Papers.Data.Code

The Weekly ML Signal

Selected, not collected.

Week 27 · 2026

Jun 29 – Jul 05

20 papers, repos and datasets selected this week.

Papers

Picked Jul 3

Picked Jul 2

Picked Jul 1

Picked Jun 30

Picked Jun 29

Repos

Picked Jul 3

  • Repo
    xiaobiaodu/Flux-GS

    Unlike most 3DGS repos, it exports compressed scenes as JSON for mobile/WebGL decoding.

    GitHubJun 30, 2026
    →

Picked Jul 2

  • Repo
    Yoonkyo/mu0

    Unlike action-token VLAs, it predicts embodiment-agnostic future 3D interaction traces pretrainable from video alone.

    GitHubJun 28, 2026
    →

Picked Jul 1

  • Repo
    wanshuiyin/Anti-Autoresearch

    Uses 46 verdict-bearing integrity patterns with deterministic adjudication; eval reports 100% recall on 7 injected deterministic defects with no clean false positives.

    GitHubJun 26, 2026
    →

Picked Jun 30

  • Repo
    davnords/HardMatch

    Provides 1,000 hand-annotated hard pairs, including 900 test and 100 validation pairs, for stress-testing image matching methods.

    GitHubJun 27, 2026
    →

Picked Jun 29

  • Repo
    deepseek-ai/DeepSpec

    Unlike single-method decoding repos, it unifies data prep, multi-GPU training, and evaluation across DSpark, DFlash, Eagle3, and four target-model setups.

    GitHubJun 26, 2026
    →

Datasets

Picked Jul 3

  • Dataset
    MAIR-Lab-HUST/SciIR-82k

    It pairs 82k scientific figures with three-part reasoning annotations and full CC-BY provenance.

    Hugging FaceJun 24, 2026
    →

Picked Jul 2

Picked Jul 1

  • Dataset
    Voxel51/SceneFun3D

    Combines 710 Faro-scanned indoor scenes with part-level affordances, motion, language, and 2D/3D correspondences.

    Hugging FaceJun 29, 2026
    →

Picked Jun 30

Picked Jun 29

  • Dataset
    nvidia/Cosmos3-DROID

    Unlike single-lab teleoperation sets, it spans 71.9K episodes across 564 scenes and 86 tasks.

    Hugging FaceJun 25, 2026
    →

One useful ML email a week.

The Weekly ML Signal.

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.