Academia

New York, New York

New York University

NYU is where the field gets audited: benchmarks that expose what models cannot do, and the convolutional groundwork that started the modern run.

3 key findings0 timeline milestones2 sources to follow

Key findings

  1. 2018

    GLUE and SuperGLUE

    Wang, Singh, Bowman et al.

    A multi-task benchmark suite for language understanding, replaced within two years by a harder version because models saturated it.

    Why it matters here · The saturation cycle we now watch quarter by quarter in the change feed.

    Human baseline passed in ~18 months
  2. 1989

    Convolutional networks and backpropagation for digits

    Yann LeCun and collaborators

    Trained a convolutional network end-to-end on handwritten digits, deployed to read bank cheques at scale.

    Why it matters here · The first commercially deployed deep network — the proof the whole industry was built on.

  3. 2015

    SNLI — inference at dataset scale

    Bowman, Angeli, Potts, Manning

    570,000 human-written sentence pairs labelled for entailment, contradiction or neutrality.

    Why it matters here · Made reasoning measurable before models could reason; still a probe for hallucination behaviour.

    570k labelled pairs

What to follow

How to cite this page

Free to cite and reuse under CC BY 4.0. Permalink: https://tomorrow.aliensquad.ai/academia/nyu

APA
Tomorrow. (2026). New York University — key findings and research feeds [Research tracker entry]. AlienSquad. Retrieved 2026-09-13, from https://tomorrow.aliensquad.ai/academia/nyu
BibTeX
@misc{tomorrow-academia-nyu,
  author       = {{Tomorrow}},
  title        = {New York University — key findings and research feeds},
  year         = {2026},
  publisher    = {AlienSquad},
  howpublished = {\url{https://tomorrow.aliensquad.ai/academia/nyu}},
  note         = {Accessed: 2026-09-13}
}