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researcher

Yann LeCun

44 papers hereh-index 224.6k citations47 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author34
  • last author6

Across the 40 of 44 papers where every author was matched, so the position is known.

fields
  • cs.LG16
  • cs.CV14
  • cs.AI7
  • cs.CL4
  • cs.SD2
  • eess.AS1
same name
  • Yann LeCun — 140 papers, h 139
  • Yann LeCun — 43 papers, h 12
  • Yann LeCun — 8 papers, h 8
  • Yann LeCun — 2 papers
  • Yann LeCun — 1 paper, h 1
  • Yann LeCun — 1 paper

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20242026
most citedG-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering

22 citations · 107 across the 37 of their papers we have counts for

collaborators
Showing 2026 · cs.AIShow all

4 papers · 2 filters

cs.AI2026

The Spike, the Sparse and the Sink: Anatomy of Massive Activations and Attention Sinks

Shangwen Sun, Alfredo Canziani, Yann LeCun +1

We study two recurring phenomena in Transformer language models: massive activations, in which a small number of tokens exhibit extreme outliers in a few channels, and attention si…

cs.AI2026

AI+HW 2035: Shaping the Next Decade

Deming Chen, Jason Cong, Azalia Mirhoseini +27

Artificial intelligence (AI) and hardware (HW) are advancing at unprecedented rates, yet their trajectories have become inseparably intertwined. The global research community lacks…

cs.AI2026★ 1 cited

AI Must Embrace Specialization via Superhuman Adaptable Intelligence

Judah Goldfeder, Philippe Wyder, Yann LeCun +1

Everyone from AI executives and researchers to doomsayers, politicians, and activists is talking about Artificial General Intelligence (AGI). Yet, they often don't seem to agree on…

cs.AI2026

Learning Latent Action World Models In The Wild

Quentin Garrido, Tushar Nagarajan, Basile Terver +3

Agents capable of reasoning and planning in the real world require the ability of predicting the consequences of their actions. While world models possess this capability, they mos…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.