AION
Opinion / analysisEvaluation & Benchmarks1 source · Oct 11, 2026

Has machine learning research gotten more "wordy"? [D]

I feel like I am unable to digest most machine learning research these days.

Key points

  • The primary reason is because I feel like they have gotten tremendously wordy.
  • Also because the papers seem to have gotten wordy, it is possible to come across some undefined (suspected) new terminology due to word usage.
  • The authors mixes colloquial conversational structure into a scientific publication "a lot of ...", "we don't feel....", "it feels like...".
  • At the same time, I feel mathematical explanation are becoming rarer in some research areas.

Sources (1)

Extractive summary: sentences quoted from the sources.

Before this

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  2. Oct 9, 2026Qwen/Qwen-Image-2.1-Turbo
  3. Oct 9, 2026Introducing Clef-omni with full multimodality, plus a faster Clef and a cheaper Clef-flash
  4. Oct 8, 2026LEGO: A Lifting-Free Approach for Exocentric-to-Egocentric Video Generation
  5. Oct 8, 2026One Block, Multiple Depths: Recurrent Vision Transformers with Depth-Programmed Experts
  6. Oct 8, 2026Scaling to Tens of Thousands of Test-Time Iterations with Loop-Native Attention Residuals

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