Papers.Data.Code

The Weekly ML Signal

Selected, not collected.

Weekly edition · Nov 02 – Nov 08 · Issue #12

Real-world agent evaluation

Long-horizon benchmarks, tool-use trajectories, and robot action labels.

Top 3 papers

  1. Proving and Improving the Platonic Representation Hypothesis with JEPAs

    It proves cross-modal JEPA encoders align up to rotation and beats 72B LMs with 42x fewer samples.

    arXivOct 29, 2026
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  2. Wave Forcing: Towards Speed-of-Light Streaming Video Generation

    It pipelines denoising with cache refresh to stream one video chunk per forward pass.

    arXivOct 31, 2026
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  3. VibeVideoBench: Evaluating Multimodal Agents on Code-Driven Video Generation

    It benchmarks autonomous code-written MP4 generation in 1-hour sandboxes with evidence-based grading across 239 tasks.

    arXivOct 27, 2026
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Top 3 repos

  1. hyz317/HairDeck

    Unlike most single-image 3D tools, it outputs hair cards, spring-bone rigs, and GLB/VRM exports together.

    GitHubOct 29, 2026
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  2. wangzan101/Mika

    Runs a cross-app Android agent entirely on-device, including background-screen execution and user handoff.

    GitHubOct 29, 2026
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  3. inclusionAI/IDM

    Uses internal EMA feature-moment matching to reach 94.25% LongText-CN in two steps.

    GitHubOct 29, 2026
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Top 3 datasets

  1. Axion1-0/axion-training-data

    Unlike mostly evaluation benchmarks, it releases 18,363 full agent-training trajectories plus 484 RL tasks with verified tool-use.

    Hugging FaceNov 2, 2026
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  2. InternRobotics/RoboAtom

    Aggregates 12 robot datasets into 100K-1M time-aligned atomic action annotations with a 500-trajectory held-out segmentation-and-description benchmark.

    Hugging FaceOct 21, 2026
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  3. google/physical-engineerings-last-exam

    Unlike recent agent benchmarks, it evaluates long-horizon engineering deliverables in realistic multi-tool CAD, BIM, and simulation workspaces.

    Hugging FaceOct 18, 2026
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The Weekly ML Signal.

Worth your time, not all of your time.

We track new ML work across papers, code, and data, then keep only the pieces worth a closer look. Selected, not collected.

Papers.Data.Code

The Weekly ML Signal

Selected, not collected.

One useful ML email a week: the papers, repos and datasets worth your attention.

Worth your time, not all of your time.