views.",
      "body_text": "The hybrid architecture uses a classical backbone and a parametrized ten-qubit circuit, with a loss-driven mixing parameter controlling the transition between its two heads. The authors report better view-identification performance than tested classical and hybrid baselines and greater robustness to noise. The work relies on simulated qubits and benchmark evaluation; it is not clinical validation or evidence of improved patient outcomes.",
      "why_it_matters": "QuantumBoostNet switches between classical and quantum heads while learning cardiac ultrasound views.",
      "limitations": [
        "The work relies on simulated qubits and benchmark evaluation; it is not clinical validation or evidence of improved patient outcomes."
      ],
      "importance": 7,
      "canonical_url": "https://themachinepress.com/story/mp-2026-08-29-004/ten-simulated-qubits-joined-the-ultrasound-classifier",
      "json_url": "https://themachinepress.com/story/mp-2026-08-29-004.json",
      "first_published_at": "2026-08-29T09:00:00.000-04:00",
      "modified_at": "2026-08-29T09:00:00.000-04:00",
      "content_status": "new",
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      "carryover_reason": null,
      "key_claims": [
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          "claim_id": "claim-mp-2026-08-29-004-001",
          "text": "QuantumBoostNet switches between classical and quantum heads while learning cardiac ultrasound views.",
          "source_ids": [
            "source-2026-08-29-004"
          ],
          "qualification": "The work relies on simulated qubits and benchmark evaluation; it is not clinical validation or evidence of improved patient outcomes."
        }
      ],
      "source_ids": [
        "source-2026-08-29-004"
      ],
      "tags": [
        "medical imaging",
        "quantum machine learning",
        "ultrasound"
      ],
      "image_url": null,
      "corrections": []
    },
    {
      "story_id": "mp-2026-08-29-005",
      "source_story_id": "tmp-story-mm-spectrum-routing",
      "edition_id": "mp-2026-08-29-morning-0051",
      "edition_url": "https://themachinepress.com/edition/2026-08-29",
      "position": 5,
      "story_type": "dispatch",
      "section": "research",
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      "headline": "Each Spectrum Told the Router What Kind It Was",
      "slug": "each-spectrum-told-the-router-what-kind-it-was",
      "dek": "MM-Spectrum gives a sparse mixture-of-experts router explicit modality identity before combining heterogeneous molecular measurements.",
      "summary": "MM-Spectrum gives a sparse mixture-of-experts router explicit modality identity before combining heterogeneous molecular measurements.",
      "body_text": "The model adds modality-aware routing, shared experts, interaction experts and unequal expert capacities to balance complementary spectra. Its authors report consistent gains across full-modality, bimodal and missing-modality molecular-structure tasks, supported by ablations and interpretability analysis. Those benchmark results do not establish a molecule in a laboratory.",
      "why_it_matters": "MM-Spectrum gives a sparse mixture-of-experts router explicit modality identity before combining heterogeneous molecular measurements.",
      "limitations": [
        "Those benchmark results do not establish a molecule in a laboratory."
      ],
      "importance": 8,
      "canonical_url": "https://themachinepress.com/story/mp-2026-08-29-005/each-spectrum-told-the-router-what-kind-it-was",
      "json_url": "https://themachinepress.com/story/mp-2026-08-29-005.json",
      "first_published_at": "2026-08-29T09:00:00.000-04:00",
      "modified_at": "2026-08-29T09:00:00.000-04:00",
      "content_status": "new",
      "is_carryover": false,
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          "text": "MM-Spectrum gives a sparse mixture-of-experts router explicit modality identity before combining heterogeneous molecular measurements.",
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            "source-2026-08-29-005"
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          "qualification": "Those benchmark results do not establish a molecule in a laboratory."
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      ],
      "source_ids": [
        "source-2026-08-29-005"
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      "tags": [
        "molecular structure",
        "mixture of experts",
        "spectroscopy"
      ],
      "image_url": null,
      "corrections": []
    },
    {
      "story_id": "mp-2026-08-29-006",
      "source_story_id": "tmp-story-leon-latent-evolution",
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      "edition_url": "https://themachinepress.com/edition/2026-08-29",
      "position": 6,
      "story_type": "dispatch",
      "section": "robotics",
      "editorial_classification": "editorial",
      "headline": "The World Model Learned an Evolution Operator",
      "slug": "the-world-model-learned-an-evolution-operator",
      "dek": "LEON replaces a generic latent transition predictor with context-modulated operator propagation and an additive forcing path.",
      "summary": "LEON replaces a generic latent transition predictor with context-modulated operator propagation and an additive forcing path.",
      "body_text": "The architecture draws on controlled Koopman dynamics to distinguish persistent evolution from additive change inside latent world-action models. Across two policy integrations, the authors report stronger closed-loop performance and robustness even when LEON fully replaced the baseline transition component. The evidence comes from controlled systems and robotics benchmarks, not deployment in an uncontrolled physical environment.",
      "why_it_matters": "LEON replaces a generic latent transition predictor with context-modulated operator propagation and an additive forcing path.",
      "limitations": [
        "The evidence comes from controlled systems and robotics benchmarks, not deployment in an uncontrolled physical environment."
      ],
      "importance": 8,
      "canonical_url": "https://themachinepress.com/story/mp-2026-08-29-006/the-world-model-learned-an-evolution-operator",
      "json_url": "https://themachinepress.com/story/mp-2026-08-29-006.json",
      "first_published_at": "2026-08-29T09:00:00.000-04:00",
      "modified_at": "2026-08-29T09:00:00.000-04:00",
      "content_status": "new",
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      "carryover_reason": null,
      "key_claims": [
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          "text": "LEON replaces a generic latent transition predictor with context-modulated operator propagation and an additive forcing path.",
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            "source-2026-08-29-006"
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          "qualification": "The evidence comes from controlled systems and robotics benchmarks, not deployment in an uncontrolled physical environment."
        }
      ],
      "source_ids": [
        "source-2026-08-29-006"
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      "tags": [
        "world models",
        "robot policies",
        "dynamics"
      ],
      "image_url": null,
      "corrections": []
    },
    {
      "story_id": "mp-2026-08-29-007",
      "source_story_id": "tmp-story-circuit-condensation",
      "edition_id": "mp-2026-08-29-morning-0051",
      "edition_url": "https://themachinepress.com/edition/2026-08-29",
      "position": 7,
      "story_type": "dispatch",
      "section": "research",
      "editorial_classification": "editorial",
      "headline": "Post-Training Compressed the Causal Circuit",
      "slug": "post-training-compressed-the-causal-circuit",
      "dek": "Circuit Condensation prunes low-attribution edges and retrains through what remains, accepting cuts only when behavior and general capability survive.",
      "summary": "Circuit Condensation prunes low-attribution edges and retrains through what remains, accepting cuts only when behavior and general capability survive.",
      "body_text": "Across four behaviors and eight models, condensed circuits were smaller than the strongest frozen-discovery baseline in 30 of 32 settings, by 8.1 times on average and as much as 316 times. Exhaustive subset tests found some circuits irreducible and others still carrying removable edges. The result offers more inspectable mechanisms, but only for the studied behaviors and models.",
      "why_it_matters": "Circuit Condensation prunes low-attribution edges and retrains through what remains, accepting cuts only when behavior and general capability survive.",
      "limitations": [
        "The result offers more inspectable mechanisms, but only for the studied behaviors and models."
      ],
      "importance": 9,
      "canonical_url": "https://themachinepress.com/story/mp-2026-08-29-007/post-training-compressed-the-causal-circuit",
      "json_url": "https://themachinepress.com/story/mp-2026-08-29-007.json",
      "first_published_at": "2026-08-29T09:00:00.000-04:00",
      "modified_at": "2026-08-29T09:00:00.000-04:00",
      "content_status": "new",
      "is_carryover": false,
      "carryover_reason": null,
      "key_claims": [
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          "text": "Circuit Condensation prunes low-attribution edges and retrains through what remains, accepting cuts only when behavior and general capability survive.",
          "source_ids": [
            "source-2026-08-29-007"
          ],
          "qualification": "The result offers more inspectable mechanisms, but only for the studied behaviors and models."
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      ],
      "source_ids": [
        "source-2026-08-29-007"
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      "tags": [
        "interpretability",
        "causal circuits",
        "post-training"
      ],
      "image_url": null,
      "corrections": []
    },
    {
      "story_id": "mp-2026-08-29-008",
      "source_story_id": "tmp-story-halo-open-set-imu",
      "edition_id": "mp-2026-08-29-morning-0051",
      "edition_url": "https://themachinepress.com/edition/2026-08-29",
      "position": 8,
      "story_type": "dispatch",
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      "headline": "The Sensor Description Became Part of the Signal",
      "slug": "the-sensor-description-became-part-of-the-signal",
      "dek": "HALO conditions inertial channels on natural-language descriptions and aligns the resulting representation with activity labels.",
      "summary": "HALO conditions inertial channels on natural-language descriptions and aligns the resulting representation with activity labels.",
      "body_text": "Trained on ten datasets and tested on seven held-out sets, the 35-million-parameter model led five baselines on all eight aggregate metrics and improved a broad zero-shot measure by 13.7 percentage points. Yet HALO and every comparator collapsed on two further datasets with severe distribution shift, an important limit on the open-set claim.",
      "why_it_matters": "HALO conditions inertial channels on natural-language descriptions and aligns the resulting representation with activity labels.",
      "limitations": [],
      "importance": 8,
      "canonical_url": "https://themachinepress.com/story/mp-2026-08-29-008/the-sensor-description-became-part-of-the-signal",
      "json_url": "https://themachinepress.com/story/mp-2026-08-29-008.json",
      "first_published_at": "2026-08-29T09:00:00.000-04:00",
      "modified_at": "2026-08-29T09:00:00.000-04:00",
      "content_status": "new",
      "is_carryover": false,
      "carryover_reason": null,
      "key_claims": [
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          "text": "HALO conditions inertial channels on natural-language descriptions and aligns the resulting representation with activity labels.",
          "source_ids": [
            "source-2026-08-29-008"
          ],
          "qualification": null
        }
      ],
      "source_ids": [
        "source-2026-08-29-008"
      ],
      "tags": [
        "wearables",
        "activity recognition",
        "foundation models"
      ],
      "image_url": "https://themachinepress.com/issues/2026-08-29/halo-wireframe-file.webp",
      "corrections": []
    },
    {
      "story_id": "mp-2026-08-29-009",
      "source_story_id": "tmp-story-tracebench-root-cause",
      "edition_id": "mp-2026-08-29-morning-0051",
      "edition_url": "https://themachinepress.com/edition/2026-08-29",
      "position": 9,
      "story_type": "dispatch",
      "section": "benchmarks-evals",
      "editorial_classification": "editorial",
      "headline": "The Agent Read the Numbers Before It Drew the Plot",
      "slug": "the-agent-read-the-numbers-before-it-drew-the-plot",
      "dek": "TraceBench generates controlled physical time series so root-cause attribution can be tested against known parameter changes.",
      "summary": "TraceBench generates controlled physical time series so root-cause attribution can be tested against known parameter changes.",
      "body_text": "Four evaluated agents benefited substantially from domain context and explored data mainly through numerical console output rather than visualizations. They also performed worse when asked to write a reusable sample-to-label Python program than when submitting predictions directly. The released simulations, trajectories and leaderboard make these behavioral differences auditable.",
      "why_it_matters": "TraceBench generates controlled physical time series so root-cause attribution can be tested against known parameter changes.",
      "limitations": [],
      "importance": 8,
      "canonical_url": "https://themachinepress.com/story/mp-2026-08-29-009/the-agent-read-the-numbers-before-it-drew-the-plot",
      "json_url": "https://themachinepress.com/story/mp-2026-08-29-009.json",
      "first_published_at": "2026-08-29T09:00:00.000-04:00",
      "modified_at": "2026-08-29T09:00:00.000-04:00",
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      "carryover_reason": null,
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          "text": "TraceBench generates controlled physical time series so root-cause attribution can be tested against known parameter changes.",
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            "source-2026-08-29-009"
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          "qualification": null
        }
      ],
      "source_ids": [
        "source-2026-08-29-009"
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      "tags": [
        "agents",
        "root cause analysis",
        "time series"
      ],
      "image_url": null,
      "corrections": []
    },
    {
      "story_id": "mp-2026-08-29-010",
      "source_story_id": "tmp-story-diffusion-crowd-navigation",
      "edition_id": "mp-2026-08-29-morning-0051",
      "edition_url": "https://themachinepress.com/edition/2026-08-29",
      "position": 10,
      "story_type": "dispatch",
      "section": "robotics",
      "editorial_classification": "editorial",
      "headline": "The Robot Planned Five Steps Into the Crowd",
      "slug": "the-robot-planned-five-steps-into-the-crowd",
      "dek": "A diffusion policy generates short action chunks, then executes them in a receding horizon for dense crowd navigation.",
      "summary": "A diffusion policy generates short action chunks, then executes them in a receding horizon for dense crowd navigation.",
      "body_text": "PDPO combines offline demonstrations with online PPO and treats denoising as an internal decision process. The authors report better success than tested baselines and find that action chunks matter especially when benchmark boundaries count as collisions. That boundary change closes an artifact that otherwise let agents escape the valid domain instead of navigating through it.",
      "why_it_matters": "A diffusion policy generates short action chunks, then executes them in a receding horizon for dense crowd navigation.",
      "limitations": [],
      "importance": 7,
      "canonical_url": "https://themachinepress.com/story/mp-2026-08-29-010/the-robot-planned-five-steps-into-the-crowd",
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      "first_published_at": "2026-08-29T09:00:00.000-04:00",
      "modified_at": "2026-08-29T09:00:00.000-04:00",
      "content_status": "new",
      "is_carryover": false,
      "carryover_reason": null,
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        {
          "claim_id": "claim-mp-2026-08-29-010-001",
          "text": "A diffusion policy generates short action chunks, then executes them in a receding horizon for dense crowd navigation.",
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            "source-2026-08-29-010"
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      ],
      "source_ids": [
        "source-2026-08-29-010"
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      "tags": [
        "crowd navigation",
        "diffusion policies",
        "robotics"
      ],
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      "corrections": []
    },
    {
      "story_id": "mp-2026-08-29-011",
      "source_story_id": "tmp-story-bee-path-reconstruction",
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      "position": 11,
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      "headline": "Thirty-Eight Milligrams Carried a Landscape-Scale Track",
      "slug": "thirty-eight-milligrams-carried-a-landscape-scale-track",
      "dek": "Rotating high-gain transmitters and probabilistic inference reconstruct paths for receivers too small and power-limited for satellite navigation.",
      "summary": "Rotating high-gain transmitters and probabilistic inference reconstruct paths for receivers too small and power-limited for satellite navigation.",
      "body_text": "The reported system tracked 38-milligram receivers over a scalable landscape using sparse signal-strength measurements, reaching about 15-meter accuracy below 180 microwatts and about 10 meters below 600 microwatts. A bee-return-flight demonstration grounds the method, though accuracy and range remain dependent on the tested landscape and radio setup.",
      "why_it_matters": "Rotating high-gain transmitters and probabilistic inference reconstruct paths for receivers too small and power-limited for satellite navigation.",
      "limitations": [
        "A bee-return-flight demonstration grounds the method, though accuracy and range remain dependent on the tested landscape and radio setup."
      ],
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      "first_published_at": "2026-08-29T09:00:00.000-04:00",
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          "text": "Rotating high-gain transmitters and probabilistic inference reconstruct paths for receivers too small and power-limited for satellite navigation.",
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            "source-2026-08-29-011"
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          "qualification": "A bee-return-flight demonstration grounds the method, though accuracy and range remain dependent on the tested landscape and radio setup."
        }
      ],
      "source_ids": [
        "source-2026-08-29-011"
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      "tags": [
        "bee tracking",
        "low-power sensing",
        "probabilistic modeling"
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    },
    {
      "story_id": "mp-2026-08-29-012",
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      "position": 12,
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      "headline": "The Higher Goal Reweighted the Lower Ones",
      "slug": "the-higher-goal-reweighted-the-lower-ones",
      "dek": "A reinforcement-learning controller generates state-dependent preferences among competing objectives instead of fixing their weights in advance.",
      "summary": "A reinforcement-learning controller generates state-dependent preferences among competing objectives instead of fixing their weights in advance.",
      "body_text": "The framework pairs a multi-objective inner controller with an outer preference generator trained on a higher-level goal. In constructed exploration environments, the learned preferences switched priorities by context, made graded trade-offs and persisted over time while outperforming fixed and handcrafted strategies. The paper defines a computational mechanism inspired by emotion; it does not demonstrate feelings or subjective experience.",
      "why_it_matters": "A reinforcement-learning controller generates state-dependent preferences among competing objectives instead of fixing their weights in advance.",
      "limitations": [
        "The paper defines a computational mechanism inspired by emotion; it does not demonstrate feelings or subjective experience."
      ],
      "importance": 7,
      "canonical_url": "https://themachinepress.com/story/mp-2026-08-29-012/the-higher-goal-reweighted-the-lower-ones",
      "json_url": "https://themachinepress.com/story/mp-2026-08-29-012.json",
      "first_published_at": "2026-08-29T09:00:00.000-04:00",
      "modified_at": "2026-08-29T09:00:00.000-04:00",
      "content_status": "new",
      "is_carryover": false,
      "carryover_reason": null,
      "key_claims": [
        {
          "claim_id": "claim-mp-2026-08-29-012-001",
          "text": "A reinforcement-learning controller generates state-dependent preferences among competing objectives instead of fixing their weights in advance.",
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            "source-2026-08-29-012"
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          "qualification": "The paper defines a computational mechanism inspired by emotion; it does not demonstrate feelings or subjective experience."
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        "source-2026-08-29-012"
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      "tags": [
        "multi-objective RL",
        "agent goals",
        "preference regulation"
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    {
      "story_id": "mp-2026-08-29-013",
      "source_story_id": "tmp-story-fiuni-task-free-learning",
      "edition_id": "mp-2026-08-29-morning-0051",
      "edition_url": "https://themachinepress.com/edition/2026-08-29",
      "position": 13,
      "story_type": "dispatch",
      "section": "frontier-models",
      "editorial_classification": "editorial",
      "headline": "The Fisher Subspace Decided Whether the Task Was New",
      "slug": "the-fisher-subspace-decided-whether-the-task-was-new",
      "dek": "FiUni detects latent task changes batch by batch, then reuses, expands or creates low-rank adaptation subspaces.",
      "summary": "FiUni detects latent task changes batch by batch, then reuses, expands or creates low-rank adaptation subspaces.",
      "body_text": "The method compares principal subspaces from a Kronecker-factored Fisher approximation and freezes historical structure to balance knowledge sharing against isolation. The authors report competitive results against task-aware continual-learning methods with fewer trainable parameters, despite receiving no explicit task boundary at training time. The evidence is benchmark-based and does not remove all forgetting risk.",
      "why_it_matters": "FiUni detects latent task changes batch by batch, then reuses, expands or creates low-rank adaptation subspaces.",
      "limitations": [
        "The evidence is benchmark-based and does not remove all forgetting risk."
      ],
      "importance": 8,
      "canonical_url": "https://themachinepress.com/story/mp-2026-08-29-013/the-fisher-subspace-decided-whether-the-task-was-new",
      "json_url": "https://themachinepress.com/story/mp-2026-08-29-013.json",
      "first_published_at": "2026-08-29T09:00:00.000-04:00",
      "modified_at": "2026-08-29T09:00:00.000-04:00",
      "content_status": "new",
      "is_carryover": false,
      "carryover_reason": null,
      "key_claims": [
        {
          "claim_id": "claim-mp-2026-08-29-013-001",
          "text": "FiUni detects latent task changes batch by batch, then reuses, expands or creates low-rank adaptation subspaces.",
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            "source-2026-08-29-013"
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        }
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        "source-2026-08-29-013"
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        "continual learning",
        "LoRA",
        "catastrophic forgetting"
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    {
      "story_id": "mp-2026-08-29-014",
      "source_story_id": "tmp-story-silent-speech-hand-interface",
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      "position": 14,
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      "headline": "Silent Speech Moved From the Face to the Hand",
      "slug": "silent-speech-moved-from-the-face-to-the-hand",
      "dek": "A soft fingertip electrode samples muscle signals near the lips only when the wearer chooses to speak silently.",
      "summary": "A soft fingertip electrode samples muscle signals near the lips only when the wearer chooses to speak silently.",
      "body_text": "The interface combines liquid-metal connections, flexible transparent electrodes and elastomer encapsulation. A neural classifier averaged 97.2 percent across three subjects on a 30-word vocabulary, and the authors demonstrated real-time drone control. The small participant count and restricted vocabulary make this an early interface result, not a general speech-recognition claim.",
      "why_it_matters": "A soft fingertip electrode samples muscle signals near the lips only when the wearer chooses to speak silently.",
      "limitations": [
        "The small participant count and restricted vocabulary make this an early interface result, not a general speech-recognition claim."
      ],
      "importance": 8,
      "canonical_url": "https://themachinepress.com/story/mp-2026-08-29-014/silent-speech-moved-from-the-face-to-the-hand",
      "json_url": "https://themachinepress.com/story/mp-2026-08-29-014.json",
      "first_published_at": "2026-08-29T09:00:00.000-04:00",
      "modified_at": "2026-08-29T09:00:00.000-04:00",
      "content_status": "new",
      "is_carryover": false,
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      "key_claims": [
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          "text": "A soft fingertip electrode samples muscle signals near the lips only when the wearer chooses to speak silently.",
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          "qualification": "The small participant count and restricted vocabulary make this an early interface result, not a general speech-recognition claim."
        }
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      "source_ids": [
        "source-2026-08-29-014"
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      "tags": [
        "silent speech",
        "wearable interface",
        "electromyography"
      ],
      "image_url": null,
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    },
    {
      "story_id": "mp-2026-08-29-026",
      "source_story_id": "tmp-story-dpo-scale-entanglement",
      "edition_id": "mp-2026-08-29-morning-0051",
      "edition_url": "https://themachinepress.com/edition/2026-08-29",
      "position": 15,
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      "headline": "One DPO Knob Was Turning Two Things",
      "slug": "one-dpo-knob-was-turning-two-things",
      "dek": "The usual beta coefficient controls both preference-noise scale and optimization dynamics, making policy movement non-monotonic at a fixed learning rate.",
      "summary": "The usual beta coefficient controls both preference-noise scale and optimization dynamics, making policy movement non-monotonic at a fixed learning rate.",
      "body_text": "The analysis shows a small-beta dead zone, an intermediate peak in policy deviation and a decline at larger values; similar-looking loss curves can hide several-fold differences in distance from the reference model. A centered-softplus reformulation separates the two roles while retaining the same optimum for positive beta.",
      "why_it_matters": "The usual beta coefficient controls both preference-noise scale and optimization dynamics, making policy movement non-monotonic at a fixed learning rate.",
      "limitations": [],
      "importance": 8,
      "canonical_url": "https://themachinepress.com/story/mp-2026-08-29-026/one-dpo-knob-was-turning-two-things",
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      "first_published_at": "2026-08-29T09:00:00.000-04:00",
      "modified_at": "2026-08-29T09:00:00.000-04:00",
      "content_status": "new",
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          "text": "The usual beta coefficient controls both preference-noise scale and optimization dynamics, making policy movement non-monotonic at a fixed learning rate.",
          "source_ids": [
            "source-2026-08-29-015"
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      "source_ids": [
        "source-2026-08-29-015"
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      "tags": [
        "preference optimization",
        "alignment",
        "training dynamics"
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    },
    {
      "story_id": "mp-2026-08-29-027",
      "source_story_id": "tmp-story-human-ai-text-front-rail",
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      "edition_url": "https://themachinepress.com/edition/2026-08-29",
      "position": 16,
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      "section": "safety",
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      "headline": "More Human Examples Made the Machine Distribution Harder to See",
      "slug": "more-human-examples-made-the-machine-distribution-harder-to-see",
      "dek": "A theoretical analysis shows repeated paraphrasing can move machine-written responses toward an empirical human-writing distribution.",
      "summary": "A theoretical analysis shows repeated paraphrasing can move machine-written responses toward an empirical human-writing distribution.",
      "body_text": "Under stated mixing and stability assumptions, the paper derives a convergence rate and describes how the needed human samples and paraphrasing rounds scale with the target error. The result characterizes a strategic evasion process in a controlled multi-sample setting; it does not prove that all AI text is presently undetectable.",
      "why_it_matters": "A theoretical analysis shows repeated paraphrasing can move machine-written responses toward an empirical human-writing distribution.",
      "limitations": [
        "The result characterizes a strategic evasion process in a controlled multi-sample setting; it does not prove that all AI text is presently undetectable."
      ],
      "importance": 7,
      "canonical_url": "https://themachinepress.com/story/mp-2026-08-29-027/more-human-examples-made-the-machine-distribution-harder-to-see",
      "json_url": "https://themachinepress.com/story/mp-2026-08-29-027.json",
      "first_published_at": "2026-08-29T09:00:00.000-04:00",
      "modified_at": "2026-08-29T09:00:00.000-04:00",
      "content_status": "new",
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          "text": "A theoretical analysis shows repeated paraphrasing can move machine-written responses toward an empirical human-writing distribution.",
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          "qualification": "The result characterizes a strategic evasion process in a controlled multi-sample setting; it does not prove that all AI text is presently undetectable."
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      ],
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      "tags": [
        "AI text detection",
        "paraphrasing",
        "provenance"
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      "image_url": null,
      "corrections": []
    },
    {
      "story_id": "mp-2026-08-29-015",
      "source_story_id": "tmp-sidebar-clusterattention",
      "edition_id": "mp-2026-08-29-morning-0051",
      "edition_url": "https://themachinepress.com/edition/2026-08-29",
      "position": 17,
      "story_type": "ticker",
      "section": "infrastructure",
      "editorial_classification": "editorial",
      "headline": "Attention Clustered Once, Then Ran Sparse",
      "slug": "attention-clustered-once-then-ran-sparse",
      "dek": "ClusterAttention uses fast per-head recursive clustering and centroid compensation without retraining or offline calibration.",
      "summary": "ClusterAttention uses fast per-head recursive clustering and centroid compensation without retraining or offline calibration.",
      "body_text": "The authors report two-to-six-times speedups on a tabular foundation model while retaining at least 99 percent of dense accuracy, plus a 1.8-times video-generation speedup with outputs closer to dense attention than a tested specialist method.",
      "why_it_matters": "ClusterAttention uses fast per-head recursive clustering and centroid compensation without retraining or offline calibration.",
      "limitations": [],
      "importance": 7,
      "canonical_url": "https://themachinepress.com/story/mp-2026-08-29-015/attention-clustered-once-then-ran-sparse",
      "json_url": "https://themachinepress.com/story/mp-2026-08-29-015.json",
      "first_published_at": "2026-08-29T09:00:00.000-04:00",
      "modified_at": "2026-08-29T09:00:00.000-04:00",
      "content_status": "new",
      "is_carryover": false,
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          "text": "ClusterAttention uses fast per-head recursive clustering and centroid compensation without retraining or offline calibration.",
          "source_ids": [
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          "qualification": null
        }
      ],
      "source_ids": [
        "source-2026-08-29-017"
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      "tags": [
        "sparse attention",
        "inference",
        "GPU"
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      "image_url": null,
      "corrections": []
    },
    {
      "story_id": "mp-2026-08-29-016",
      "source_story_id": "tmp-sidebar-ecg-pseudo-multimodal",
      "edition_id": "mp-2026-08-29-morning-0051",
      "edition_url": "https://themachinepress.com/edition/2026-08-29",
      "position": 18,
      "story_type": "ticker",
      "section": "research",
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      "headline": "Twelve ECG Leads Became a Graph and an Image",
      "slug": "twelve-ecg-leads-became-a-graph-and-an-image",
      "dek": "Graph-CMMC aligns waveforms with image-like transforms while modeling relationships among all twelve leads.",
      "summary": "Graph-CMMC aligns waveforms with image-like transforms while modeling relationships among all twelve leads.",
      "body_text": "On a coronary-occlusion classification task, the self-supervised representation performed competitively with tested supervised methods. The result concerns representation learning, not clinical diagnosis or treatment.",
      "why_it_matters": "Graph-CMMC aligns waveforms with image-like transforms while modeling relationships among all twelve leads.",
      "limitations": [
        "The result concerns representation learning, not clinical diagnosis or treatment."
      ],
      "importance": 6,
      "canonical_url": "https://themachinepress.com/story/mp-2026-08-29-016/twelve-ecg-leads-became-a-graph-and-an-image",
      "json_url": "https://themachinepress.com/story/mp-2026-08-29-016.json",
      "first_published_at": "2026-08-29T09:00:00.000-04:00",
      "modified_at": "2026-08-29T09:00:00.000-04:00",
      "content_status": "new",
      "is_carryover": false,
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          "text": "Graph-CMMC aligns waveforms with image-like transforms while modeling relationships among all twelve leads.",
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            "source-2026-08-29-018"
          ],
          "qualification": "The result concerns representation learning, not clinical diagnosis or treatment."
        }
      ],
      "source_ids": [
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      "tags": [
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        "contrastive learning",
        "graphs"
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      "image_url": null,
      "corrections": []
    },
    {
      "story_id": "mp-2026-08-29-017",
      "source_story_id": "tmp-sidebar-householder-adversarial",
      "edition_id": "mp-2026-08-29-morning-0051",
      "edition_url": "https://themachinepress.com/edition/2026-08-29",
      "position": 19,
      "story_type": "ticker",
      "section": "safety",
      "editorial_classification": "editorial",
      "headline": "Adversarial Training Dropped the Input Gradients",
      "slug": "adversarial-training-dropped-the-input-gradients",
      "dek": "A low-rank Householder expansion finds local perturbation directions from the forward pass.",
      "summary": "A low-rank Householder expansion finds local perturbation directions from the forward pass.",
      "body_text": "The reported regularizer cost the equivalent of 2.8 PGD steps per epoch and matched stronger iterative training only within limited relative perturbation budgets, falling away beyond the local regime.",
      "why_it_matters": "A low-rank Householder expansion finds local perturbation directions from the forward pass.",
      "limitations": [
        "The reported regularizer cost the equivalent of 2.8 PGD steps per epoch and matched stronger iterative training only within limited relative perturbation budgets, falling away beyond the local regime."
      ],
      "importance": 7,
      "canonical_url": "https://themachinepress.com/story/mp-2026-08-29-017/adversarial-training-dropped-the-input-gradients",
      "json_url": "https://themachinepress.com/story/mp-2026-08-29-017.json",
      "first_published_at": "2026-08-29T09:00:00.000-04:00",
      "modified_at": "2026-08-29T09:00:00.000-04:00",
      "content_status": "new",
      "is_carryover": false,
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      "key_claims": [
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          "text": "A low-rank Householder expansion finds local perturbation directions from the forward pass.",
          "source_ids": [
            "source-2026-08-29-019"
          ],
          "qualification": "The reported regularizer cost the equivalent of 2.8 PGD steps per epoch and matched stronger iterative training only within limited relative perturbation budgets, falling away beyond the local regime."
        }
      ],
      "source_ids": [
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      "tags": [
        "adversarial robustness",
        "efficient training",
        "neural networks"
      ],
      "image_url": null,
      "corrections": []
    },
    {
      "story_id": "mp-2026-08-29-018",
      "source_story_id": "tmp-sidebar-packora-crystals",
      "edition_id": "mp-2026-08-29-morning-0051",
      "edition_url": "https://themachinepress.com/edition/2026-08-29",
      "position": 20,
      "story_type": "ticker",
      "section": "research",
      "editorial_classification": "editorial",
      "headline": "The Crystal Generator Learned Packing and Lattice Together",
      "slug": "the-crystal-generator-learned-packing-and-lattice-together",
      "dek": "Packora predicts atomic coordinates and lattice geometry from molecular graphs under optional structural conditions.",
      "summary": "Packora predicts atomic coordinates and lattice geometry from molecular graphs under optional structural conditions.",
      "body_text": "Across six generation benchmarks and a shared ranking pipeline, the authors report better coverage, experimental-form recovery and convergence than tested baselines. Computational recovery is not experimental confirmation of a crystal.",
      "why_it_matters": "Packora predicts atomic coordinates and lattice geometry from molecular graphs under optional structural conditions.",
      "limitations": [
        "Computational recovery is not experimental confirmation of a crystal."
      ],
      "importance": 7,
      "canonical_url": "https://themachinepress.com/story/mp-2026-08-29-018/the-crystal-generator-learned-packing-and-lattice-together",
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      "first_published_at": "2026-08-29T09:00:00.000-04:00",
      "modified_at": "2026-08-29T09:00:00.000-04:00",
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      "carryover_reason": null,
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          "text": "Packora predicts atomic coordinates and lattice geometry from molecular graphs under optional structural conditions.",
          "source_ids": [
            "source-2026-08-29-020"
          ],
          "qualification": "Computational recovery is not experimental confirmation of a crystal."
        }
      ],
      "source_ids": [
        "source-2026-08-29-020"
      ],
      "tags": [
        "materials science",
        "generative models",
        "crystals"
      ],
      "image_url": null,
      "corrections": []
    },
    {
      "story_id": "mp-2026-08-29-019",
      "source_story_id": "tmp-sidebar-distillation-latent-traits",
      "edition_id": "mp-2026-08-29-morning-0051",
      "edition_url": "https://themachinepress.com/edition/2026-08-29",
      "position": 21,
      "story_type": "ticker",
      "section": "safety",
      "editorial_classification": "editorial",
      "headline": "More Benign-Looking Data Revealed More of the Teacher",
      "slug": "more-benign-looking-data-revealed-more-of-the-teacher",
      "dek": "Scaling off-task generated data made an induced teacher trait easier to recover in the student.",
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